diff --git a/assets/images/help/copilot/example_beautiful_soup.png b/assets/images/help/copilot/example_beautiful_soup.png
new file mode 100644
index 0000000000..e81f7c155a
Binary files /dev/null and b/assets/images/help/copilot/example_beautiful_soup.png differ
diff --git a/assets/images/help/copilot/example_greek.png b/assets/images/help/copilot/example_greek.png
new file mode 100644
index 0000000000..7138c0602f
Binary files /dev/null and b/assets/images/help/copilot/example_greek.png differ
diff --git a/assets/images/help/copilot/example_last_straw.png b/assets/images/help/copilot/example_last_straw.png
new file mode 100644
index 0000000000..70c4e8fe5c
Binary files /dev/null and b/assets/images/help/copilot/example_last_straw.png differ
diff --git a/assets/images/help/copilot/example_repetitions.png b/assets/images/help/copilot/example_repetitions.png
new file mode 100644
index 0000000000..5a8ce6eb40
Binary files /dev/null and b/assets/images/help/copilot/example_repetitions.png differ
diff --git a/assets/images/help/copilot/example_robot.png b/assets/images/help/copilot/example_robot.png
new file mode 100644
index 0000000000..e6173faf63
Binary files /dev/null and b/assets/images/help/copilot/example_robot.png differ
diff --git a/assets/images/help/copilot/matched_snippets.csv b/assets/images/help/copilot/matched_snippets.csv
new file mode 100644
index 0000000000..7c83713aa5
--- /dev/null
+++ b/assets/images/help/copilot/matched_snippets.csv
@@ -0,0 +1,3408 @@
+;example_id;matching_part_of_suggestion;number_of_tokens_in_matching_part_of_suggestion;number_of_matches;link_to_example_match;number_of_lines_of_context
+1;efa667297f49ca5065e12e0a9743445e00ebd1c2;"x, y, u, v = 0, 1, 1, 0
+    while a != 0:
+        q, r = b // a, b % a
+        m, n = x - u * q, y - v * q
+        b, a, x, y, u, v = a, r, u, v, m, n";71;2;https://github.com/remifuhriman/numerical_computing/blob/master/Labs/RSA/solutions.py;2
+2;c101dc6dd83eca9260fbfc0369979a7965240df4;\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\;97;1;https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py;>7
+3;c101dc6dd83eca9260fbfc0369979a7965240df4;\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+;99;1;https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py;>7
+4;c101dc6dd83eca9260fbfc0369979a7965240df4;\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\;100;1;https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py;>7
+5;7f55777d22c616ae337c2f440e38ddb311907824;\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)',;98;1;https://github.com/dvdylus/treeCl/blob/master/bin/fast_run_raxml.py;>7
+6;5d7d7b9e5d18d271ba8065b57b63c11aa62650e4;")       
+    def forward(self, x):       
+        x = self.pool(F.relu(self.conv1(x)))       
+        x = self.pool(F.relu(self.conv2(x)))       
+        x = x.view(-1, 16 * 5 * 5)       
+        x = F.relu(self.fc1(x))       
+        x =";75;6;https://github.com/strongio/cerbero/blob/master/examples/cifar10_example/cifar10_multitask.py;4
+7;5d7d7b9e5d18d271ba8065b57b63c11aa62650e4;")       
+    def forward(self, x):       
+        x = self.pool(F.relu(self.conv1(x)))       
+        x = self.pool(F.relu(self.conv2(x)))       
+        x = x.view(-1, 16 * 5 * 5)       
+        x = F.relu(self.fc1(x))       
+        x =";75;6;https://github.com/strongio/cerbero/blob/master/examples/cifar10_example/cifar10_multitask.py;4
+8;8fe8dc24f5255aaa660568e64cf3489b795ed621;")
+    stock_data = []
+    split_source = source_code.split('\n')
+    for line in split_source:
+        split_line = line.split(',')
+        if len(split_line) == 6:
+            if 'values' not in line and 'labels' not in line:
+                stock_data.append(line)";61;2;https://github.com/DIS17JTH/displayPiProject/blob/master/data_from_internet.py;>7
+9;f72768d35a1bfee78c27a8c920ca4a80b27f719b;of the following questions (which you may assume is evaluated independently of the previous questions, so that testList has the value indicated above), provide an expression using applyToEach, so that after evaluation testList has the indicated value. You may need to write a simple procedure in each question to help with this process.;60;1;https://github.com/kd-nguyen/guttag/blob/master/6.00.1x/w5-apply_to_each.py;1
+10;13af40cbffd29607178688e4f935be6af655d203;B/C/D/E/F/G/H/I/J/K/L/M/N/O/P/Q/R/S/T/U/V/W/X/Y/Z/0/1/2/3/4/5/6/7/8/9/;70;2;https://github.com/IronLanguages/ironpython3/blob/master/Tests/test_stdmodules.py;1
+11;9ceada1552a2619b2ecd33e07321e0e5e45663b8;", cv2.COLOR_BGR2GRAY)
+    gray = cv2.GaussianBlur(gray, (21, 21), 0)
+
+    # if the first frame is None, initialize it
+    if firstFrame is None:
+        firstFrame = gray
+        continue
+
+    # compute the absolute difference between the current frame and
+    # first frame
+    frameDelta = cv2.absdiff(firstFrame, gray)
+    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
+
+    # dilate the thresholded image to fill in holes, then find contours
+    # on thresholded image
+    thresh = cv2.dilate(thresh, None, iterations=2)
+    cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
+                            cv2.CHAIN_APPROX_SIMPLE)
+    cnts = cnts[0] if imutils.is_cv2() else cnts[1]
+
+    # loop over the contours
+    for c in cnts:
+        # if the contour is too small, ignore it
+        if cv2.contourArea(c) < args[""min_area""]:
+            continue
+
+        # compute the bounding box for the contour, draw it on the frame,
+        # and update the text
+        (x, y, w, h) = cv2.boundingRect(c)
+        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+        text = """;257;16;https://github.com/nishantpoorswani/motion_detection/blob/master/motion_detector.py;1
+12;10035a5ef46e05f698fced88ff6a520b1fda6943;"k, a, b, a1, b1 = 2, 4, 1, 12, 4
+    while True:
+        p, q, k = k*k, 2*k+1, k+1
+        a, b, a1, b1 = a1, b1, p*a+q*a1, p*b+q*b1
+        d, d1 = a/";74;3;https://github.com/fmasanori/PPZ/blob/master/pi generator.py;>7
+13;10035a5ef46e05f698fced88ff6a520b1fda6943;"k, a, b, a1, b1 = 2, 4, 1, 12, 4
+    while True:
+        p, q, k = k*k, 2*k+1, k+1
+        a, b, a1, b1 = a1, b1, p*a+q*a1, p*b+q*b1
+        d, d1 = a/";74;3;https://github.com/fmasanori/PPZ/blob/master/pi generator.py;>7
+14;10035a5ef46e05f698fced88ff6a520b1fda6943;"k, a, b, a1, b1 = 2, 4, 1, 12, 4
+    while True:
+        p, q, k = k*k, 2*k+1, k+1
+        a, b, a1, b1 = a1, b1, p*a+q*a1, p*b+q*b1
+        d, d1 = a/";74;3;https://github.com/fmasanori/PPZ/blob/master/pi generator.py;>7
+15;87d22e982aec01dbba1e64a84b0937cad199bda8;q, r, t, k, m, x = 10*q, 10*(r-m*t), t, k, (10*(3*q+r))//t - 10*m, x;50;1;https://github.com/steven-cutting/maths/blob/master/maths/otherpie.py;>7
+16;87d22e982aec01dbba1e64a84b0937cad199bda8;q, r, t, k, m, x = q*k, (2*q+r)*x, t*x, k+1, (q*(7*k+2)+r*x)//(t*x), x+2;60;1;https://github.com/steven-cutting/maths/blob/master/maths/otherpie.py;>7
+17;a4c3d2c979c489e47c250f5fd3402328044f19fa;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2
+    c = 2 * asin(sqrt(a))
+    km = 6367 * c
+    return km";113;5;https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py;6
+18;2c50c483254cf60b00a276cd01eb5a5f4ae91bdc;"dlat = radians(lat2 - lat1)
+    dlon = radians(lon2 - lon1)
+    a = sin(dlat / 2) * sin(dlat / 2) + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) * sin(dlon / 2)
+    c = 2 * atan2(sqrt(a), sqrt(1 - a))";79;3;https://github.com/kyb3r/majorproject/blob/master/server/core/route_generation.py;6
+19;8c76f07cfbfa90928d72dcf76029b44d8e9eb21c;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+    c = 2 * asin(sqrt(a))
+    r = 6371 # Radius of earth in kilometers. Use 3956 for miles
+    return c * r";124;6;https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py;6
+20;a4c3d2c979c489e47c250f5fd3402328044f19fa;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+    c = 2 * asin(sqrt(a))
+    km = 6367 * c
+    return km";113;5;https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py;6
+21;8c76f07cfbfa90928d72dcf76029b44d8e9eb21c;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2
+    c = 2 * asin(sqrt(a))
+    r = 6371  # Radius of earth in kilometers. Use 3956 for miles
+    return c * r";124;6;https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py;6
+22;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+23;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+24;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+25;023ba10b2acf76024e495c08ef92741a5c95480b;"print(16)
+    print(17)
+    print(18)
+    print(19)
+    print(20)
+    print(21)
+    print(22)
+    print(23)
+    print(24)
+    print(25)
+    print(26)
+    print(27)
+    print(28)
+    print(29)
+    print(30)";60;1;https://github.com/raoniteixeira/algoritmos_te/blob/master/unidade_4/2.py;>7
+26;16be96e3c6cc6ac83349eee9632bb7f9765e99e8;"a = 1
+    b = 2
+    c = 3
+    d = 4
+    e = 5
+    f = 6
+    g = 7
+    h = 8
+    i = 9
+    j = 10
+    k = 11
+    l = 12
+    m = 13
+    n = 14
+    o = 15
+    p = 16
+    q = 17
+    r = 18
+    s = 19
+    t = 20
+    u = 21
+    v = 22
+    w = 23
+    x = 24
+    y = 25
+    z = 26";78;2;https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py;>7
+27;16be96e3c6cc6ac83349eee9632bb7f9765e99e8;"a = 1
+    b = 2
+    c = 3
+    d = 4
+    e = 5
+    f = 6
+    g = 7
+    h = 8
+    i = 9
+    j = 10
+    k = 11
+    l = 12
+    m = 13
+    n = 14
+    o = 15
+    p = 16
+    q = 17
+    r = 18
+    s = 19
+    t = 20
+    u = 21
+    v = 22
+    w = 23
+    x = 24
+    y = 25
+    z = 26";78;2;https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py;>7
+28;8ea4e63c0d203860c4f59de75d87344671a383ec;/query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22nome%2C%20ak%22)&format=json&env=store%3A%;72;2;https://github.com/sirinenisaikiran/Python/blob/master/Traning/PyQs-master/PyQs-master/python-initial-reference/ToBeShared/reference/Code/web/flask/weather.py;>7
+29;6b5df31137bd436722936c6357a8dfe955215a86;"Return a list of all items in this linked list.
+        Best and worst case running time: Theta(n) for n items in the list
+        because we always need to loop through all n nodes.""""""
+        # Create an empty list of results
+        result = []  # Constant time to create a new list
+        # Start at the head node
+        node = self.head  # Constant time";75;2;https://github.com/asha952/cs-1.3_algorithms/blob/master/linked_list.py;2
+30;6b5df31137bd436722936c6357a8dfe955215a86;"Return a list of all items in this linked list.
+        Best and worst case running time: Theta(n) for n items in the list
+        because we always need to loop through all n nodes.""""""
+        # Create an empty list of results
+        result = []  # Constant time to create a new list
+        # Start at the head node
+        node = self.head";72;2;https://github.com/asha952/cs-1.3_algorithms/blob/master/linked_list.py;4
+31;5d1cabb5ea56ef3ac8607c9ea420c56678ae6e7b;,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,;81;2;https://github.com/JulienAndres/p_androidKilobot/blob/master/mEDEA/stats_robot/test.py;>7
+32;aa914b233c39f2bba9f9ca3425eb0adb631a43fc;")
+    response.raise_for_status()
+
+    analysis = response.json()
+
+    # Extract the word bounding boxes and text.
+    line_infos = [region[""lines""] for region in analysis[""regions""]]
+    word_infos = []
+    for line in line_infos:
+        for word_metadata in line:
+            for word_info in word_metadata[""words""]:
+                word_infos.append(word_info)";71;5;https://github.com/pziajski/ZRecognition/blob/master/AzureImageRecognition.py;>7
+33;c94cf9a0235e7137f88385ab5c88ae6369e736c8;"headers  = {'Ocp-Apim-Subscription-Key': subscription_key, 'Content-Type': 'application/octet-stream'}
+    params   = {'language': 'unk', 'detectOrientation ': 'true'}
+    data     = {'url': image_url}
+    response = requests.post(";63;3;https://github.com/aayushvats/med_id/blob/master/ocr.py;>7
+34;00f38ab64ac06074049b0dde2efdba6d52214313;"image_data = open(image_path, ""rb"").read()
+
+    headers  = {'Ocp-Apim-Subscription-Key': subscription_key,
+                'Content-Type': 'application/octet-stream'}
+    params   = {'visualFeatures': 'Categories,Description,Color'}
+    response = requests.post(analyze_url, headers=headers, params=params, data=image_data)
+    response.raise_for_status()
+
+    # The 'analysis' object contains various fields that describe the image. The most
+    # relevant caption for the image is obtained from the 'description' property.
+    analysis = response.json()
+    image_caption = analysis[""description""][""captions""][0][""text""].capitalize()";146;6;https://github.com/vishnoitanuj/Azure-tutorials/blob/master/Video_Analysis.py;>7
+35;910dc45b477682df33a75979ecb8932612776c35;"""
+
+    image_data = open(image_path, ""rb"").read()
+
+    headers  = {'Ocp-Apim-Subscription-Key': subscription_key,
+                'Content-Type': 'application/octet-stream'}
+    params   = {'visualFeatures': 'Categories,Description,Color'}
+    response = requests.post(
+        analyze_url, headers=headers, params=params, data=image_data)
+    response.raise_for_status()
+
+    analysis = response.json()";91;4;https://github.com/nrjvarshney/QuoteFromPic/blob/master/quotesServer/quotesServer/quoteapi/views.py;>7
+36;f0bc867888c48e59d98da85a88da423465d13d10;"vision_base_url = ""https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/""
+
+    ocr_url = vision_base_url + ""ocr""
+
+    headers  = {'Ocp-Apim-Subscription-Key': subscription_key, 'Content-Type': 'application/octet-stream'}
+    params   = {'language': 'unk', 'detectOrientation': 'true'}";79;3;https://github.com/Ujjwal0501/hallucinators/blob/master/Text_Gen.py;>7
+37;02fce827f849a37fd59ba18a70852fa1bca546af;")
+    response.raise_for_status()
+
+    analysis = response.json()
+
+    # Extract the word bounding boxes and text.
+    line_infos = [region[""lines""] for region in analysis[""regions""]]
+    word_infos = []
+    for line in line_infos:
+        for word_metadata in line:
+            for word_info in word_metadata[""words""]:
+                word_infos.append(word_info)";71;3;https://github.com/WeiShi78/Xbuyer/blob/master/test/Test.py;>7
+38;910dc45b477682df33a75979ecb8932612776c35;"assert subscription_key
+
+    vision_base_url = ""https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/""
+
+    analyze_url = vision_base_url + ""analyze""
+
+    image_data = open(image_path, ""rb"").read()
+    headers = {'Ocp-Apim-Subscription-Key': subscription_key,
+                'Content-Type': 'application/octet-stream'}
+    params = {'visualFeatures': 'Categories,Description,Color'}
+    response = requests.post(analyze_url, headers=headers, params=params, data=image_data)
+    response.raise_for_status()
+    analysis = response.json()";123;5;https://github.com/nrjvarshney/QuoteFromPic/blob/master/quotesServer/quotesServer/quoteapi/views.py;>7
+39;f75875be86f0f17fc3e9aae98f743f02982e444a;"= [""2000"", ""2001"", ""2002"", ""2003"", ""2004"", ""2005"", ""2006"", ""2007"", ""2008"", ""2009"", ""2010"", ""2011"", ""2012"", ""2013"",
+             ""2014"", ""2015"", ""2016"", ""2017""]";74;2;https://github.com/DaviPolita/Dashboards/blob/master/Plotly_Graphs/Animated_Scatter/gender_ineq.py;>7
+40;876ad13e615cda2592f907c2739e09faa21477d4;"""2016"", ""2015"", ""2014"", ""2013"", ""2012"", ""2011"", ""2010"", ""2009"", ""2008"", ""2007"", ""2006"", ""2005"", ""2004"", ""2003"", ""2002"", ""2001"", ""2000"", ""1999"", ""1998"", ""1997""";79;2;https://github.com/abhinavbansal19961996/Advocatefinal/blob/master/update.py;>7
+41;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+42;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+43;5e9c280ba82bbe9237fe3f8dff0c82dce3bdcf5e;"):
+    less = []
+    equal = []
+    greater = []
+
+    if len(array) > 1:
+        pivot = array[0]
+        for x in array:
+            if x < pivot:
+                less.append(x)
+            if x == pivot:
+                equal.append(x)
+            if x > pivot:
+                greater.append(x)
+        return";68;2;https://github.com/morganhowell95/Algorithms/blob/master/Comparison-Sorts/quick_sort.py;2
+44;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+45;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+46;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+47;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+48;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+49;21f646e28b5aa5d074688a587f8cc16d2d05a5b0;"a):
+    if len(a) <= 1:
+        return a
+    pivot = a[len(a) // 2]
+    left = [x for x in a if x < pivot]
+    middle = [x for x in a if x == pivot]
+    right = [x for x in a if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;2;https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py;2
+50;2edbc61bf0f23c785b94c3dd6b178bbc94127f35;"lista):
+    if len(lista) <= 1:
+        return lista
+    pivo = lista[0]
+    iguais  = [x for x in lista if x == pivo]
+    menores = [x for x in lista if x <  pivo]
+    maiores = [x for x in lista if x >  pivo]
+    return quicksort(menores) +";66;3;https://github.com/AAMergulhao/Sort_Algorithms/blob/master/algorithms.py;2
+51;7457f881c1b82d80957b8acf1859a4a73a7e88b4;"array):
+    if len(array) <= 1:
+        return array
+    pivot = array[len(array) // 2]
+    left = [x for x in array if x < pivot]
+    middle = [x for x in array if x == pivot]
+    right = [x for x in array if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;4;https://github.com/fali007/basic-programming/blob/master/sorting/quicksort.py;2
+52;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+	if len(arr) <= 1:
+		return arr
+	pivot = arr[len(arr) / 2]
+	left = [x for x in arr if x < pivot]
+	middle = [x for x in arr if x == pivot]
+	right = [x for x in arr if x > pivot]
+	return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+53;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+54;7457f881c1b82d80957b8acf1859a4a73a7e88b4;"array):
+    if len(array) <= 1:
+        return array
+    pivot = array[len(array) // 2]
+    left = [x for x in array if x < pivot]
+    middle = [x for x in array if x == pivot]
+    right = [x for x in array if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;4;https://github.com/fali007/basic-programming/blob/master/sorting/quicksort.py;2
+55;d730f06e052b92b5241b0feb5b7436ad708f79b1;"arr):
+    if len(arr) <= 1:
+        return arr
+    else:
+        pivot = arr[len(arr) / 2]
+        left = [x for x in arr if x < pivot]
+        middle = [x for x in arr if x == pivot]
+        right = [x for x in arr if x > pivot]
+        return quicksort(left) + middle + quicksort(right)";79;6;https://github.com/yvprashanth/python-google-tutorial/blob/master/basic/quicksort.py;2
+56;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+57;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+58;be05fb926bf6d0f5b10addd65a7bd26bf41a466e;"# Plot the decision boundary. For that, we will assign a color to each
+    # point in the mesh [x_min, x_max]x[y_min, y_max].
+    x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
+    y_min, y_max = X[:, 1].min() - .5, X[:, 1].";89;2;https://github.com/mszhai/nlp_algo/blob/master/test/pd.py;1
+59;c054698149636d13ae8ad1ed97459812d0d1ebbc;"fig = plt.figure()
+    ax = fig.add_subplot(111, projection='3d')
+    n = 100
+    for c, m, zl, zh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:
+        xs = randrange(n, 23, 32)
+        ys = randrange(n, 0, 100)
+        zs = randrange(n, zl, zh)
+        ax.scatter(xs, ys, zs, c=c, marker=m)";115;5;https://github.com/afding/mylab/blob/master/algrithm/3dplot.demo.py;0
+60;f4e6dcf3008410acb9d95b2ba78645b12f5eebf8;"]x[y_min, y_max].
+    x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5
+    y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5
+    xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
+    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
+
+    # Put the result into a color plot
+    Z = Z.reshape(xx.shape)
+    pl.figure(1, figsize=(4, 3))
+    pl.pcolormesh(xx, yy, Z, cmap=pl.cm.Paired)
+
+    # Plot also the training points
+    pl.scatter(X[:, 0], X[:, 1], c=Y,
+⋯
+, cmap=pl.cm.Paired)
+    pl.xlabel('Sepal length')
+    pl.ylabel('Sepal width')
+
+    pl.xlim(xx.min(), xx.max())
+    pl.ylim(yy.min(), yy.max())
+    pl.xticks(())
+    pl.yticks(())
+
+    pl.show()";279;14;https://github.com/v3ss0n/scikit-learn/blob/master/examples/svm/plot_svm_iris.py;0
+61;a80fef7436689974cff2664b4a0e8160c74a06a2;"from matplotlib import rc
+    rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
+    ## for Palatino and other serif fonts use:
+    #rc('font',**{'family':'serif','serif':['Palatino']})
+    rc('text', usetex=True)";85;5;https://github.com/kmandli/ML-python-code-without-LIBRARIES/blob/master/linear_regression_cost_function.py;0
+62;c690d3284caf91996572b047fbe5425c93d8e25e;"')
+
+    # Data for three-dimensional scattered points
+    zdata = 15 * np.random.random(100)
+    xdata = np.sin(zdata) + 0.1 * np.random.randn(100)
+    ydata = np.cos(zdata) + 0.1 * np.random.randn(100)
+    ax.scatter3D(xdata, ydata, zdata, c=zdata, cmap='";81;3;https://github.com/TheRealMarcusChiu/PythonMasterExample/blob/master/src/third-party/03_graphs/3d/scatter.py;0
+63;9303cf4b43f8b33a958f1b0025bd2a07f2798e80;"# Importing the dataset
+    dataset = pd.read_csv('Social_Network_Ads.csv')
+    X = dataset.iloc[:, [2, 3]].values
+    y = dataset.iloc[:, 4].values
+
+    # Splitting the dataset into the Training set and Test set
+    from sklearn.cross_validation import train_test_split
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0)
+
+    # Feature Scaling
+    from sklearn.preprocessing import StandardScaler
+    sc = StandardScaler()
+    X_train = sc.fit_transform(X_train)
+    X_test = sc.transform(X_test)
+
+    # Fitting classifier to the Training set
+    from sklearn.svm import SVC
+    classifier = SVC(kernel = 'linear', random_state = 0)
+    classifier.fit(X_train, y_train)
+
+    # Predicting the Test set results
+    y_pred = classifier.predict(X_test)
+
+    # Making the Confusion Matrix
+    from sklearn.metrics import confusion_matrix
+    cm = confusion_matrix(y_test, y_pred)
+
+    # Visualising the Training set results
+    from matplotlib.colors import ListedColormap
+    X_set, y_set = X_train, y_train
+    X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01),
+                         np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01))
+    plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape),
+                 alpha = 0.75, cmap =";341;22;https://github.com/ranasingh-gkp/Machine-Learning/blob/master/Part 3 - Classification/Section 16 - Support Vector Machine (SVM)/Python_SVM.py;0
+64;5e9c280ba82bbe9237fe3f8dff0c82dce3bdcf5e;"):
+    less = []
+    equal = []
+    greater = []
+    if len(array) > 1:
+        pivot = array[0]
+        for x in array:
+            if x < pivot:
+                less.append(x)
+            if x == pivot:
+                equal.append(x)
+            if x > pivot:
+                greater.append(x)
+        return";68;2;https://github.com/morganhowell95/Algorithms/blob/master/Comparison-Sorts/quick_sort.py;2
+65;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+66;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+67;68813c1284352872db9a5abdaaaabf8c8e21c16d;['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DWDP','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX',';106;3;https://github.com/parsa3000/SE18/blob/master/stockgame2/home/listofstockscrypto.py;>7
+68;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+69;3a162697d1abaa9ffb4d3f14ff97828c642ea427;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';99;2;https://github.com/quentintruong/Stocks-Scraper/blob/master/stocks/spiders/stocks_spider.py;>7
+70;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+71;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+72;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+73;886bc47941eadd52a758206094854c8505d85410;', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z';101;5;https://github.com/andrewmagis/docker/blob/master/ipython-dev/Qiime/qiime/split_libraries_fastq.py;0
+74;5b2bf24b4ae3a8c68dc4e52c1e5bdca89af216c4;= {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6, 7:7, 8:8, 9:9, 10:10, 11:11, 12:12, 13:13, 14:14, 15:15, 16:16, 17:17, 18:18, 19:19, 20:20, 21:21, 22:22, 23:23, 24:;100;3;https://github.com/cnrat/dec-eve-serenity/blob/master/client/encodings/cp864.py;1
+75;5b2bf24b4ae3a8c68dc4e52c1e5bdca89af216c4;= {0:0, 1:1, 2:2, 3:3, 4:4, 5:5, 6:6, 7:7, 8:8, 9:9, 10:10, 11:11, 12:12, 13:13, 14:14, 15:15, 16:16, 17:17, 18:18, 19:19, 20:20, 21:21, 22:22, 23:23, 24:;100;3;https://github.com/cnrat/dec-eve-serenity/blob/master/client/encodings/cp864.py;1
+76;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,;96;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+77;af4b00fee4953dec519c7e35e3163f60609466dc;s[0],s[1],s[2],s[3],s[4],s[5],s[6],s[7],s[8],s[9],s[10],s[11],s[12],s[13],s[14],s[15],s[16],s[17];89;4;https://github.com/wjwainwright/Capstone/blob/master/IsoFitv18.py;>7
+78;eb3ae194c4c2eb8719db5c353485c3e31831f1ac;"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"",
+                          tuple(";64;4;https://github.com/labopvlab/PythonDataAnalyzer/blob/master/apps/mergingDBs_v1.py;>7
+79;8f0abf15d48fe3c7357ed453ba8bb45dbd536d07;"lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2
+    c = 2 * asin(sqrt(a))
+    r = 6371
+    return c * r * 1000";83;6;https://github.com/TimothyLx/Mining-method-based-on-semantic-trajectory-frequent-pattern-and-carpooling-application/blob/master/distance_calculate.py;6
+80;a4c3d2c979c489e47c250f5fd3402328044f19fa;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+    c = 2 * asin(sqrt(a))
+    km = 6367 * c
+    return km";113;5;https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py;6
+81;a4c3d2c979c489e47c250f5fd3402328044f19fa;"""""""
+    Calculate the great circle distance between two points
+    on the earth (specified in decimal degrees)
+    """"""
+    # convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+    c = 2 * asin(sqrt(a))
+    km = 6367 * c
+    return km";113;5;https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py;6
+82;8c76f07cfbfa90928d72dcf76029b44d8e9eb21c;"# convert decimal degrees to radians
+    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
+
+    # haversine formula
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2
+    c = 2 * asin(sqrt(a))
+    r = 6371  # Radius of earth in kilometers. Use 3956 for miles
+    return c * r";101;5;https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py;6
+83;b3326f25c405bab05ae8898a978dcd1bb27358b0;"parser = argparse.ArgumentParser(description='PyTorch CIFAR10 Training')
+    parser.add_argument('--lr', default=0.1, type=float, help='learning rate')
+    parser.add_argument('--resume', '-r', action='store_true', help='resume from checkpoint')
+    args = parser.parse_args()";77;5;https://github.com/THULimy/pytorch-Hscore/blob/master/cifar-resnet.py;1
+84;21f646e28b5aa5d074688a587f8cc16d2d05a5b0;"a):
+    if len(a) <= 1:
+        return a
+    pivot = a[len(a) // 2]
+    left = [x for x in a if x < pivot]
+    middle = [x for x in a if x == pivot]
+    right = [x for x in a if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;2;https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py;1
+85;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+86;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+87;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+88;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+89;fde8fae9d13625d97b7d39342bbc9100a42cf8d9;= ['Date/Time', 'Temp (°C)', 'Dew Point Temp (°C)', 'Rel Hum (%)', 'Wind Dir (10s deg)', 'Wind Spd (km/h)', 'Visibility (km)', 'Stn Press (kPa)', ';69;4;https://github.com/patrickacheung/weather-tod-predictor/blob/master/clean_weather.py;>7
+90;f2ed15c0121fc4d4ab8d3c0c87c3c745aa05853f;= ['Date/Time', 'Year', 'Month', 'Day', 'Time', 'Data Quality', 'Temp (°C)', 'Temp Flag', 'Dew Point Temp (°C)', 'Dew Point Temp Flag', 'Rel Hum (%)', 'Rel Hum Flag', 'Wind Dir;76;3;https://github.com/iss4e/webike-toolchain/blob/master/webike/data/WeatherGC.py;>7
+91;8288745b3d457294b33551ac7a3d6d8d391c44fa;"headers = {
+        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36'
+    }
+    response = requests.get(url, headers=headers)";65;2;https://github.com/ZhekunInc/football-wiki/blob/master/src/scraping/management/commands/fifa_country.py;4
+92;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+93;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+94;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+95;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr)/2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";77;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+96;47081907e60f9f9cab0effee35db245a5b7003a6;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+97;47081907e60f9f9cab0effee35db245a5b7003a6;":
+    if len(arr) <= 1 :
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";76;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+98;47081907e60f9f9cab0effee35db245a5b7003a6;":
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";76;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+99;47081907e60f9f9cab0effee35db245a5b7003a6;":
+	if len(arr) <= 1 :
+		return arr
+	pivot = arr[len(arr) // 2]
+	left = [x for x in arr if x < pivot]
+	middle = [x for x in arr if x == pivot]
+	right = [x for x in arr if x > pivot]
+	return quicksort(left) + middle + quicksort(right)";76;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+100;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";74;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+101;47081907e60f9f9cab0effee35db245a5b7003a6;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";75;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+102;47081907e60f9f9cab0effee35db245a5b7003a6;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";75;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+103;47081907e60f9f9cab0effee35db245a5b7003a6;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";75;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;1
+104;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";74;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;1
+105;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49;97;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;4
+106;43d142060c012adf5436e71991f17b8e81168311;[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,;439;1;https://github.com/youngminpark2559/temp_for_study/blob/master/study_huggingface_NLP/examples/My_test/Test_BERT_LM_model.py;1
+107;9ebe0da4eabfbbd56a5cdd9704fb6c3872162936;"Config(object):
+    SECRET_KEY = os.environ.get('SECRET_KEY') or 'you-will-never-guess'
+    SQLALCHEMY_DATABASE_URI = os.environ.get('DATABASE_URL') or \
+        'sqlite:///' + os.path.join(basedir, 'app.db')
+    SQLALCHEMY_TRACK_MODIFICATIONS = False
+    MAIL_SERVER = os.environ.get('MAIL_SERVER')
+    MAIL_PORT = int(os.environ.get('MAIL_PORT') or 25)
+    MAIL_USE_TLS = os.environ.get('MAIL_USE_TLS') is not None
+    MAIL_USERNAME = os.environ.get('MAIL_USERNAME')
+    MAIL_PASSWORD = os.environ.get(";130;4;https://github.com/vitalii-levko/microblog/blob/master/microblog/config.py;2
+108;9ebe0da4eabfbbd56a5cdd9704fb6c3872162936;"Config(object):
+    SECRET_KEY = os.environ.get('SECRET_KEY') or 'you-will-never-guess'
+    SQLALCHEMY_DATABASE_URI = os.environ.get('DATABASE_URL') or \
+        'sqlite:///' + os.path.join(basedir, 'app.db')
+    SQLALCHEMY_TRACK_MODIFICATIONS = False
+    MAIL_SERVER = os.environ.get('MAIL_SERVER')
+    MAIL_PORT = int(os.environ.get('MAIL_PORT') or 25)
+    MAIL_USE_TLS = os.environ.get('MAIL_USE_TLS') is not None
+    MAIL_USERNAME = os.environ.get('MAIL_USERNAME')
+    MAIL_PASSWORD = os.environ.get(";130;4;https://github.com/vitalii-levko/microblog/blob/master/microblog/config.py;2
+109;59b316cdb58c43d28de33d284ed7b8ac9bab06ba;if y != '0' and y != '1' and y != '2' and y != '3' and y != '4' and y != '5' and y != '6' and y != '7' and y != '8' and y != '9' and y != ';75;2;https://github.com/duongd08/CECS-174-Spring-2018/blob/master/Uno.py;>7
+110;8b515e8a34021fe09632bd8387ef3a9734bb1c1b;', 'AMD', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT;68;2;https://github.com/rorygwozdz/coding/blob/master/finance/gcg/image_creator.py;>7
+111;7ebb786cd066594187910cfba3b3e58c3603b02d;', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT', 'ALL', 'GOOGL', 'GOOG', 'MO', 'AMZN', 'AEE', 'AAL', 'AEP', 'AXP', 'AIG', 'AMT', 'AWK', 'AMP', 'ABC', 'AME', 'AMGN', 'APH', 'APC', 'ADI', 'ANDV', 'ANSS', 'ANTM', 'AON', 'AOS', 'APA', 'AIV', 'AAPL', 'AMAT', 'APTV', 'ADM', 'ARNC', 'AJG', 'AIZ', 'T', 'ADSK', 'ADP', 'AZO', 'AVB', 'AVY', ';223;15;https://github.com/Shiva-gs/Project3/blob/master/stock_data.py;>7
+112;7ebb786cd066594187910cfba3b3e58c3603b02d;', 'ALL', 'GOOGL', 'GOOG', 'MO', 'AMZN', 'AEE', 'AAL', 'AEP', 'AXP', 'AIG', 'AMT', 'AWK', 'AMP', 'ABC', 'AME', 'AMGN', 'APH', 'APC', 'ADI', 'ANDV', 'ANSS', 'ANTM', 'AON', 'AOS', 'APA', 'AIV', 'AAPL', 'AMAT', 'APTV', 'ADM', 'ARNC', 'AJG', 'AIZ', 'T', 'ADSK', 'ADP', 'AZO', 'AVB', 'AVY', 'BHGE', 'BLL', 'BAC', 'BK', 'BAX', 'BBT', 'BDX', 'BRK.B', 'BBY', 'BIIB', 'BLK', 'HRB', 'BA', 'BWA', 'BXP', 'BSX',;224;10;https://github.com/Shiva-gs/Project3/blob/master/stock_data.py;>7
+113;7ebb786cd066594187910cfba3b3e58c3603b02d;', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT', 'ALL', 'GOOGL', 'GOOG', 'MO', 'AMZN', 'AEE', 'AAL', 'AEP', 'AXP', 'AIG', 'AMT', 'AWK', 'AMP', 'ABC', 'AME', 'AMGN', 'APH', 'APC', 'ADI', 'ANDV', 'ANSS', 'ANTM', 'AON', 'AOS', 'APA', 'AIV', 'AAPL', 'AMAT', 'APTV', 'ADM', 'ARNC', 'AJG', 'AIZ', 'T', 'ADSK', 'ADP', 'AZO', 'AVB', 'AVY', 'BHGE', 'BLL', 'BAC', 'BK', 'BAX', 'BBT', 'BDX', 'BRK.B', 'BBY', 'BIIB', 'BLK', 'HRB', 'BA', 'BWA', 'BXP', 'BSX', 'BHF', 'BMY', 'AVGO', 'BF.B', 'CHRW', 'CA', 'COG', ';319;19;https://github.com/Shiva-gs/Project3/blob/master/stock_data.py;>7
+114;687774b16d0478f4bf1aca760b628253d21d3267;"if n == 1:
+        return False
+    elif n < 4:
+        return True
+    elif n%2 == 0:
+        return False
+    elif n < 9:
+        return True
+    elif n%3 == 0:
+        return False
+    else:
+        r = int(n**0.5)
+        f = 5
+        while f <= r:
+            if n%f == 0:
+                return False";74;3;https://github.com/redmechanic/My-Project-Euler-Solutions/blob/master/Problem 27/prime_quadratic.py;2
+115;c61d42e2a6eaf8c9c9b03d4ebc15e6a9ec999768;"print(now.strftime(""%Y-%m-%d %H:%M:%S""))
+    print(now.strftime(""%Y-%m-%d""))
+    print(now.strftime(""%H:%M:%S""))";62;2;https://github.com/contsman/pythonweb/blob/master/testpython/Commonly_used_builtin_module.py;>7
+116;964357c438769c177a2c14743aa82fa875ac2d80;",
+        ""Intended Audience :: Developers"",
+        ""License :: OSI Approved :: Apache Software License"",
+        ""Operating System :: OS Independent"",
+        ""Programming Language :: Python"",
+        ""Programming Language :: Python :: 2"",
+        ""Programming Language :: Python :: 2.7"",
+        ""Programming Language :: Python :: 3"",
+        ""Programming Language :: Python :: 3.4"",
+        ""Programming Language :: Python :: 3.5"",
+        ""Programming Language :: Python :: 3.6"",
+        ""Programming Language :: Python :: 3.7"",
+        ""Programming Language :: Python :: 3.8"",
+        """;140;8;https://github.com/da-woods/cython/blob/master/setup.py;>7
+117;964357c438769c177a2c14743aa82fa875ac2d80;""",
+        ""Programming Language :: Python :: 2.7"",
+        ""Programming Language :: Python :: 3"",
+        ""Programming Language :: Python :: 3.4"",
+        ""Programming Language :: Python :: 3.5"",
+        ""Programming Language :: Python :: 3.6"",
+        ""Programming Language :: Python :: 3.7"",
+        ""Programming Language :: Python :: 3.8"",
+        ""Programming Language :: Python :: Implementation :: CPython"",
+        ""Programming Language :: Python :: Implementation :: PyPy"",";119;6;https://github.com/da-woods/cython/blob/master/setup.py;>7
+118;1324ed920d6ad53fd3322f862703051161d16b4f;"@gmail.com"",
+    license=""MIT"",
+    classifiers=[
+        ""Development Status :: 3 - Alpha"",
+        ""Intended Audience :: Developers"",
+        ""Topic :: Software Development :: Build Tools"",
+        ""License :: OSI Approved :: MIT License"",
+        ""Programming Language :: Python :: 3";66;3;https://github.com/ylathouris/glossy/blob/master/setup.py;>7
+119;9da3365c7b91281b7073c07c495ff3033dfaa543;"(G, start, end=None):
+    """"""
+    Find shortest paths from the start vertex to all
+    vertices nearer than or equal to the end.
+
+    The input graph G is assumed to have the following
+    representation: A vertex can be any object that can
+    be used as an index into a dictionary.  G is a
+    dictionary, indexed by vertices.  For any vertex v,
+    G[v] is itself a dictionary, indexed by the neighbors
+    of v.  For any edge v->w, G[v][w] is the length of
+    the edge.  This is related to the representation in
+    <http://www.python.org/doc/essays/graphs.html>
+    where Guido van Rossum suggests representing graphs
+    as dictionaries mapping vertices to lists of neighbors,
+    however dictionaries of edges have many advantages
+    over lists: they can store extra information (here,
+    the lengths), they support fast existence tests,
+    and they allow easy modification of the graph by edge
+    insertion and removal.  Such modifications are not
+    needed here but are important in other graph algorithms.
+    Since dictionaries obey iterator protocol, a graph
+    represented as described here could be handed without
+    modification to an algorithm using Guido's representation.
+
+    Of course, G and G[v] need not be Python dict objects;
+    they can be any other object that obeys dict protocol,
+    for instance a wrapper in which vertices are URLs
+    and a call to G[v] loads the web page and finds its links.
+    
+    The output is a pair (D,P) where D[v] is the distance
+    from start to v and P[v] is the predecessor of v along
+    the shortest path from s to v.
+    
+    Dijkstra's algorithm is only guaranteed to work correctly
+    when all edge lengths are positive. This code does not
+    verify this property for all edges (only the edges seen
+    before the end vertex is reached), but will correctly
+    compute shortest paths even for some graphs with negative
+    edges, and will raise an exception if it discovers that
+    a negative edge";396;18;https://github.com/bachiraoun/pdbparser/blob/master/Utilities/Collection.py;2
+120;9da3365c7b91281b7073c07c495ff3033dfaa543;"(G, start, end=None):
+    """"""
+    Find shortest paths from the start vertex to all
+    vertices nearer than or equal to the end.
+
+    The input graph G is assumed to have the following
+    representation: A vertex can be any object that can
+    be used as an index into a dictionary.  G is a
+    dictionary, indexed by vertices.  For any vertex v,
+    G[v] is itself a dictionary, indexed by the neighbors
+    of v.  For any edge v->w, G[v][w] is the length of
+    the edge.  This is related to the representation in
+    <http://www.python.org/doc/essays/graphs.html>
+    where Guido van Rossum suggests representing graphs
+    as dictionaries mapping vertices to lists of neighbors,
+    however dictionaries of edges have many advantages
+    over lists: they can store extra information (here,
+    the lengths), they support fast existence tests,
+    and they allow easy modification of the graph by edge
+    insertion and removal.  Such modifications are not
+    needed here but are important in other graph algorithms.
+    Since dictionaries obey iterator protocol, a graph
+    represented as described here could be handed without
+    modification to an algorithm using Guido's representation.
+
+    Of course, G and G[v] need not be Python dict objects;
+    they can be any other object that obeys dict protocol,
+    for instance a wrapper in which vertices are URLs
+    and a call to G[v] loads the web page and finds its links.
+    
+    The output is a pair (D,P) where D[v] is the distance
+    from start to v and P[v] is the predecessor of v along
+    the shortest path from s to v.
+    
+    Dijkstra's algorithm is only guaranteed to work correctly
+    when all edge lengths are positive. This code does not
+    verify this property for all edges (only the edges seen
+    before the end vertex is";367;17;https://github.com/bachiraoun/pdbparser/blob/master/Utilities/Collection.py;2
+121;b32657aa5d791091bd6992730a1a48d8b4b1152f;= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),;61;1;https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py;3
+122;209e809060efff74c137c9b7c69d5d5168bff92a;2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9, 9, 9, 10, 10, 10, 10, 11, 11, 11, 11, 12, 12, 12, 12, 13, 13, 13, 13;91;3;https://github.com/odolan/Game-of-War-Predictor-/blob/master/War Predictor/GameOfWar.py;>7
+123;bd0d429e0742b94a8b820221dd64c909f7b47c13;, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,;73;2;https://github.com/rogerkenny/pystuff/blob/master/Solutions.py;>7
+124;b32657aa5d791091bd6992730a1a48d8b4b1152f;= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),;61;1;https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py;3
+125;b32657aa5d791091bd6992730a1a48d8b4b1152f;= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),;61;1;https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py;3
+126;eb52f02463b6ed46f0ffbbe2e15a65998cc778d4;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t;141;2;https://github.com/dbc1040/WeiboCrawler/blob/master/weibocrawler/proc_user_pages.py;1
+127;46a01cf8cb75ac9b2b7e223e22f1575d0cf1320d;"object.
+
+  Fields:
+    filter: The standard list filter.
+    name: The name of the operation's parent resource.
+    pageSize: The standard list page size.
+    pageToken: The standard list page token.
+  """"""
+
+  filter = _messages.StringField(1)
+  name = _messages.StringField(2, required=True)
+  pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32)
+  pageToken = _messages.StringField(4)";86;3;https://github.com/munishgarg-02/GoogleAPI/blob/master/google-cloud-sdk/lib/googlecloudsdk/third_party/apis/dialogflow/v2/dialogflow_v2_messages.py;0
+128;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,;100;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;0
+129;e0dead7e27af4a6122ccff07904c4d91137f59d9;"():
+    resp = requests.get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text
+        tickers.append(ticker)";101;5;https://github.com/RajputJay41/python-for-finance/blob/master/automating and getting  s&p list.py;6
+130;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47;93;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+131;24657fc9722b450bcb7afda9c2cbfa54d356d80f;"home_dir = os.path.expanduser('~')
+    credential_dir = os.path.join(home_dir, '.credentials')
+    if not os.path.exists(credential_dir):
+        os.makedirs(credential_dir)
+    credential_path =";46;1;https://github.com/lucaspbordignon/sgbcloud/blob/master/src/nlp.py;>7
+132;287df0f319785e386cb64eda635766799a1b731d;"?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)"""""",
+        (row[0], row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10]";81;2;https://github.com/devichs/Python-Bball-Stats/blob/master/shotStat.py;>7
+133;507245517ceb9d0e901a142ad45a421ee0cc008b;"', 'Accept': 'application/json, text/javascript, */*; q=0.01', 'Accept-Language': 'en-US,en;q=0.5', 'Accept-Encoding': 'gzip, deflate', 'X-Requested-With': 'XMLHttpRequest', 'Referer': 'http://";79;3;https://github.com/lianghq7/get_url/blob/master/qunaer/qunaer.py;>7
+134;45074562bee9d4f6d264fe9a484446a6ab78dd34;"# Copyright (C) 2010 Google Inc. All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are
+# met:
+#
+#    * Redistributions of source code must retain the above copyright
+# notice, this list of conditions and the following disclaimer.
+#    * Redistributions in binary form must reproduce the above
+# copyright notice, this list of conditions and the following disclaimer
+# in the documentation and/or other materials provided with the
+# distribution.
+#    * Neither the name of Google Inc. nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+# ""AS IS"" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import unittest
+
+from webkitpy.common.system.outputcapture import OutputCapture
+from webkitpy.thirdparty.mock import Mock
+from webkitpy.tool.commands.rebaseline import *
+from webkitpy.tool.mocktool import MockTool, MockOptions";331;24;https://github.com/auroranockert/webkit/blob/master/Tools/Scripts/webkitpy/tool/commands/rebaseline_unittest.py;0
+135;3a066157e3ff2c9b6b148ae7da3f4f6887c6379d;"#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+""""""
+This code implements a basic, Twitter-aware tokenizer.
+
+A tokenizer is a function that splits a string of text into words. In
+Python terms, we map string and unicode objects into lists of unicode
+objects.
+
+There is not a single right way to do tokenizing. The best method
+depends on the application.  This tokenizer is designed to be flexible
+and this easy to adapt to new domains and tasks.  The basic logic is
+this:
+
+1. The tuple regex_strings defines a list of regular expression
+   strings.
+
+2. The regex_strings strings are put, in order, into a compiled
+   regular expression object called word_re.
+
+3. The tokenization is done by word_re.findall(s), where s is the
+   user-supplied string, inside the tokenize() method of the class
+   Tokenizer.
+
+4. When instantiating Tokenizer objects, there is a single option:
+   preserve_case.  By default, it is set to True. If it is set to
+   False, then the tokenizer will downcase everything except for
+   emoticons.
+
+The __main__ method illustrates by tokenizing a few examples.
+
+I've also included a Tokenizer method tokenize_random_tweet(). If the
+twitter library is installed (http://code.google.com/p/python-twitter/)
+and Twitter is cooperating, then it should tokenize a random
+English-language tweet.
+""""""
+
+__author__ = ""Christopher Potts""
+__copyright__ = ""Copyright 2011, Christopher Potts""
+__credits__ = []
+__license__ = ""Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License: http://creativecommons.org/licenses/by-nc-sa/3.0/""
+__version__ = ""1.0""
+__maintainer__ = ""Christopher Potts""
+__email__ = ""See the author's website""";360;23;https://github.com/roelvanderburg/Sentiment-Analysis/blob/master/tweet_tokenizer.py;0
+136;c101dc6dd83eca9260fbfc0369979a7965240df4;s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d;100;1;https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py;4
+137;a805fae6363210162f97e35e88cd8aec0ac453a9;"Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the ""Software""), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:";86;2;https://github.com/rckirby/loopy/blob/master/loopy/diagnostic.py;3
+138;a805fae6363210162f97e35e88cd8aec0ac453a9;"Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the ""Software""), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:";86;2;https://github.com/rckirby/loopy/blob/master/loopy/diagnostic.py;3
+139;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,;100;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+140;34819bf6e7c8d452fbd0c131403c453a11338308;"(function):
+    if getattr(function, ATTR_EXPECTS_NAMESPACE_OBJECT, False):
+        return
+
+    spec = get_arg_spec(function)
+
+    defaults = dict(zip(*[reversed(x) for x in (spec.args,
+                                                spec.defaults or [])]))
+    defaults.update(getattr(spec, 'kwonlydefaults', None) or {})
+
+    kwonly = getattr(spec, 'kwonlyargs', [])
+
+    if sys.version_info < (3,0):
+        annotations = {}
+    else:
+        annotations = dict((k,v) for k,v in function.__annotations__.items()
+                           if isinstance(v, str))";128;4;https://github.com/jumpscale7/web/blob/master/pythonlib/argh/assembling.py;>7
+141;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,;98;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+142;971a5155a320a23115a41d16f14b6ccc6ffe9801;,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53;100;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+143;146055c776a42d50e98ffd46b5e6fbe5aca46707;"The Linux Foundation. All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are
+# met:
+#     * Redistributions of source code must retain the above copyright
+#       notice, this list of conditions and the following disclaimer.
+#     * Redistributions";62;1;https://github.com/tadiphone-caf/bootable_bootloader_edk2/blob/master/QcomModulePkg/Tools/image_header.py;0
+144;b180c23466aeb19f0e063e72e078778ffc9918b5;>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>;103;1;https://github.com/DixonShen/paper_work1/blob/master/v3/v3_utils.py;1
+145;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,;98;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+146;e2ed4a8c5b4df153be23cdfe09e9753c21631f56;"[int]]) -> bool:
+        graph = [[] for _ in range(numCourses)]
+        visit = [0 for _ in range(numCourses)]
+        for x, y in prerequisites:
+            graph[x].append(y)
+        for i in range(numCourses):
+            if not self.dfs";63;2;https://github.com/varun21290/leetcode_solutions/blob/master/Course Schedule/Solution.py;2
+147;29e7bb8572b9d802dda47c3dda901f3c44a5504d;'2022', '2023', '2024', '2025', '2026', '2027', '2028', '2029', '2030', '2031', '2032', '2033', '2034', '2035', '2036', '2037', '2038', '2039', '2040', '2041', '2042', '2043', '2044', '2045', '2046',;100;3;https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py;0
+148;d3fd8267c90805fcb17e609d7f96a6fc376eb881;'2018', '2017', '2016', '2015', '2014', '2013', '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005', '2004', '2003', '2002', '2001', '2000', '1999', '1998', '1997', '1996', '1995', '1994', '1993', '1992', '1991', '1990';115;4;https://github.com/pnxenopoulos/cs-communities/blob/master/prepare-data/process_data.py;0
+149;29e7bb8572b9d802dda47c3dda901f3c44a5504d;2022', '2023', '2024', '2025', '2026', '2027', '2028', '2029', '2030', '2031', '2032', '2033', '2034', '2035', '2036', '2037', '2038', '2039', '2040', '2041', '2042', '2043', '2044', '2045', '2046', ';100;3;https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py;0
+150;d3fd8267c90805fcb17e609d7f96a6fc376eb881;'2018', '2017', '2016', '2015', '2014', '2013', '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005', '2004', '2003', '2002', '2001', '2000', '1999', '1998', '1997', '1996', '1995', '1994', '1993', '1992', '1991', '1990';115;4;https://github.com/pnxenopoulos/cs-communities/blob/master/prepare-data/process_data.py;0
+151;29e7bb8572b9d802dda47c3dda901f3c44a5504d;'2022', '2023', '2024', '2025', '2026', '2027', '2028', '2029', '2030', '2031', '2032', '2033', '2034', '2035', '2036', '2037', '2038', '2039', '2040', '2041', '2042', '2043', '2044', '2045', '2046',;100;3;https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py;0
+152;fc6fc80b7defa2838dc26c92a245648646d24f17;"(r""^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$""";91;3;https://github.com/Zenithar/cuckoo-modified/blob/master/web/web/settings.py;>7
+153;fc6fc80b7defa2838dc26c92a245648646d24f17;"(r""^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01";75;3;https://github.com/Zenithar/cuckoo-modified/blob/master/web/web/settings.py;>7
+154;0b72bbb9d93a63b5da7c49c438e6cd10df9283e5;"',
+    classifiers=[
+        'Development Status :: 2 - Pre-Alpha',
+        'Framework :: Django',
+        'Intended Audience :: Developers',
+        'License :: OSI Approved :: MIT License',
+        'Natural Language :: English',
+        'Programming Language :: Python :: 2',
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.3',
+        'Programming Language :: Python :: 3.4',";113;4;https://github.com/dominicrodger/djangofinance/blob/master/setup.py;0
+155;0e3d2aa266b13e6a7f62b708d8fb4ba0a43cdb25;"#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+""""""
+Copyright (c) 2014-2015 pocsuite developers (http://seebug.org)
+See the file 'docs/COPYING' for copying permission
+""""""
+#命令行
+from pocsuite import pocsuite_cli
+#验证模块
+from pocsuite import pocsuite_verify
+#攻击模块
+from pocsuite import pocsuite_attack
+#控制台模式
+from pocsuite import pocsuite_console
+from pocsuite.api.request import req 
+from pocsuite.api.poc import register
+from pocsuite.api.poc import Output, POCBase";106;3;https://github.com/vulscanteam/vulscan/blob/master/vul/49-Nginx-Remote-Integer-Overflow.py;0
+156;ec98dbafc2251a08cb676e29f9af05b779fbf542;"# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2005 by Holger Schurig
+# 
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program; if not, write to the Free Software
+# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
+#
+
+
+from configlets import *";176;9;https://github.com/BackupTheBerlios/destar-svn/blob/master/branches/icom-avatar/cfg_app_meetme.py;0
+157;640099e1563924a7ab8373807462716eb43273e7;"HANGMAN = (
+""""""
+ ------
+ |    |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |
+ |
+ |
+ |
+ |
+ |
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |   -+-
+ | 
+ |   
+ |   
+ |   
+ |   
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |  /-+-
+ |   
+ |   
+ |   
+ |   
+ |   
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |  /-+-/
+ |   
+ |   
+ |   
+ |   
+ |   
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |  /-+-/
+ |    |
+ |   
+ |   
+ |   
+ |   
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |  /-+-/
+ |    |
+ |    |
+ |   | 
+ |   | 
+ |   
+----------
+"""""",
+""""""
+ ------
+ |    |
+ |    O
+ |  /-+-/
+ |    |
+ |    |
+ |   | |
+ |   | |
+ |  
+----------
+"""""")
+
+MAX_WRONG = len(HANGMAN) - 1
+WORDS = (""OVERUSED"", ""CLAM"", ""GUAM"", ""TAFFETA"", ""PYTHON"")";223;10;https://github.com/theglitchmitch/M3-Learning-Python/blob/master/Chapter_5/Hangman_Game.py;5
+158;0fc3a34d1254d5dc319c792ea0b8c0c9a15ee786;"HANGMAN_PICS = ['''
+  +---+
+      |
+      |
+      |
+     ===''', '''
+  +---+
+  O   |
+      |
+      |
+     ===''', '''
+  +---+
+  O   |
+  |   |
+      |
+     ===''', '''
+  +---+
+  O   |
+ /|   |
+      |
+     ===''', '''
+  +---+
+  O   |
+ /|\  |
+      |
+     ===''', '''
+  +---+
+  O   |
+ /|\  |
+ /    |
+     ===''', '''
+  +---+
+  O   |
+ /|\  |
+ / \  |
+     ===''', '''
+  +---+
+ [O   |
+ /|\  |
+ / \  |
+     ===''', '''
+  +---+
+ [O]  |
+ /|\  |
+ / \  |
+     ===''']
+⋯
+= 'ant baboon badger bat bear beaver camel cat clam cobra cougar coyote crow deer dog donkey duck eagle ferret fox frog goat goose hawk lion lizard llama mole monkey moose mouse mule newt otter owl panda parrot pigeon python rabbit ram rat raven rhino salmon seal shark sheep skunk sloth snake spider stork swan tiger toad trout turkey turtle weasel whale wolf wombat zebra'.split()";272;15;https://github.com/ShulinLiu/PythonNote/blob/master/Games/hangman.py;5
+159;aa88d5324a6c0b45becff4fac72e7b92c753684a;", 'html.parser')
+    table = soup.find('table', attrs={'class':'wikitable sortable'})
+    rows = table.find_all('tr')
+    for row in rows :
+        cols = row.find_all('td')
+        if len(cols) ==";62;2;https://github.com/jaeteekae/DelayedTwitter/blob/master/get_top_twitter_accounts.py;5
+160;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;0.68, 0.69, 0.7, 0.71, 0.72, 0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.8, 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.9, 0.91, 0.92,;100;5;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+161;e47ed3a97799388b6100bb67048e6ad8c0e4da5f;i[0],i[1],i[2],i[3],i[4],i[5],i[6],i[7],i[8],i[9],i[10],i[11],i[12],i[13],i[14],i[15],i[16],i[17],i[18],i[19],i[20],i[21],i[22],i[23],i[24],i[25],i[26],i[27],i[28],i[29],i[30],i[31],i[32],i[33],i[34],i[35],i[36],i[37],i[38],i[39],i[40],i[41],i[42],i[43],i[44],i;226;12;https://github.com/genezonxiii/Population_Data/blob/master/population_data/age_education.py;>7
+162;26baf8973a6c2bb1a52ea72d6da4a2e552a10ebc;".read().decode()
+    stock_data = []
+    split_source = source_code.split('\n')
+    for line in split_source:
+        split_line = line.split(',')
+        if len(split_line) == 6:
+            if 'values' not in line and 'labels' not in line:
+                stock_data.append(line)
+    date, closep, highp, lowp, openp, volume = np.loadtxt(stock_data,
+                                                          delimiter=',',
+                                                          unpack=True,
+                                                          converters={0: bytespdate2num('%Y%m%d')})";114;4;https://github.com/rishikksh20/matplotlib/blob/master/customizationExamples.py;6
+163;0837e9d3e9367fd29476288ee8a1bad8d45f2466;0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.2, 0.21, 0.22, 0.23, 0.24, 0.25, 0.26,;100;5;https://github.com/samta/nonlinear_regression/blob/master/data.py;>7
+164;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+165;81c282288dfee4875a4f8e004d5f3a6ccdd2a49f;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';115;3;https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py;>7
+166;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+167;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+168;a272bcee535cdfdaeb6c1472e475e76cb0e2e3fa;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DWDP','XOM','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ','V','WMT';117;3;https://github.com/seantrinh/thewolvesofwallstreet/blob/master/copy_run.py;>7
+169;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+170;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';95;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+171;80e251e4e9f8b0f9ac0207bf84a036f040e10cb2;")
+    df['100ma'] = df['Adj Close'].rolling(window=100,min_periods=0).mean()
+    df_ohlc = df['Adj Close'].resample('10D').ohlc()
+    df_volume = df['Volume'].resample('10D').sum()
+    df_ohlc.reset_index(inplace=True)
+    df_ohlc['Date'] = df_ohlc['Date'].map(mdates.date2num)
+    ax1 = plt.subplot2grid((6,1),(0,0),rowspan=5,colspan=1)
+    ax2 = plt.subplot2grid((6,1),(5,0),rowspan=1,colspan=1,sharex=ax1)
+    ax1.xaxis_date()
+    candlestick_ohlc(ax1,df_ohlc.values,width=2,colorup='g')
+    ax2.fill_between(df_volume.index.map(mdates.date2num),df_volume.values,0)";197;12;https://github.com/SombrHeroQc/Finance101/blob/master/investing101.py;>7
+172;7ebb786cd066594187910cfba3b3e58c3603b02d;= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT;100;4;https://github.com/Shiva-gs/Project3/blob/master/stock_data.py;>7
+173;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+174;81c282288dfee4875a4f8e004d5f3a6ccdd2a49f;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';115;3;https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py;>7
+175;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+176;81c282288dfee4875a4f8e004d5f3a6ccdd2a49f;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';115;3;https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py;>7
+177;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+178;81c282288dfee4875a4f8e004d5f3a6ccdd2a49f;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';115;3;https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py;>7
+179;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+180;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+181;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+182;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+183;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+184;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+185;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+186;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+187;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+188;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+189;68813c1284352872db9a5abdaaaabf8c8e21c16d;['MMM', 'AXP', 'AAPL', 'BA', 'CAT', 'CVX', 'CSCO', 'KO', 'DIS', 'DWDP', 'XOM', 'GE', 'GS', 'HD', 'IBM', 'INTC', 'JNJ', 'JPM', 'MCD', 'MRK', 'MSFT', 'NKE', 'PFE', 'PG', 'TRV', ';102;3;https://github.com/parsa3000/SE18/blob/master/stockgame2/home/listofstockscrypto.py;>7
+190;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';95;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+191;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';95;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+192;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';95;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+193;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47;93;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+194;ef289839bba660b1ea8e7dfbf6ede70578ead0e3;"# 1                                                          
+# 2                                                          
+# 3                                                          
+# 4                                                          
+# 5                                                          
+# 6                                                          
+# 7                                                          
+# 8                                                          
+# 9                                                          
+# 10                                                         
+# 11                                                         
+# 12                                                         
+# 13                                                         
+# 14                                                         
+# 15                                                         
+# 16                                                         
+# 17                                                         
+# 18                                                         
+# 19                                                         
+# 20                                                         
+# 21                                                         
+# 22                                                         
+# 23                                                         
+# 24                                                         
+# 25                                                         
+# 26                                                         
+# 27                                                         
+# 28                                                         
+# 29                                                         
+# 30                                                         
+# 31                                                         
+# 32                                                         
+# 33                                                         
+# 34                                                         
+# 35                                                         
+# 36                                                         
+# 37                                                         
+# 38                                                         
+# 39                                                         
+# 40                                                         
+# 41                                                         
+# 42                                                         
+# 43                                                         
+# 44                                                         
+# 45                                                         
+# 46                                                         
+# 47                                                         
+# 48                                                         
+# 49                                                         
+# 50                                                         
+# 51                                                         
+# 52                                                         
+# 53                                                         
+# 54                                                         
+# 55                                                         
+# 56                                                         
+# 57                                                         
+# 58                                                         
+# 59                                                         
+# 60                                                         
+# 61                                                         
+# 62                                                         
+# 63                                                         
+# 64                                                         
+# 65";130;5;https://github.com/MReneBrown/Python-Course/blob/master/Function_Syntax.py;>7
+195;ef289839bba660b1ea8e7dfbf6ede70578ead0e3;"# 1                                                                 
+# 2                                                                 
+# 3                                                                 
+# 4                                                                 
+# 5                                                                 
+# 6                                                                 
+# 7                                                                 
+# 8                                                                 
+# 9                                                                 
+# 10                                                                 
+# 11                                                                 
+# 12                                                                 
+# 13                                                                 
+# 14                                                                 
+# 15                                                                 
+# 16                                                                 
+# 17                                                                 
+# 18                                                                 
+# 19                                                                 
+# 20                                                                 
+# 21                                                                 
+# 22                                                                 
+# 23                                                                 
+# 24                                                                 
+# 25                                                                 
+# 26                                                                 
+# 27                                                                 
+# 28                                                                 
+# 29                                                                 
+# 30                                                                 
+# 31                                                                 
+# 32                                                                 
+# 33                                                                 
+# 34                                                                 
+# 35                                                                 
+# 36                                                                 
+# 37                                                                 
+# 38                                                                 
+# 39                                                                 
+# 40                                                                 
+# 41                                                                 
+# 42                                                                 
+# 43                                                                 
+# 44                                                                 
+# 45                                                                 
+# 46                                                                 
+# 47                                                                 
+# 48                                                                 
+# 49                                                                 
+# 50                                                                 
+# 51                                                                 
+# 52                                                                 
+# 53                                                                 
+# 54                                                                 
+# 55                                                                 
+# 56                                                                 
+# 57                                                                 
+# 58                                                                 
+# 59                                                                 
+# 60                                                                 
+# 61                                                                 
+# 62                                                                 
+# 63                                                                 
+# 64";128;5;https://github.com/MReneBrown/Python-Course/blob/master/Function_Syntax.py;>7
+196;4c950265f099c64e88b64082cea5a8d91ba5e08f;"T1"", ""T2"", ""T3"", ""T4"", ""T5"", ""T6"", ""T7"", ""T8"", ""T9"", ""T10"", ""T11"", ""T12"", ""T13"", ""T14"", ""T15"", ""T16"", ""T17"", ""T18"", ""T19"", ""T20"", ""T21"", ""T22"", ""T23"", ""T24"", ""T25"", """;100;4;https://github.com/AndresGarciaEscalante/Schnell-Language/blob/master/Schnell.py;2
+197;4c950265f099c64e88b64082cea5a8d91ba5e08f;"T1"", ""T2"", ""T3"", ""T4"", ""T5"", ""T6"", ""T7"", ""T8"", ""T9"", ""T10"", ""T11"", ""T12"", ""T13"", ""T14"", ""T15"", ""T16"", ""T17"", ""T18"", ""T19"", ""T20"", ""T21"", ""T22"", ""T23"", ""T24"", ""T25"", """;100;4;https://github.com/AndresGarciaEscalante/Schnell-Language/blob/master/Schnell.py;2
+198;cbf3fa5bd72d753c2018a0f797cb3b65d5dea3d5;"A"", ""B"", ""C"", ""D"", ""E"", ""F"", ""G"", ""H"", ""I"", ""J"", ""K"", ""L"", ""M"", ""N"", ""O"", ""P"", ""Q"", ""R"", ""S"", ""T"", ""U"", ""V"", ""W"", ""X"", ""Y"", ""Z"", ""0"", ""1"", ""2"", ""3"", ""4"", ""5"", ""6"", ""7";133;3;https://github.com/EdwinUrbina-13/CipherGUI/blob/master/MorseCodeCipher.py;2
+199;506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefb;""", ""F"", ""G"", ""H"", ""I"", ""J"", ""K"", ""L"", ""M"", ""N"", ""O"", ""P"", ""Q"", ""R"", ""S"", ""T"", ""U"", ""V"", ""W"", ""X"", ""Y"", ""Z""";85;2;https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py;2
+200;6dc7fe0605c4c500e135fb4760bf9116a131239e;"1"", ""2"", ""3"", ""4"", ""5"", ""6"", ""7"", ""8"", ""9"", ""10"", ""11"", ""12"", ""13"", ""14"", ""15"", ""16"", ""17"", ""18"", ""19"", ""20"", ""21"", ""22"", ""23"", ""24"", ""25"", ""26"", ""27"", ""28"", ""29"", ""30"", ""31"", ""32"", ""33"", ""34";133;7;https://github.com/kevinwlip/Automation/blob/master/lib/common/zbAlertTemplates.py;2
+201;506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefb;"A"", ""B"", ""C"", ""D"", ""E"", ""F"", ""G"", ""H"", ""I"", ""J"", ""K"", ""L"", ""M"", ""N"", ""O"", ""P"", ""Q"", ""R"", ""S"", ""T"", ""U""";82;1;https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py;2
+202;8d7c80312dc967564c5e1cf3df26468097be232e;d.e.f.g.h.i.j.k.l.m.n.o.p.q.r.s.t.u.v.w.x.y.z.a.b.c.d.e.f.g.h.i.j.k.l.m.n.o.p.q.;80;1;https://github.com/schottkey7/codewars/blob/master/Strings/domain_name_validator.py;2
+203;96826b181bdcae40df1006b93a8b4fe5b83ad735;":
+        print(""\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n";418;2;https://github.com/elodietheelectronicfairy/blood_runner/blob/master/blood_runner_for_embedd.py;5
+204;9b7fae8909304d7d462d3800e5dbe8d23ed4c342;"(x):
+    """"""
+    Input:
+        x (numpy array) = input sequence of length N
+    Output:
+        The function should return a numpy array of length N
+        X (numpy array) = The N point DFT of the input sequence x
+    """"""
+    ## Your code here
+    N = len(x)";61;2;https://github.com/stembl/sigproc/blob/master/asp/workspace/A2/A2Part3.py;2
+205;43981045ad2ae677328bfec2fb4d28db1d1b0fd9;"get_all_tweets(screen_name):
+	#Twitter only allows access to a users most recent 3240 tweets with this method
+	#authorize twitter, initialize tweepy
+	auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
+	auth.set_access_token(access_token, access_token_secret)
+	api = tweepy.API(auth)
+	
+	#initialize a list to hold all the tweepy Tweets
+	alltweets = []	
+	
+	#make initial request for most recent tweets (200 is the maximum allowed count)
+	new_tweets = api.user_timeline(screen_name = screen_name,count=200)
+	
+	#save most recent tweets
+	alltweets.extend(new_tweets)
+	
+	#save the id of the oldest tweet less one
+	oldest = alltweets[-1].id - 1
+	
+	#keep grabbing tweets until there are no tweets left to grab
+	while len(new_tweets) > 0:
+		print ""getting tweets before %s"" % (oldest)
+		
+		#all subsiquent requests use the max_id param to prevent duplicates";171;9;https://github.com/coej/social-analytics/blob/master/twitter_dl.py;1
+206;43981045ad2ae677328bfec2fb4d28db1d1b0fd9;"get_all_tweets(screen_name):
+	#Twitter only allows access to a users most recent 3240 tweets with this method
+	
+	#authorize twitter, initialize tweepy
+	auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
+	auth.set_access_token(access_token, access_token_secret)
+	api = tweepy.API(auth)
+	
+	#initialize a list to hold all the tweepy Tweets
+	alltweets = []	
+	
+	#make initial request for most recent tweets (200 is the maximum allowed count)
+	new_tweets = api.user_timeline(screen_name = screen_name,count=200)
+	
+	#save most recent tweets
+	alltweets.extend(new_tweets)
+	
+	#save the id of the oldest tweet less one
+	oldest = alltweets[-1].id - 1
+	
+	#keep grabbing tweets until there are no tweets left to grab
+	while len(new_tweets) > 0:
+		print ""getting tweets before %s"" % (oldest)
+		
+		#all subsiquent requests use the max_id param to prevent";170;9;https://github.com/coej/social-analytics/blob/master/twitter_dl.py;1
+207;5c9798600f20016bc7878a7cfbcf29dec327f0a1;""")
+    print(""I like typing this."")
+    print(""This is fun."")
+    print('Yay! Printing.')
+    print(""I'd much rather you 'not'."")
+    print('I ""said"" do not touch this.')
+    print(""";62;2;https://github.com/mikelei8291/LearnPython/blob/master/lpthw/ex1.py;1
+208;f955f9cd2d4b2ddeb44349c2716b17dfa3f7ef3c;"].values
+# %%
+# Splitting the dataset into the Training set and Test set
+from sklearn.model_selection import train_test_split
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)
+# %%
+# Feature Scaling
+from sklearn.preprocessing import StandardScaler
+sc_X = StandardScaler()
+X_train = sc_X.fit_transform(X_train)
+X_test = sc_X.transform(X_test)
+# %%";83;5;https://github.com/KaziSabrinaSonnet/Essential_Tremor_Detection/blob/master/Feature_Extracting/Classifier/Classifier_LR.py;>7
+209;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;0.43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67,;100;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+210;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;0.43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67,;100;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+211;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.;100;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+212;3f99df658c409d54d612943f38b9c8263059704b;46, 0.48, 0.5, 0.52, 0.54, 0.56, 0.58, 0.6, 0.62, 0.64, 0.66, 0.68, 0.7, 0.72, 0.74, 0.76, 0.78, 0.8, 0.82, 0.84, 0.86, 0.88, 0.9, 0.92, 0.94, 0.;100;3;https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py;>7
+213;3f99df658c409d54d612943f38b9c8263059704b;0.48, 0.5, 0.52, 0.54, 0.56, 0.58, 0.6, 0.62, 0.64, 0.66, 0.68, 0.7, 0.72, 0.74, 0.76, 0.78, 0.8, 0.82, 0.84, 0.86, 0.88, 0.9, 0.92, 0.94, 0.96,;100;3;https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py;>7
+214;3f99df658c409d54d612943f38b9c8263059704b;0.5, 0.52, 0.54, 0.56, 0.58, 0.6, 0.62, 0.64, 0.66, 0.68, 0.7, 0.72, 0.74, 0.76, 0.78, 0.8, 0.82, 0.84, 0.86, 0.88, 0.9, 0.92, 0.94, 0.96, 0.98,;100;3;https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py;>7
+215;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;0.43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67;99;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+216;3f99df658c409d54d612943f38b9c8263059704b;44, 0.46, 0.48, 0.5, 0.52, 0.54, 0.56, 0.58, 0.6, 0.62, 0.64, 0.66, 0.68, 0.7, 0.72, 0.74, 0.76, 0.78, 0.8, 0.82, 0.84, 0.86, 0.88, 0.9, 0.92, 0.;100;3;https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py;>7
+217;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;43, 0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.;100;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+218;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.;100;6;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+219;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;0.44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68,;100;3;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+220;c4a3a88b9fccb47902fd5b19acb79c98865d0ac8;44, 0.45, 0.46, 0.47, 0.48, 0.49, 0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 0.59, 0.6, 0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.;100;4;https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py;>7
+221;371419a87b9319fba36391e8005c806e75a639d3;"import threading
+    class InterruptableThread(threading.Thread):
+        def __init__(self):
+            threading.Thread.__init__(self)
+            self.result = None
+
+        def run(self):
+            try:
+                self.result = func(*args, **kwargs)
+            except:
+                self.result = default
+
+    it = InterruptableThread()
+    it.start()
+    it.join(timeout_duration)
+    if it.isAlive():";80;3;https://github.com/monicashver/PongAI/blob/master/PongAIvAI.py;>7
+222;371419a87b9319fba36391e8005c806e75a639d3;"import threading
+    class InterruptableThread(threading.Thread):
+        def __init__(self):
+            threading.Thread.__init__(self)
+            self.result = None
+
+        def run(self):
+            try:
+                self.result = func(*args, **kwargs)
+            except:
+                self.result = default
+
+    it = InterruptableThread()
+    it.start()
+    it.join(timeout_duration)
+    if it.isAlive():";80;3;https://github.com/monicashver/PongAI/blob/master/PongAIvAI.py;>7
+223;58458902e8132d42fc3ec0fb6495937d1f63357e;"import threading
+    class FuncThread(threading.Thread):
+        def __init__(self):
+            threading.Thread.__init__(self)
+            self.result = None
+
+        def run(self):
+            self.result = func(*args, **kwargs)
+
+        def _stop(self):
+            if self.isAlive():
+                threading.Thread._Thread__stop(self)
+    it = FuncThread()
+    it.start()
+    it.join(";83;3;https://github.com/angelfish91/web-crawler/blob/master/baidu-image.py;>7
+224;d86d3e0a8905ba466258ab06f1a8d8811832dc9b;"import signal
+
+    class TimeoutError(Exception):
+        pass
+
+    def handler(signum, frame):
+        raise TimeoutError()
+
+    # set the timeout handler
+    signal.signal(signal.SIGALRM, handler) 
+    signal.alarm(timeout_duration)
+    try:
+        result = func(*args, **kwargs)
+    except TimeoutError as exc:
+        result = default
+    finally:
+        signal.alarm(0)
+
+    return result";73;3;https://github.com/cnelsonsic/public_drown_scanner/blob/master/scanner.py;>7
+225;d86d3e0a8905ba466258ab06f1a8d8811832dc9b;"import signal
+
+    class TimeoutError(Exception):
+        pass
+
+    def handler(signum, frame):
+        raise TimeoutError()
+
+    # set the timeout handler
+    signal.signal(signal.SIGALRM, handler)
+    signal.alarm(timeout_duration)
+    try:
+        result = func(*args, **kwargs)
+    except TimeoutError as exc:
+        result = default
+    finally:
+        signal.alarm(0)
+
+    return result";73;3;https://github.com/cnelsonsic/public_drown_scanner/blob/master/scanner.py;>7
+226;4bfe52bdc8fdc752a0d278665c62155c81273f86;0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.;90;3;https://github.com/bkargoll/TriggerStudies/blob/master/turnOnTauProducer.py;>7
+227;87ea0a8e40da6e6d9671275b4a0c345009f695ff;"for i in range(1, len(array)):
+        key = array[i]
+        j = i - 1
+        while j >= 0 and array[j] > key:
+            array[j + 1] = array[j]
+            j -= 1
+        array[j + 1] = key";60;2;https://github.com/cjh5414/sort-with-python/blob/master/insertion-sort.py;0
+228;67046ceffbef8e95b72daaa339225e8634694fa7;": sorted array
+    """"""
+    for i in range(len(array)):
+        for j in range(i, len(array)):
+            if array[i] > array[j]:
+                array[i], array[j] = array[j], array[i]
+    return array";62;1;https://github.com/xyang57/LeetCode/blob/master/all_sorts.py;0
+229;8ec0d022ae4f38b9e6d535435488a680b65f1645;"if not re.match(""^[a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+@[a-zA-Z0-9-]+(?:\.[a-zA-Z0-9-]+)*$"",";71;3;https://github.com/OliverJ20/Team-Rocket-Website-IFB299/blob/master/app/testfunctions.py;0
+230;99d65b9588838b2879ab981458b79dc8a434d232;".csv"", ""rb"")
+        
+        part = MIMEBase('application', 'octet-stream')
+        part.set_payload((attachment).read())
+        encoders.encode_base64(part)
+        part.add_header('Content-Disposition', ""attachment; filename= %s"" % filename)
+        
+        msg.attach(part)
+        
+        server = smtplib.SMTP('smtp";75;3;https://github.com/sgoodwin90/work/blob/master/ZendeskAPI.py;4
+231;1f11d7da7ffc7a04c263f7ac1d19ef5d3ccdba3a;"server_ssl = smtplib.SMTP_SSL(""smtp.gmail.com"", 465)
+        server_ssl.ehlo() # optional, called by login()
+        server_ssl.login(gmail_user, gmail_pwd)
+        # ssl server doesn't support or need tls, so don't call server_ssl.starttls()
+        server_ssl.sendmail(FROM, TO, message";67;3;https://github.com/antowe001253/STOCKS/blob/master/Python34/old/best_play.py;4
+232;6e4a00787ce01b50c584f048d8dd13192b64f96e;"attachment = open(filename, 'rb')
+    part = MIMEBase('application', 'octet-stream')
+    part.set_payload((attachment).read())
+    encoders.encode_base64(part)
+    part.add_header('Content-Disposition', ""attachment; filename= %s"" % filename)
+    msg.attach(part)";69;3;https://github.com/Presto412/VIT-Timetable-Scraper/blob/master/SendEmail.py;4
+233;5218aed8cf46e2ca6f38b96a56c76b381add047a;"# Prepare actual message
+    message = """"""\From: %s\nTo: %s\nSubject: %s\n\n%s
+    """""" % (FROM, "", "".join(TO), SUBJECT, TEXT)
+    try:
+        #server = smtplib.SMTP(SERVER) 
+        server = smtplib.SMTP(""smtp.gmail.com"", 587) #or port 465 doesn't seem to work!
+        server.ehlo()
+        server.starttls()
+        server.login(gmail_user, gmail_pwd)
+        server.sendmail(FROM, TO, message)
+        #server.quit()
+        server.close()
+        print 'successfully sent the mail'
+    except:
+        print ""failed to send mail""";143;5;https://github.com/spatwardhan7/Disaster-Management-Mobile-Web-App-/blob/master/sendemail.py;4
+234;90b47ef628f14b678d612f1d24960af0b6b68391;"(n):
+    if n == 2:
+        return True
+    if n % 2 == 0 or n <= 1:
+        return False
+    sqr = int(math.sqrt(n)) + 1
+    for divisor in range(3, sqr, 2):
+        if n % divisor == 0:
+            return False
+    return True";64;1;https://github.com/skalam02/Crypto/blob/master/rsa.py;1
+235;adcedfe70ca347338148f2049eb9671d22f334d4;"""User-Agent"":""Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.104 Safari/537.36 Core/1.53.4549.400 QQBrowser/9.7.12900.400""";65;5;https://github.com/WatsonLee/python-small-tools/blob/master/upload.py;4
+236;795c84b13e59790cd5e8fe2b61b8a3e69c722c4e;"header = {'User-Agent':""Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/43.0.2357.134 Safari/537.36""}       
+    soup = get_soup(url, header)       
+    ActualImages = []       
+    for a in soup.find_all(""div"", {""class"":""rg_meta""}):       
+        link, Type = json.loads(a.text)[""ou""], json.loads(a.text)[""ity""]       
+        ActualImages.append((link, Type))       
+    for i, (img, Type) in enumerate(ActualImages[0:";141;11;https://github.com/apiss2/Polka-dot/blob/master/im_search.py;>7
+237;795c84b13e59790cd5e8fe2b61b8a3e69c722c4e;"header = {'User-Agent':""Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/43.0.2357.134 Safari/537.36""}       
+    soup = get_soup(url, header)       
+    ActualImages = []       
+    for a in soup.find_all(""div"", {""class"":""rg_meta""}):       
+        link, Type = json.loads(a.text)[""ou""], json.loads(a.text)[""ity""]       
+        ActualImages.append((link, Type))";126;8;https://github.com/apiss2/Polka-dot/blob/master/im_search.py;>7
+238;d2e6309f96f7a621a36b42174489c5a494336fe9;".api.cognitive.microsoft.com/vision/v2.0/""
+
+    analyze_url = vision_base_url + ""analyze""
+
+    headers = {'Ocp-Apim-Subscription-Key': subscription_key,
+               'Content-Type': 'application/octet-stream'}
+    params = {'visualFeatures': 'Categories,Description,Color'}";67;3;https://github.com/baileye/azure-custom-vision-siggraph/blob/master/azurevision.py;0
+239;dc53ab4c451394227f75e0f9efa2633b445f8ce8;"vision_base_url = ""https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/""
+
+    vision_analyze_url = vision_base_url + ""analyze""
+
+    headers = {'Ocp-Apim-Subscription-Key': subscription_key}
+    params  = {'visualFeatures': 'Categories,Description,Color'}
+    data    = {'url':";68;2;https://github.com/xodhr98/hello/blob/master/main.py;0
+240;b31e66e793acc8639668f9c8b5ac939b5e128191;".api.cognitive.microsoft.com/vision/v2.0/""
+    vision_analyze_url = vision_base_url + ""analyze""
+    headers = {'Ocp-Apim-Subscription-Key': subscription_key, ""Content-Type"": ""application/octet-stream""}
+    params  = {'visualFeatures': '";60;3;https://github.com/andybbruno/Mobile/blob/master/Client/test_no_opencv.py;0
+241;1e133669861afa9b7565378aa03d79259afddb98;"}
+    params = {'visualFeatures': 'Categories,Description,Color'}
+    response = requests.post(vision_analyze_url, headers=headers, params=params, data=image_data)
+    response.raise_for_status()
+    analysis = response.json()
+    image_caption = analysis[""description""][""captions""][0][""text""].capitalize()";73;3;https://github.com/xiechen0692/Computer-vision/blob/master/Intelligent_home/Iot_Project1.py;0
+242;ef496219f168d0a706bbba504682869e30baea2a;"}
+    response = requests.post(ocr_url, headers=headers, params=params, json=data)
+    response.raise_for_status()
+
+    analysis = response.json()
+
+    # Extract the word bounding boxes and text.
+    line_infos = [region[""lines""] for region in analysis[""regions""]]
+    word_infos = []
+    for line in line_infos:
+        for word_metadata in line:
+            for word_info in word_metadata[""words""]:
+                word_infos.append(word_info)";91;3;https://github.com/thetime50/ocr/blob/master/ocr_ms/print.py;0
+243;c47a16aef42e78cfdcf126d9a9ac129a457af617;"('DISCORD_TOKEN')
+    client = discord.Client()
+
+    @client.event
+    async def on_ready():
+        print('Logged in as')
+        print(client.user.name)
+        print(client.user.id)
+        print('------')
+
+    @client.event
+    async def on_message(message):
+        if message.content.startswith('!test'):
+            counter = 0
+            tmp = await client.send_message(message.channel, 'Calculating messages...')
+            async for log in client.logs_from(message.channel, limit=100):
+                if log.author == message.author:
+                    counter += 1
+
+            await client.edit_message(tmp, 'You have {} messages.'.format(counter))
+        elif message.content.startswith('!sleep'):
+            await asyncio.sleep(5)
+            await client.send_message(message.channel, 'Done sleeping')
+        elif message.content.startswith('";192;10;https://github.com/eschlon/uther/blob/master/uther/uther.py;0
+244;7fcb86edfddd0bb8fde6e53dc22f364c663617ab;"i = m - 1
+        j = n - 1
+        k = m + n - 1
+        while i >= 0 and j >= 0:
+            if nums1[i] > nums2[j]:
+                nums1[k] = nums1[i]
+                i -= 1
+            else:
+                nums1[k] = nums2[j]
+                j -= 1
+            k -= 1
+        while j >= 0:
+            nums1[k] = nums2[j]
+            k -= 1
+            j -= 1";94;4;https://github.com/qijiayin/jiayin_practice/blob/master/88.py;0
+245;eac35f84b641852e2893d17a79aa0e00fb067daf;"with open(file_name) as csv_file:
+        csv_reader = csv.reader(csv_file, delimiter=',')
+        line_count = 0
+        for row in csv_reader:
+            if line_count == 0:
+                print(f'Column names are {"", "".join(row)}')
+                line_count += 1
+            else:
+                print(f'\t{row[0]} works in the {row[1]} department, and was born in {row[2]}.')
+                line_count += 1
+        print(f'Processed {line_count} lines.')";113;5;https://github.com/NilsBlach/AirplaneBoarding/blob/master/code/AirplaneBoarding/measurements.py;0
+246;067c3c43ff91c2c19ff20715e61c5786a13e9ed8;= ['__abs__', '__add__', '__and__', '__call__', '__cmp__', '__coerce__', '__contains__', '__delitem__', '__delslice__', '__div__', '__divmod__', '__eq__', '__float__', '__floordiv__', '__ge__', '__getitem__', '__getslice__;68;2;https://github.com/cyisfor/media-tagger/blob/master/proxy.py;>7
+247;a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772;= {'a':[1,2,3,4,5,6,7,8,9,10], 'b':[1,2,3,4,5,6,7,8,9,10], 'c':[1,2,3,4,5,6,7,8,9,10];79;1;https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py;3
+248;89d6b0e1c01b7070b218dfed327575e26464e2fc;":
+            if line_count == 0:
+                print(f'Column names are {"", "".join(row)}')
+                line_count += 1
+            else:
+                print(f'\t{row[0]} works in the {row[1]} department, and was born in {row[2]}.')
+                line_count += 1
+        print(f'Processed {line_count} lines.')";84;3;https://github.com/abhinav2127/ProblemStatements-Python/blob/master/ConvertReadCsvUTF16ToUTF8/converter.py;0
+249;89d6b0e1c01b7070b218dfed327575e26464e2fc;":
+            if line_count == 0:
+                print(f'Column names are {"", "".join(row)}')
+                line_count += 1
+            else:
+                print(f'\t{row[0]} works in the {row[1]} department, and was born in {row[2]}.')
+                line_count += 1
+        print(f'Processed {line_count} lines.')";84;3;https://github.com/abhinav2127/ProblemStatements-Python/blob/master/ConvertReadCsvUTF16ToUTF8/converter.py;0
+250;9061ffa7d967c6ff59217b36a9b608f1ecfa9e45;'C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9', 'C10', 'C11', 'C12', 'C13', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21', 'C22', 'C23', 'C24',;96;5;https://github.com/DownyPrio/xDeepFM/blob/master/exdeepfm/convert_ffm_process.py;3
+251;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+252;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+253;fba9c49e384d6e3bb736c3f5c161afd2f0d1506d;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';111;4;https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py;>7
+254;33c156f0d7710a8d91218dfc2c46d643a0a6bd84;[1]/div[1]/div[1]/div[1]/div[2]/div[2]/div[1]/div[1]/div[2]/div[1]/div[1]/div[1]/div[1]/div[;66;2;https://github.com/holyrocklee/Internship/blob/master/WebAutomation/test/webtest.py;>7
+255;16be96e3c6cc6ac83349eee9632bb7f9765e99e8;"a = 1
+    b = 2
+    c = 3
+    d = 4
+    e = 5
+    f = 6
+    g = 7
+    h = 8
+    i = 9
+    j = 10
+    k = 11
+    l = 12
+    m = 13
+    n = 14
+    o = 15
+    p = 16
+    q = 17
+    r = 18
+    s = 19
+    t = 20
+    u = 21
+    v = 22
+    w = 23
+    x = 24
+    y = 25
+    z = 26";78;3;https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py;3
+256;72a565623c7ae62b6488db3ddfe11b6de53ffb34;""", ""1:00 PM"", ""2:00 PM"", ""3:00 PM"", ""4:00 PM"", ""5:00 PM"", ""6:00 PM"", ""7:00 PM"", ""8:00 PM"", ""9:00 PM"", ""10:00 PM""";71;1;https://github.com/rxkt/Ama_Raid_Bot/blob/master/amabot.py;>7
+257;87d694589ac4f070de7ddb8de182c7359a4172be;"""10:00"", ""11:00"", ""12:00"", ""13:00"", ""14:00"", ""15:00"", ""16:00"", ""17:00"", ""18:00"", ""19:00"", ""20:00"", ""21:00"", ""22:00"", ""23:00""]";84;2;https://github.com/faical-yannick-congo/news-backend/blob/master/news-service/news/endpoints/coverage_endpoint.py;>7
+258;a1ec0be5df1321ae12b2e74acc601a181af0532e;"""10:00"", ""10:30"", ""11:00"", ""11:30"", ""12:00"", ""12:30"", ""13:00"", ""13:30"", ""14:00"", ""14:30"", ""15:00"", ""15:30"", ""16:00"", ""16:30"", ""17:00"", ""17:30"", ""18:00"", ""18:30"", ""19:00"", ""19:30"",";120;3;https://github.com/Schlegen/Microgrid-Manager/blob/master/tools.py;>7
+259;662476e59a96a119b89f796faf116e2d1543f13c;= [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199, 211, 223, 227,;100;3;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+260;a00de22eb0c4a03289b3ece804b2e7dd0de1b66e;"if n == 2 or n == 3: return True
+    if n < 2 or n%2 == 0: return False
+    if n < 9: return True
+    if n%3 == 0: return False
+    r = int(n**0.5)
+    f = 5
+    while f <= r:
+        if n%f == 0: return False
+        if n%(f+2) == 0: return False
+        f +=6
+    return True";94;2;https://github.com/hkws/atcoder/blob/master/ABC142/D.py;>7
+261;a00de22eb0c4a03289b3ece804b2e7dd0de1b66e;"if n == 2 or n == 3: return True
+    if n < 2 or n%2 == 0: return False
+    if n < 9: return True
+    if n%3 == 0: return False
+    r = int(n**0.5)
+    f = 5
+    while f <= r:
+        if n%f == 0: return False
+        if n%(f+2) == 0: return False
+        f +=6
+    return True";94;2;https://github.com/hkws/atcoder/blob/master/ABC142/D.py;>7
+262;90b47ef628f14b678d612f1d24960af0b6b68391;"if n == 2:
+        return True
+    if n % 2 == 0 or n <= 1:
+        return False
+
+    sqr = int(math.sqrt(n)) + 1
+
+    for divisor in range(3, sqr, 2):
+        if n % divisor == 0:
+            return False
+    return True";60;1;https://github.com/skalam02/Crypto/blob/master/rsa.py;>7
+263;0fcee6e1cf3e8ccf71a129b3a2e7be174ca28ee0;"if n == 2:
+        return True
+    if n % 2 == 0 or n <= 1:
+        return False
+
+    sqr = int(n**0.5) + 1
+
+    for divisor in range(3, sqr, 2):
+        if n % divisor == 0:
+            return False
+    return True";60;1;https://github.com/thbertoldi/trustcode_desafio/blob/master/fourth.py;>7
+264;a00de22eb0c4a03289b3ece804b2e7dd0de1b66e;"if n == 2 or n == 3: return True
+    if n < 2 or n % 2 == 0: return False
+    if n < 9: return True
+    if n % 3 == 0: return False
+    r = int(n**0.5)
+    f = 5
+    while f <= r:
+        if n % f == 0: return False
+        if n % (f + 2) == 0: return False
+        f += 6
+    return True";94;2;https://github.com/hkws/atcoder/blob/master/ABC142/D.py;>7
+265;662476e59a96a119b89f796faf116e2d1543f13c;[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199, 211, 223, 227, 229;100;3;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+266;662476e59a96a119b89f796faf116e2d1543f13c;[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199, 211, 223, 227, 229;100;3;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+267;662476e59a96a119b89f796faf116e2d1543f13c;, 233, 239, 241, 251, 257, 263, 269, 271, 277, 281, 283, 293, 307, 311, 313, 317, 331, 337, 347, 349, 353, 359, 367, 373, 379, 383, 389, 397, 401, 409, 419, 421, 431, 433, 439, 443, 449, 457, 461, 463, 467, 479, 487, 491, 499;90;2;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+268;662476e59a96a119b89f796faf116e2d1543f13c;, 503, 509, 521, 523, 541, 547, 557, 563, 569, 571, 577, 587, 593, 599, 601, 607, 613, 617, 619, 631, 641, 643, 647, 653, 659, 661, 673, 677, 683, 691, 701, 709, 719, 727, 733, 739, 743, 751, 757, 761, 769, 773, 787, 797, 809, 811, 821, 823, 827, 829, 839, 853, 857, 859, 863, 877, 881, 883, 887, 907, 911, 919, 929, 937, 941, 947, 953, 967, 971, 977, 983, 991, 997];147;8;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+269;f0374e36670fa34a2c3264679ae2a608cc8b051a;"# NOTE the stream=True parameter
+    r = requests.get(url, stream=True)
+    with open(local_filename, 'wb') as f:
+        for chunk in r.iter_content(chunk_size=1024):
+            if chunk:  # filter out keep-alive new chunks
+                f.write(chunk)
+                #f.flush() commented by recommendation from J.F.Sebastian
+    return local_filename";77;2;https://github.com/yeony102/DTW2018/blob/master/Week06/pinterest.py;>7
+270;c858f69d234ae6fdf3c9240ea1c57a080d0163a0;"image_data = open(image_path, ""rb"").read()
+    headers    = {'Ocp-Apim-Subscription-Key': subscription_key,
+                  'Content-Type': 'application/octet-stream'}
+    params     = {'visualFeatures': 'Categories,Description,Color'}
+    response = requests.post(
+        analyze_url, headers=headers, params=params, data=image_data)
+    response.raise_for_status()
+
+    # The 'analysis' object contains various fields that describe the image. The most
+    # relevant caption for the image is obtained from the 'description' property.
+    analysis = response.json()";121;7;https://github.com/feniculi/Azure/blob/master/jumple-cognitive-services-633bdce3da9e/Test Computer Vision/riconocimento_immagine_locale.py;4
+271;a34690a93f7e38c8de2c4f333bd147d39441c1ec;"for i in range(1, 5):
+        for j in range(1, 5):
+            for k in range(1, 5):
+                for l in range(1, 5):
+                    for m in range(1, 5):
+                        for n in range(1, 5):";60;2;https://github.com/ljeabmreosn/projecteuler/blob/master/python/pe205.py;2
+272;971a5155a320a23115a41d16f14b6ccc6ffe9801;10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54;89;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+273;971a5155a320a23115a41d16f14b6ccc6ffe9801;10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52;85;2;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+274;85df0d22a300a937b676a185f6da4d658e61c522;"#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an ""AS IS"" BASIS, WITHOUT
+#    WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+#    License for the specific language governing permissions and limitations
+#    under the License.";59;1;https://github.com/blkart/glance/blob/master/glance/async/utils.py;0
+275;c834b0254318ff35a015d0e79f7ddfba6f7368f9;"Copyright (c) 2017-present, Facebook, Inc.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the LICENSE file in
+# the root directory of this source tree. An additional grant of patent rights
+# can be found in the PATENTS file in the same directory.";61;1;https://github.com/zhongxia96/MGSum/blob/master/fairseq/tasks/abstractive_and_extractive.py;0
+276;5c2b775890ed9d5219db155e56656d9fc53152cc;"#    This program is distributed in the hope that it will be useful,
+#    but WITHOUT ANY WARRANTY; without even the implied warranty of
+#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#    GNU Affero General Public License for more details.
+#
+#    You should have received a copy of the GNU Affero General Public License
+#    along with this program.  If not, see <http";74;2;https://github.com/kevinspaceyvn/odoo-clearcorp/blob/master/TODO-9.0/project_subproject/project_project.py;0
+277;c101dc6dd83eca9260fbfc0369979a7965240df4;\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d;77;1;https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py;>7
+278;32cae5b3f480c11171b1162046f11fcb1a27270f;['AL','AK','AZ','AR','CA','CO','CT','DE','DC','FL','GA','HI','ID','IL','IN','IA','KS','KY','LA','ME','MD','MA','MI','MN','MS','MO','MT','NE','NV','NH','NJ','NM','NY','NC','ND','OH','OK','OR','PA','RI','SC','SD','TN','TX','UT','VT','VA','WA','WV','WI','WY'];205;10;https://github.com/rcally72/501Project1/blob/master/501Project1_Part2 v3.py;5
+279;971a5155a320a23115a41d16f14b6ccc6ffe9801;,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54;98;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+280;27ea56215171eda10f2b8dafa08ae4c8ff75e2c8;"/w1_slave"")
+    # Read all of the text in the file.
+    text = tfile.read()
+    # Close the file now that the text has been read.
+    tfile.close()
+    # Split the text with new lines (\n) and select the second line.
+    secondline = text.split(""\n"")[1]
+    # Split the line into words, referring to the spaces, and select the 10th word (counting from 0).
+    temperaturedata = secondline.split("" "")[9]
+    # The first two characters are ""t="", so get rid of those and convert the temperature from a string to a number.
+    temperature = float(temperaturedata[2:])
+    # Put the decimal point in the right place and display it.
+    temperature = temperature / 1000";159;9;https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py;>7
+281;27ea56215171eda10f2b8dafa08ae4c8ff75e2c8;"/w1_slave"")
+    # Read all of the text in the file.
+    text = tfile.read()
+    # Close the file now that the text has been read.
+    tfile.close()
+    # Split the text with new lines (\n) and select the second line.
+    secondline = text.split(""\n"")[1]
+    # Split the line into words, referring to the spaces, and select the 10th word (counting from 0).
+    temperaturedata = secondline.split("" "")[9]
+    # The first two characters are ""t="", so get rid of those and convert the temperature from a string to a number.
+    temperature = float(temperaturedata[2:])
+    # Put the decimal point in the right place and display it.
+    temperature = temperature / 1000";159;9;https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py;>7
+282;66bc4cdb34b19d1c00c02dd980d8ea139b170094;"if lines[0].strip()[-3:] == 'YES':
+        equals_pos = lines[1].find('t=')
+        if equals_pos != -1:
+            temp_string = lines[1][equals_pos+2:]
+            temp_c = float(temp_string) / 1000.0";63;2;https://github.com/heuristik1/eai_brms/blob/master/tempsensor/readtemp.py;>7
+283;15c61c768eb373210b4686ef71c948b0acc20fc3;"()
+            while lines[0].strip()[-3:] != ""YES"":
+                time.sleep(0.2)
+                lines = read_temp_raw()
+            equals_pos = lines[1].find(""t="")
+            if equals_pos != -1:
+                temp_string = lines[1][equals_pos+2:]
+                temp_c = float(temp_string) / 1000.0
+                temp_f = temp_c * 9.0 / 5.0 + 32.0";93;2;https://github.com/sejgit/fishtank/blob/master/fishtank.py;>7
+284;425ddffd44b7825c94c77c2e1d35a333a81035ef;0x00, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,;230;2;https://github.com/sbhklr/Brutus/blob/master/RPi-Core/gfx/logo.py;>7
+285;27ea56215171eda10f2b8dafa08ae4c8ff75e2c8;"/w1_slave"")
+    # Read all of the text in the file.
+    text = tfile.read()
+    # Close the file now that the text has been read.
+    tfile.close()
+    # Split the text with new lines (\n) and select the second line.
+    secondline = text.split(""\n"")[1]
+    # Split the line into words, referring to the spaces, and select the 10th word (counting from 0).
+    temperaturedata = secondline.split("" "")[9]
+    # The first two characters are ""t="", so get rid of those and convert the temperature from a string to a number.
+    temperature = float(temperaturedata[2:])
+    # Put the decimal point in the right place and display it.";154;9;https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py;>7
+286;e74fbd2de9afeacf9f43249f451e262e560852a5;"def __init__(self, x=0.0, y=0.0, heading=0.0, turning=2*pi/10, distance=1.0):
+        """"""This function is called when you create a new robot. It sets some of
+        the attributes of the robot, either to their default values or to the values
+        specified when it is created.""""""
+        self.x = x
+        self.y = y
+        self.heading = heading
+        self.turning = turning # only applies to target robots who constantly move in a circle
+        self.distance = distance # only applies to target bot, who always moves at same speed.
+        self.turning_noise    = 0.0
+        self.distance_noise    = 0.0
+        self.measurement_noise = 0.0
+
+
+    def set_noise(self, new_t_noise, new_d_noise, new_m_noise):
+        """"""This lets us change the noise parameters, which can be very
+        helpful when using particle filters.""""""
+        self.turning_noise    = float(new_t_noise)
+        self.distance_noise    = float(new_d_noise)
+        self.measurement_noise = float(new_m_noise)
+
+
+    def move(self, turning, distance, tolerance = 0.001, max_turning_angle = pi):
+        """"""This function turns the robot and then moves it forward.""""""
+        # apply noise, this doesn't change anything if turning_noise
+        # and distance_noise are zero.
+        turning = random.gauss(turning, self.turning_noise)
+        distance = random.gauss(distance, self.distance_noise)
+
+        # truncate to fit physical limitations
+        turning = max(-max_turning_angle, turning)
+        turning = min( max_turning_angle, turning)
+        distance = max(0.0, distance)
+
+        # Execute motion
+        self.heading += turning
+        self.heading = angle_trunc(self.heading)
+        self.x += distance * cos(self";353;20;https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py;5
+287;e74fbd2de9afeacf9f43249f451e262e560852a5;"""""""
+        self.turning_noise = float(new_t_noise)
+        self.distance_noise = float(new_d_noise)
+        self.measurement_noise = float(new_m_noise)
+    
+    def move(self, turning, distance, tolerance = 0.001, max_turning_angle = pi):
+        """"""
+        This function turns the robot and then moves it forward";60;2;https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py;5
+288;e74fbd2de9afeacf9f43249f451e262e560852a5;"def __init__(self, x=0.0, y=0.0, heading=0.0, turning=2*pi/10, distance=1.0):
+        """"""This function is called when you create a new robot. It sets some of 
+        the attributes of the robot, either to their default values or to the values
+        specified when it is created.""""""
+        self.x = x
+        self.y = y
+        self.heading = heading
+        self.turning = turning # only applies to target robots who constantly move in a circle
+        self.distance = distance # only applies to target bot, who always moves at same speed.
+        self.turning_noise    = 0.0
+        self.distance_noise    = 0.0
+        self.measurement_noise = 0.0
+
+
+    def set_noise(self, new_t_noise, new_d_noise, new_m_noise):
+        """"""This lets us change the noise parameters, which can be very
+        helpful when using particle filters.""""""
+        self.turning_noise    = float(new_t_noise)
+        self.distance_noise    = float(new_d_noise)
+        self.measurement_noise = float(new_m_noise)
+
+
+    def move(self, turning, distance, tolerance=0.001, max_turning_angle=pi):
+        """"""This function turns the robot and then moves it forward.""""""
+        # apply noise, this doesn't change anything if turning_noise
+        # and distance_noise are zero.
+        turning = random.gauss(turning, self.turning_noise)
+        distance = random.gauss(distance, self.distance_noise)
+
+        # truncate to fit physical limitations
+        turning = max(-max_turning_angle, turning)
+        turning = min( max_turning_angle, turning)
+        distance = max(0.0, distance)
+
+        # Execute motion
+        self.heading += turning
+        self.heading = angle_trunc(self.heading)
+        self.x += distance * cos(";352;20;https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py;5
+289;e74fbd2de9afeacf9f43249f451e262e560852a5;"def __init__(self, x=0.0, y=0.0, heading=0.0, turning=2*pi/10, distance=1.0):
+        """"""This function is called when you create a new robot. It sets some of 
+        the attributes of the robot, either to their default values or to the values
+        specified when it is created.""""""
+        self.x = x
+        self.y = y
+        self.heading = heading
+        self.turning = turning # only applies to target robots who constantly move in a circle
+        self.distance = distance # only applies to target bot, who always moves at same speed.
+        self.turning_noise    = 0.0
+        self.distance_noise    = 0.0
+        self.measurement_noise = 0.0
+
+
+    def set_noise(self, new_t_noise, new_d_noise, new_m_noise):
+        """"""This lets us change the noise parameters, which can be very
+        helpful when using particle filters.""""""
+        self.turning_noise    = float(new_t_noise)
+        self.distance_noise    = float(new_d_noise)
+        self.measurement_noise = float(new_m_noise)
+
+
+    def move(self, turning, distance, tolerance = 0.001, max_turning_angle = pi):
+        """"""This function turns the robot and then moves it forward.""""""
+        # apply noise, this doesn't change anything if turning_noise
+        # and distance_noise are zero.
+        turning = random.gauss(turning, self.turning_noise)
+        distance = random.gauss(distance, self.distance_noise)
+
+        # truncate to fit physical limitations
+        turning = max(-max_turning_angle, turning)
+        turning = min( max_turning_angle, turning)
+        distance = max(0.0, distance)
+
+        # Execute motion
+        self.heading += turning
+        self.heading = angle_trunc(self.heading)
+        self.x += distance * cos(";352;20;https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py;5
+290;e74fbd2de9afeacf9f43249f451e262e560852a5;"def __init__(self, x=0.0, y=0.0, heading=0.0, turning=2*pi/10, distance=1.0):
+        """"""This function is called when you create a new robot. It sets some of
+        the attributes of the robot, either to their default values or to the values
+        specified when it is created.""""""
+        self.x = x
+        self.y = y
+        self.heading = heading
+        self.turning = turning # only applies to target robots who constantly move in a circle
+        self.distance = distance # only applies to target bot, who always moves at same speed.
+        self.turning_noise    = 0.0
+        self.distance_noise    = 0.0
+        self.measurement_noise = 0.0
+
+
+    def set_noise(self, new_t_noise, new_d_noise, new_m_noise):
+        """"""This lets us change the noise parameters, which can be very
+        helpful when using particle filters.""""""
+        self.turning_noise    = float(new_t_noise)
+        self.distance_noise    = float(new_d_noise)
+        self.measurement_noise = float(new_m_noise)
+
+
+    def move(self, turning, distance, tolerance=0.001, max_turning_angle=pi):
+        """"""This function turns the robot and then moves it forward.""""""
+        # apply noise, this doesn't change anything if turning_noise
+        # and distance_noise are zero.
+        turning = random.gauss(turning, self.turning_noise)
+        distance = random.gauss(distance, self.distance_noise)
+
+        # truncate to fit physical limitations
+        turning = max(-max_turning_angle, turning)
+        turning = min( max_turning_angle, turning)
+        distance = max(0.0, distance)
+
+        # Execute motion
+        self.heading += turning
+        self.heading = angle_trunc(self.heading)
+        self.x += distance * cos(self";353;20;https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py;5
+291;b84be4250873fec8f80b0194f70170020bfd5720;".0, 1.0])
+    glLightfv(GL_LIGHT0, GL_DIFFUSE, [1.0, 1.0, 1.0, 1.0])
+    glLightfv(GL_LIGHT0, GL_SPECULAR, [1.0, 1.0, 1.0, 1.0])
+    glEnable(GL_LIGHT0)
+    glEnable(GL_LIGHTING)
+    glEnable(";66;3;https://github.com/clover1967/pj_graphic/blob/master/pj2/teapot.py;>7
+292;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,;90;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+293;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48;95;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+294;6f6654aeec5d798a590781b5c69fdfffb0f91548;"(object):
+    """"""Simple vocabulary wrapper.""""""
+    def __init__(self):
+        self.word2idx = {}
+        self.idx2word = {}
+        self.idx = 0
+
+    def add_word(self, word):
+        if not word in self.word2idx:
+            self.word2idx[word] = self.idx
+            self.idx2word[self.idx] = word
+            self.idx += 1
+
+    def __call__(self, word):
+        if not word in self.word2idx:
+            return self.word2idx['<unk>']
+        return self.word2idx[word]
+
+    def __len__(self):
+        return len(self.word2idx)";126;4;https://github.com/Aiman-Jabaren/Image-Captioning-using-LSTM-network/blob/master/pretrained_embedding.py;0
+295;c16151c80c7598b36ad40fd178926c8dda519605;2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7], [7, 8], [8, 9], [9, 10], [10, 11], [11, 12], [12, 13], [13, 14], [14, 15], [15, 16], [16, 17], [17, 18], [18, 19], [19, 20];110;4.0;https://github.com/sony/nnabla-examples/blob/master/GANs/reenactgan/utils/preprocess_utils.py;>7
+296;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47;93;3.0;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+297;7ebb786cd066594187910cfba3b3e58c3603b02d;= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', ';99;4;https://github.com/Shiva-gs/Project3/blob/master/stock_data.py;>7
+298;9382a1faf862ff3c879e84459dbce7ddba467ef5;")
+    glBegin(GL_QUADS)
+    glColor3f(1.0, 0.0, 0.0)
+    glVertex3f( 1.0, 1.0, -1.0)
+    glVertex3f(-1.0, 1.0, -1.0)
+    glVertex3f(-1.0, 1.0,  1.0)
+    glVertex3f( 1.0, 1.0,  1.0)
+    glColor3f(0.0, 1.0, 0.0)
+    glVertex3f( 1.0,-1.0,  1.0)
+    glVertex3f(-1.0,-1.0,  1.0)
+    glVertex3f(-1.0,-1.0, -1.0)
+    glVertex3f( 1.0,-1.0, -1.0)
+    glColor3f(0.0, 0.0, 1.0)
+    glVertex3f( 1.0, 1.0, 1.0)
+    glVertex3f(-1.0, 1.0, 1.0)
+    glVertex3f(-1.0,-1.0, 1";213;10;https://github.com/Nibba2018/gluppy/blob/master/trans_rot_cube.py;>7
+299;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+300;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+301;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+302;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+303;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+304;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+305;81c282288dfee4875a4f8e004d5f3a6ccdd2a49f;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','TRV','UTX','UNH','VZ',';115;3;https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py;>7
+306;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+307;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+308;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+309;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+310;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+311;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+312;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG',';95;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+313;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+314;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+		return arr
+	pivot = arr[len(arr) // 2]
+	left = [x for x in arr if x < pivot]
+	middle = [x for x in arr if x == pivot]
+	right = [x for x in arr if x > pivot]
+	return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+315;5940ba60408240b861d1371d7df60df1fc31835c;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";74;5;https://github.com/gaowenhao/PythonAlgorithm/blob/master/sort/quick_sort.py;1
+316;099c9271fb7cad9c165584be13e16d396017aeca;"pivot = arr[len(arr) // 2]
+        left = [x for x in arr if x < pivot]
+        middle = [x for x in arr if x == pivot]
+        right = [x for x in arr if x > pivot]
+        return quick_sort(left) + middle + quick_sort(right)";64;2;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+317;9b3598903f3e1a54a5319dce6b56d92b6889bb64;"less = []
+    pivotList = []
+    more = []
+    if len(arr) <= 1:
+        return arr
+    else:
+        pivot = arr[0]
+        for i in arr:
+            if i < pivot:
+                less.append(i)
+            elif i > pivot:
+                more.append(i)
+            else:
+                pivotList.append(i)
+        less = quick_sort(less)
+        more = quick_sort(more)
+        return less + pivotList + more";84;6;https://github.com/maxgardiner/sorting-algorthms/blob/master/sorting_algorithms.py;1
+318;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+319;0198c9dba18ccdd13c2092a1ee70fb4d9f90b0eb;"if len(arr) < 2:
+        return arr
+    else:
+        pivot = arr[0]
+        less = [i for i in arr[1:] if i < pivot]
+        greater = [i for i in arr[1:] if i > pivot]
+        return quick_sort(less) + [pivot] + quick_sort(greater)";66;2;https://github.com/mrdulin/python-codelab/blob/master/src/algorithm/quick_sort.py;1
+320;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+321;099c9271fb7cad9c165584be13e16d396017aeca;"pivot = arr[len(arr) // 2]
+        left = [x for x in arr if x < pivot]
+        middle = [x for x in arr if x == pivot]
+        right = [x for x in arr if x > pivot]
+        return quick_sort(left) + middle + quick_sort(right)";64;2;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+322;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+323;9b3598903f3e1a54a5319dce6b56d92b6889bb64;"less = []
+    pivotList = []
+    more = []
+    if len(arr) <= 1:
+        return arr
+    else:
+        pivot = arr[0]
+        for i in arr:
+            if i < pivot:
+                less.append(i)
+            elif i > pivot:
+                more.append(i)
+            else:
+                pivotList.append(i)
+        less = quick_sort(less)
+        more = quick_sort(more)
+        return less + pivotList + more";84;6;https://github.com/maxgardiner/sorting-algorthms/blob/master/sorting_algorithms.py;1
+324;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+325;2252b5bd0da7241aec6675c8898e18c3e4dddfc7;"less = []
+    pivot_list = []
+    more = []
+    if len(arr) <= 1:
+        return arr
+    else:
+        pivot = arr[0]
+        for i in arr:
+            if i < pivot:
+                less.append(i)
+            elif i > pivot:
+                more.append(i)
+            else:
+                pivot_list.append(i)
+        less = quick_sort(less)
+        more = quick_sort(more)
+        return less + pivot_list + more";84;6;https://github.com/garciaae/median50/blob/master/sorting/quicksort.py;1
+326;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+327;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+328;099c9271fb7cad9c165584be13e16d396017aeca;":
+    if len(arr) <= 1 :
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";76;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+329;abd2a5bc34797016cf29ad70805a629175962b85;":
+        return arr
+    pivot = arr[0]
+    left = []
+    right = []
+    for i in range(1, len(arr)) :
+        if arr[i] < pivot :
+            left.append(arr[i])
+        else :
+            right.append(arr[i])
+    return quick_sort(left) + [pivot] + quick_sort(right)";72;1;https://github.com/HanifCarroll/DSA-Practice/blob/master/python/sorting/quick_sort.py;1
+330;099c9271fb7cad9c165584be13e16d396017aeca;":
+    if len(arr) <= 1 :
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";76;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+331;6ea15d729be6e3fa7ac9a454f483d54d5f63ad66;"list):
+    if len(list) <= 1:
+        return list
+    else:
+        pivot = list[0]
+        less = [i for i in list[1:] if i <= pivot]
+        greater = [i for i in list[1:] if i > pivot]
+        return quick_sort(less) + [pivot] + quick_sort(greater)";71;3;https://github.com/kahee/Python-Study/blob/master/data_structure/sort/quick_sort.py;1
+332;099c9271fb7cad9c165584be13e16d396017aeca;"arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";78;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+333;099c9271fb7cad9c165584be13e16d396017aeca;"if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quick_sort(left) + middle + quick_sort(right)";75;3;https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py;1
+334;21f646e28b5aa5d074688a587f8cc16d2d05a5b0;"a):
+    if len(a) <= 1:
+        return a
+    pivot = a[len(a) // 2]
+    left = [x for x in a if x < pivot]
+    middle = [x for x in a if x == pivot]
+    right = [x for x in a if x > pivot]
+    return";67;2;https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py;1
+335;6866b3eef9754b93a23047b81b0b6d7064a989ed;pw[0] + pw[1] + pw[2] + pw[3] + pw[4] + pw[5] + pw[6] + pw[7] + pw[8] + pw[9] + pw[10] + pw[11] + pw[12] + pw[13];69;2;https://github.com/RelyingEarth87/PracticePython/blob/master/passwordgenerator.py;3
+336;ef64dcb139235e9eaee8d75108fe8ba5c5ef8fee;".replace(""1"", """").replace(""2"", """").replace(""3"", """").replace(""4"", """").replace(""5"", """").replace(""6"", """").replace(""7"", """").replace(""8"", """").replace(""9"", """").replace(""0"", """")
+⋯
+"", """").replace(""!"", """").replace(""@"", """").replace(""#"", """").replace(""$"", """").replace(""%"", """").replace(""^"", """").replace(""&"", """").replace(""*"", """").replace(""("", """").replace("")"", """").replace(""";209;11;https://github.com/noeleon930/firetruckingHWs/blob/master/WSM/Project1/codes/VectorSpace.py;3
+337;3b81ee5a96ea9b5b5a0ec3ea35bd3895947fd7d8;"required for this module')
+
+    # collect the parameters that are passed to boto3. Keeps us from having so many scalars floating around.
+    stack_params = {
+        'Capabilities': ['CAPABILITY_IAM', 'CAPABILITY_NAMED_IAM'],
+        'ClientRequestToken': to_native(uuid.uuid4()),
+    }
+    state = module.params";62;1;https://github.com/angystardust/ansible/blob/master/lib/ansible/modules/cloud/amazon/cloudformation.py;3
+338;5a625b09081aca8c504d9ee48c61a15cf4173045;"""User-Agent"": ""Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36"",
+        ""X-Requested-With"": ""XMLHttpRequest"",
+        """;63;3;https://github.com/qiuxianZz/qq_spider/blob/master/weixin/test1.py;>7
+339;5a625b09081aca8c504d9ee48c61a15cf4173045;"""User-Agent"": ""Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36"",
+        ""X-Requested-With"": ""XMLHttpRequest"",
+        """;63;3;https://github.com/qiuxianZz/qq_spider/blob/master/weixin/test1.py;>7
+340;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll";69;2;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+341;4992ed94b48a8e1e5d77f8c13a21258f20e616bb;= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','UTX','UNH','VZ',';107;3;https://github.com/jiewwantan/StarTrader/blob/master/compare.py;>7
+342;5ceada08cfab615035f6a845610f25e4bd50b246;'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on;130;6;https://github.com/shayneobrien/conversational-analysis/blob/master/src/utils.py;>7
+343;bc6a870dbfef043d927eff793af24291cc7268e2;""", ""he"", ""him"", ""his"", ""himself"", ""she"", ""her"", ""hers"", ""herself"", ""it"", ""its"", ""itself"", ""they"", ""them"", ""their"", ""theirs"", ""themselves"", ""what"", ""which"", """;75;1;https://github.com/ammar188/jobAssignment/blob/master/nlp/nlp.py;>7
+344;077a277acd2e9431ffb39e07c10d9707e3ee344b;"""a"", ""b"", ""c"", ""d"", ""e"", ""f"", ""g"", ""h"", ""i"", ""j"", ""k"", ""l"", ""m"", ""n"", ""o"", ""p"", ""q"", ""r"", ""s"", ""t"", ""u"", ""v"", ""w"", ""x"", ""y"", ""z""";103;4;https://github.com/Villager-Dev/hypixel-stats/blob/master/cogs/cmds/settings.py;>7
+345;bd0d429e0742b94a8b820221dd64c909f7b47c13;10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,;100;1;https://github.com/rogerkenny/pystuff/blob/master/Solutions.py;>7
+346;8b06b6b0365888726b12724e05a6da81fc1ad47f;'A': 0, 'B': 1, 'C': 2, 'D': 3, 'E': 4, 'F': 5, 'G': 6, 'H': 7, 'I': 8, 'J': 9, 'K': 10, 'L': 11, 'M': 12, 'N': 13, 'O': 14, 'P': 15, 'Q': 16, 'R': 17, 'S': 18, 'T':;118;5;https://github.com/fabiocaccamo/python-codicefiscale/blob/master/codicefiscale/codicefiscale.py;>7
+347;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;"():
+    resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr";75;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;0
+348;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;"():
+    resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs.BeautifulSoup(resp.text, 'lxml')
+    table = soup.find('table', {'class': 'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text
+        tickers.append(ticker)";103;4;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;0
+349;73ebdd2f75a8ca79dd317ae39c5285fb7c2c4365;"()
+    else:
+        with open(""sp500tickers.pickle"", ""rb"") as f:
+            tickers = pickle.load(f)
+    if not os.path.exists('stock_dfs'):
+        os.makedirs('stock_dfs')
+
+    start = dt.datetime(2000, 1, 1)
+    end = dt.datetime(2016, 12, 31)
+    for ticker in tickers:
+        print(ticker)
+        if not os.path.exists('stock_dfs/{}.csv'.format(ticker)):
+            df = web.DataReader(ticker, 'yahoo', start, end)
+            df.to_csv('stock_dfs/{}.csv'.format(ticker))
+        else:
+            print('Already have {}'.format(ticker))";155;6;https://github.com/infiniteloop91/Python_Projects/blob/master/S&P_Scraper.py;>7
+350;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,;98;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+351;8a08651c753c2c5d40ab282024384e108eb8b5d8;"values (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)"""""",";66;4;https://github.com/kbalsamy/eallot/blob/master/eallot/portal/api.py;>7
+352;c6540a8a78181301d8e00c27331a12a26e9f469a;,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18,p19,p20,p21,p22,p23,p24,p25,p26,p27,p28,p29,p30,p31,p32,p33,p34;66;2;https://github.com/outofink/twisted-pentago/blob/master/gamedb.py;0
+353;4d13d1320e6f71fcac284159f5443962443ceb50;"# http://stackoverflow.com/questions/2068372/fastest-way-to-list-all-primes-below-n-in-python/3035188#3035188
+    """""" Input n>=6, Returns a list of primes, 2 <= p < n """"""
+    correction = (n%6>1)
+    n = {0:n,1:n-1,2:n+4,3:n+3,4:n+2,5:n+1}[n%6]
+    sieve = [True] * (n/3)
+    sieve[0] = False
+    for i in xrange(int(n**0.5)/3+1):
+      if sieve[i]:
+        k=3*i+1|1
+        sieve[      ((k*k)/3)      ::2*k]=[False]*((n/6-(k*k)/6-1)/k+1)
+        sieve[(k*k+4*k-2*k*(i&1))/3::2*k]=[False]*((n/6-(k*k+4*k-2*k*(i&1))/6-1)/k+1)
+    return [2,3] + [3*i+1|1 for i in xrange(1,n/3-correction) if sieve[i]]";309;16;https://github.com/ArturoBlazquez/Project-Euler/blob/master/10.py;0
+354;f26a638e6f0e5c795f679fb1bf040962839cdd39;"{
+        0: ""C"",
+        1: ""C#"",
+        2: ""D"",
+        3: ""D#"",
+        4: ""E"",
+        5: ""F"",
+        6: ""F#"",
+        7: ""G"",
+        8: ""G#"",
+        9: ""A"",
+        10: ""A#"",
+        11: ""B""
+    }";78;3;https://github.com/vrnmthr/CptGen/blob/master/CptGen/CptGen/utils.py;0
+355;96826b181bdcae40df1006b93a8b4fe5b83ad735;"():
+    print(""\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\";499;2;https://github.com/elodietheelectronicfairy/blood_runner/blob/master/blood_runner_for_embedd.py;>7
+356;7a28d2ce8c0641197d5927debf7e2d961e165c54;"def start(bot, update):   
+        bot.send_message(chat_id=update.message.chat_id, text=""I'm a bot, please talk to me!"")   
+
+    def echo(bot, update):   
+        bot.send_message(chat_id=update.message.chat_id, text=update.message.text)   
+
+    def caps(bot, update, args):   
+        text_caps = '";77;4;https://github.com/Paddy420/pybot/blob/master/pybot.py;4
+357;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49,;98;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;2
+358;d03c6a562fb23b5afcd5175a1cacd19cb37806a5;[0,0,1],[0,0,2],[0,0,3],[0,0,4],[0,0,5],[0,0,6],[0,0,7],[0,0,8],[0,0,9],[0,0,10],[0,0,11],[0,0,12],[0,0,13],[0,0,14],[0,0;116;7;https://github.com/marcusljx/python-sandbox/blob/master/puzzles/TowerOfHanoi/HanoiTower.py;>7
+359;ee44cf1b6b1805f8ae909b88840460baf21af333;"Let d(n) be defined as the sum of proper divisors of n (numbers less than n which divide evenly into n).
+    If d(a) = b and d(b) = a, where a ≠ b, then a and b are an amicable pair and each of a and b are called amicable numbers.
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44, 55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4, 71 and 142; so d(284) = 220.
+    Evaluate the sum of all the amicable numbers under 10000.";140;6;https://github.com/alistair-clark/project-euler/blob/master/problem21.py;0
+360;e445c6716afdb916d46e4c111cd0ba00f1994fac;"""""""
+    Let d(n) be defined as the sum of proper divisors of n (numbers less than n
+    which divide evenly into n). If d(a) = b and d(b) = a, where a != b, then a
+    and b are an amicable pair and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44,
+    55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4,
+    71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.
+    """"""";147;5;https://github.com/tofu-rocketry/project-euler/blob/master/ProjectEulerAnswers.py;0
+361;a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89;"Let d(n) be defined as the sum of proper divisors of n (numbers less than n
+    which divide evenly into n). If d(a) = b and d(b) = a, where a != b, then
+    a and b are an amicable pair and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44,
+    55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4,
+    71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.";141;6;https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py;0
+362;a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89;"Let d(n) be defined as the sum of proper divisors of n (numbers less than n
+    which divide evenly into n). If d(a) = b and d(b) = a, where a != b, then a
+    and b are an amicable pair and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44,
+    55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4,
+    71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.";141;6;https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py;0
+363;ee44cf1b6b1805f8ae909b88840460baf21af333;"Let d(n) be defined as the sum of proper divisors of n (numbers less than n which divide evenly into n).
+    If d(a) = b and d(b) = a, where a ≠ b, then a and b are an amicable pair and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44, 55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4, 71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.";140;7;https://github.com/alistair-clark/project-euler/blob/master/problem21.py;0
+364;e445c6716afdb916d46e4c111cd0ba00f1994fac;"""""""
+    Let d(n) be defined as the sum of proper divisors of n (numbers less than n
+    which divide evenly into n).
+    If d(a) = b and d(b) = a, where a != b, then a and b are an amicable pair
+    and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44,
+    55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4,
+    71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.
+    """"""";147;5;https://github.com/tofu-rocketry/project-euler/blob/master/ProjectEulerAnswers.py;0
+365;a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89;"Let d(n) be defined as the sum of proper divisors of n (numbers less than n
+    which divide evenly into n).
+    If d(a) = b and d(b) = a, where a != b, then a and b are an amicable pair
+    and each of a and b are called amicable numbers.
+
+    For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44,
+    55 and 110; therefore d(220) = 284. The proper divisors of 284 are 1, 2, 4,
+    71 and 142; so d(284) = 220.
+
+    Evaluate the sum of all the amicable numbers under 10000.";141;7;https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py;0
+366;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46;91;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;1
+367;971a5155a320a23115a41d16f14b6ccc6ffe9801;1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49;97;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;1
+368;5d30bbfdf55673e86b167fe3560491f89b24bed0;, 1468, 1470, 1472, 1474, 1476, 1478, 1480, 1482, 1484, 1486, 1488, 1490, 1492, 1494, 1496, 1498, 1500, 1502, 1504, 1506, 1508, 1510, 1512, 1514, 1516, 1518, 1520, 1522, 1524, 1526, 1528,;63;1;https://github.com/darklinden/python_algorithm_test/blob/master/01/test.py;1
+369;7ea30a2d47d5a31e795a0c8fdd20752170392e0c;0:0,1:0,2:0,3:0,4:0,5:0,6:0,7:0,8:0,9:0,10:0,11:0,12:0,13:0,14:0,15:0,16:0,17:0,18:0,19:0,20:0,21:0,22:0,23:0,24:0;99;4;https://github.com/gluoNNet/NineQuantumsMorris/blob/master/NNMM-cenk/main_da.py;>7
+370;d8f4622aadb86ed48a927146ebf0fa1407812e4f;"weights = {'W_conv1':tf.Variable(tf.random_normal([5,5,1,32])),
+               'W_conv2':tf.Variable(tf.random_normal([5,5,32,64])),
+               'W_fc':tf.Variable(tf.random_normal([7*7*64,1024])),
+               'out':tf.Variable(tf.random_normal([1024, n_classes]))}
+
+    biases = {'b_conv1':tf.Variable(tf.random_normal([32])),
+              'b_conv2':tf.Variable(tf.random_normal([64])),
+              'b_fc':tf.Variable(tf.random_normal([1024])),
+              'out':tf.Variable(tf.random_normal([n_classes]))}
+
+    #
+⋯
+conv1 = tf.nn.relu(conv2d(x, weights['W_conv1']) + biases['b_conv1'])
+    conv1 = maxpool2d(conv1)
+
+    conv2 = tf.nn.relu(conv2d(conv1, weights['W_conv2']) + biases['b_conv2'])
+    conv2 = maxpool2d(conv2)";237;12;https://github.com/brosand/JetStuff/blob/master/TensorFlow/test7.py;4
+371;dd0ad60f515961f60b9db7959953384839e98d6b;"embeddings = tf.Variable(
+                tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))
+            embed = tf.nn.embedding_lookup(embeddings, train_inputs)
+
+            # Construct the variables for the NCE loss
+            nce_weights = tf.Variable(
+                tf.truncated_normal([vocabulary_size, embedding_size],
+                                    stddev=1.0 / math.sqrt(embedding_size)))
+            nce_biases = tf.Variable(tf.zeros([vocabulary_size]))
+
+        # Compute the average NCE loss for the batch.
+        # tf.nce_loss automatically draws a new sample of the negative labels each
+        # time we evaluate the loss.
+        loss = tf.reduce_mean(
+            tf.nn.nce_loss(weights=nce_weights,
+                           biases=nce_biases,
+                           labels=train_labels,
+                           inputs=embed,
+                           num_sampled=num_sampled,
+                           num_classes=vocabulary_size))
+
+        # Construct the SGD optimizer using a learning rate of 1.0.
+        optimizer = tf.train.GradientDescentOptimizer(1.0).minimize(loss)
+
+        # Compute the cosine similarity between minibatch examples and all embeddings.
+        norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True))
+        normalized_embeddings";227;11;https://github.com/taki17/onlab/blob/master/graph_vis.py;4
+372;506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefb;"""A"", ""B"", ""C"", ""D"", ""E"", ""F"", ""G"", ""H"", ""I"", ""J"", ""K"", ""L"", ""M"", ""N"", ""O"", ""P"", ""Q"", ""R"", ""S"", ""T"", ""U"", ""V"", ""W"", ""X"", ""Y"", ""Z""";103;3;https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py;>7
+373;78fbbe00a6715e2471ad747cf604691c70940176;"make_pizza(size, *toppings):
+    """"""Summarize the pizza we are about to make.""""""
+    print(""\nMaking a "" + str(size) +
+          ""-inch pizza with the following toppings:"")
+    for topping in toppings:
+        print(""- "" + topping)";60;1;https://github.com/cintiamh/PythonCrashCourse/blob/master/src/pizza.py;6
+374;16be96e3c6cc6ac83349eee9632bb7f9765e99e8;"a = 1
+    b = 2
+    c = 3
+    d = 4
+    e = 5
+    f = 6
+    g = 7
+    h = 8
+    i = 9
+    j = 10
+    k = 11
+    l = 12
+    m = 13
+    n = 14
+    o = 15
+    p = 16
+    q = 17
+    r = 18
+    s = 19
+    t = 20
+    u = 21
+    v = 22
+    w = 23
+    x = 24
+    y = 25
+    z = 26";78;2;https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py;>7
+375;4d1c070ea37c961d457192dbe530edef1cf1c135;"with urlopen('http://sixty-north.com/c/t.txt') as story:
+        story_words = []
+        for line in story:
+            line_words = line.decode('utf-8').split()
+            for word in line_words:
+                story_words.append(word)";60;2;https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py;2
+376;4d1c070ea37c961d457192dbe530edef1cf1c135;"with urlopen('http://sixty-north.com/c/t.txt') as story:
+        story_words = []
+        for line in story:
+            line_words = line.decode('utf-8').split()
+            for word in line_words:
+                story_words.append(word)";60;2;https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py;2
+377;4d1c070ea37c961d457192dbe530edef1cf1c135;"with urlopen('http://sixty-north.com/c/t.txt') as story:
+        story_words = []
+        for line in story:
+            line_words = line.decode('utf-8').split()
+            for word in line_words:
+                story_words.append(word)";60;1;https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py;2
+378;4d1c070ea37c961d457192dbe530edef1cf1c135;"with urlopen('http://sixty-north.com/c/t.txt') as story:
+        story_words = []
+        for line in story:
+            line_words = line.decode('utf-8').split()
+            for word in line_words:
+                story_words.append(word)";60;1;https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py;2
+379;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+
+    For example::
+
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+
+        >>> orig = [""cookies"", ""love"", ""I""]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        ['I', 'love', 'cookies']
+    """"""";140;7;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+380;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+
+    For example::
+
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+
+        >>> orig = [""cookies"", ""love"", ""I""]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        ['I', 'love', 'cookies']
+    """"""";140;7;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+381;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [";101;5;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+382;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [";101;4;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+383;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [";101;5;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+384;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [""cookies"", ""love"", ""I""]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        ['I', 'love', 'cookies']
+    """"""";140;7;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+385;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+
+    For example::
+
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+
+        >>> orig = [""cookies"", ""love"", ""I""]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        ['I', 'love', 'cookies']
+    """"""";140;7;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+386;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [";101;4;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+387;6633a1db9eab30dff587a42b588fddc460dc1177;"Reverse the input list given, but do it ""in place"" --- that is,
+    do not create a new list and return it, but modify the original
+    list.
+    
+    **Do not use** the python function `reversed()` or the method
+    `list.reverse()`.
+    
+    For example::
+    
+        >>> orig = [1, 2, 3]
+        >>> reverse_list_in_place(orig)
+        >>> orig
+        [3, 2, 1]
+        >>> orig = [";101;5;https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py;2
+388;c6011f18f52e7f644a0ca14a635db4575db30ac8;")
+
+@bot.command()
+async def add(ctx, a: int, b: int):
+    await ctx.send(a+b)
+
+@bot.command()
+async def multiply(ctx, a: int, b: int):
+    await ctx.send(a*b)
+
+@bot.command()
+async def greet(ctx):
+    await ctx.send("":smiley: :wave: Hello, there!"")
+
+@bot.command()
+async def cat(ctx):
+    await ctx.send(""https://media.giphy.com/media/JIX9t2j0ZTN9S/giphy.gif"")
+
+@bot.command()
+async def info(ctx):
+    embed = discord.Embed(title=""nice bot"", description=""Nicest bot there is ever."", color=0xeee657)
+
+    # give info about you here
+    embed.add_field(name=""Author"", value=""<YOUR-USERNAME>"")
+
+    # Shows the number of servers the bot is member of.
+    embed.add_field(name=""Server count"", value=f""{len(bot.guilds)}"")
+
+    # give users a link to invite thsi bot to their server
+    embed.add_field(name=""Invite"", value=""[Invite link](<insert your OAuth invitation link here>)"")
+
+    await ctx.send(embed=embed)
+
+bot.";286;22;https://github.com/Alysius/Nanachi/blob/master/bot.py;0
+389;c6011f18f52e7f644a0ca14a635db4575db30ac8;")
+
+@bot.command()
+async def add(ctx, a: int, b: int):
+    await ctx.send(a + b)
+
+@bot.command()
+async def multiply(ctx, a: int, b: int):
+    await ctx.send(a * b)
+
+@bot.command()
+async def greet(ctx):
+    await ctx.send("":smiley: :wave: Hello, there!"")
+
+@bot.command()
+async def cat(ctx):
+    await ctx.send(""https://media.giphy.com/media/JIX9t2j0ZTN9S/giphy.gif"")
+
+@bot.command()
+async def info(ctx):
+    embed = discord.Embed(title=""nice bot"", description=""Nicest bot there is ever."", color=0xeee657)
+
+    # give info about you here
+    embed.add_field(name=""Author"", value=""<YOUR-USERNAME>"")
+
+    # Shows the number of servers the bot is member of.
+    embed.add_field(name=""Server count"", value=f""{len(bot.guilds)}"")
+
+    # give users a link to invite thsi bot to their server
+    embed.add_field(name=""Invite"", value=""[Invite link](<insert your OAuth invitation link";270;20;https://github.com/Alysius/Nanachi/blob/master/bot.py;0
+390;1b88840bbb595e30cb7664fdd72be9e2119e898a;"import discord
+import asyncio
+
+client = discord.Client()
+
+@client.event
+async def on_ready():
+    print('Logged in as')
+    print(client.user.name)
+    print(client.user.id)
+    print('------')
+
+@client.event
+async def on_message(message):
+    if message.content.startswith('!test'):
+        counter = 0
+        tmp = await client.send_message(message.channel, 'Calculating messages...')
+        async for log in client.logs_from(message.channel, limit=100):
+            if log.author == message.author:
+                counter += 1
+
+        await client.edit_message(tmp, 'You have {} messages.'.format(counter))
+    elif message.content.startswith('!sleep'):
+        await asyncio.sleep(5)
+        await client.send_message(message.channel, 'Done sleeping')
+
+client.run('";188;11;https://github.com/tylergibbs2/async2rewrite/blob/master/sample_code.py;0
+391;d993499b1a03faa99c8404845bb88c8bebe39206;"import candlestick_ohlc
+    import matplotlib
+    import pylab
+    matplotlib.rcParams.update({'font.size': 9})
+
+    def rsiFunc(prices, n=14):
+        deltas = np.diff(prices)
+        seed = deltas[:n + 1]
+        up = seed[seed >= 0].sum() / n
+        down = -seed[seed < 0].sum() / n
+        rs = up / down
+        rsi = np.zeros_like(prices)
+        rsi[:n] = 100. - 100. / (1. + rs)
+
+        for i in range(n, len(prices)):
+            delta = deltas[i - 1]  # cause the diff is 1 shorter
+
+            if delta > 0:
+                upval = delta
+                downval = 0.
+            else:
+                upval = 0.
+                downval = -delta
+
+            up = (up * (n - 1) + upval) / n
+            down = (down * (n - 1) + downval) / n
+
+            rs = up / down
+            rsi[i] = 100. - 100. / (1. + rs)
+
+        return rsi
+
+    def movingaverage(values, window):
+        weigths = np.repeat(1.0, window) / window
+        smas = np.convolve(values, weigths, 'valid')
+        return smas  # as a numpy array
+
+    def ExpMovingAverage(values, window):
+        weights = np.exp(np.linspace(-1., 0., window))
+        weights /= weights.sum()
+        a = np.convolve(values, weights, mode='full')[:len(values)]
+        a[:window] = a[window]
+        return a
+
+    def computeMACD(x, slow=26, fast=12):
+        """"""
+        compute the MACD (";349;19;https://github.com/ThalesM/Bot-acoes-analise/blob/master/Main.py;>7
+392;971a5155a320a23115a41d16f14b6ccc6ffe9801;6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54;97;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+393;2b1e7fac0b18d53b38f6131236d347a9c0ed588a;":
+        return list
+    else:
+        pivot = list[0]
+        less = [i for i in list[1:] if i <= pivot]
+        greater = [i for i in list[1:] if i > pivot]
+        return quick_sort(less) + [pivot] + quick_sort(greater)";60;2;https://github.com/jouni-kantola/algo-practice/blob/master/quick-sort/quick_sort.py;2
+394;ec31a82cecfdc9b1ef85e66d2da5f2b729af0b5e;""""""" Memoization decorator for functions taking one or more arguments. """"""
+    class memodict(dict):
+        def __init__(self, f):
+            self.f = f
+        def __call__(self, *args):
+            return self[args]
+        def __missing__(self, key):
+            ret = self[key] = self.f(*key)
+            return ret
+    return memodict(f)";78;2;https://github.com/e2crawfo/spectral_dagger/blob/master/spectral_dagger/datasets/uni_dep.py;>7
+395;25e00ef311572329f7e2180566c310c2f303f4fa;'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's',;76;2;https://github.com/austinguo550/Hangman-AI/blob/master/challenge.py;>7
+396;6d16bdd5c9dc10eb858815d3dc8825e241c38878;], 2: [], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: [];116;5;https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py;1
+397;6d16bdd5c9dc10eb858815d3dc8825e241c38878;[], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: [];112;5;https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py;1
+398;6d16bdd5c9dc10eb858815d3dc8825e241c38878;[], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: [];112;5;https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py;1
+399;d78808b7a10918d43a105d591d6bc3e2a89ec1c1;data3, data4, data5, data6, data7, data8, data9, data10, data11, data12, data13, data14, data15, data16, data17, data18, data19, data20, data21, data22, data23, data24, data25, data26, data27, data28, data29, data30, data31, data32, data33, data34, data35,;66;2;https://github.com/yfchenaa/k-means-and-assets-allocation-/blob/master/k-means.py;4
+400;1ec27f7a818531166771c359e15f8c3dfd401b32;, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180;62;2;https://github.com/jpherrenknecht/serveur_vr/blob/master/test_numba.py;2
+401;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+    table = soup.find('table', {'class': 'wikitable sortable'})                   
+    tickers = []                   
+    for row in table.findAll('tr')[1:]:                      
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+402;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+403;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+404;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')                
+        table = soup.find('table', {'class': 'wikitable sortable'})                
+        tickers = []                
+        for row in table.";64;1;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+405;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table";63;1;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+406;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;")       
+    table = soup.find('table', {'class':'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text       
+        tickers.append(ticker)";63;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;>7
+407;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class' : 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[";86;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+408;f56204645d2ade470e7792f2d675c5e6e0bd1ba4;".BeautifulSoup(resp.text, ""lxml"")       
+    table = soup.find('table', {'class' : 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";67;1;https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py;>7
+409;f56204645d2ade470e7792f2d675c5e6e0bd1ba4;".BeautifulSoup(resp.text, ""lxml"")       
+        table = soup.find('table', {'class' : 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";67;1;https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py;>7
+410;75512293896435423873fc22605f93fe01577389;"')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class' : 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text       
+            tickers.append(ticker)       
+        tickers";79;3;https://github.com/kmjacinto2145/financial-markets-simulator/blob/master/Live Financial Markets Simulator.py;>7
+411;f56204645d2ade470e7792f2d675c5e6e0bd1ba4;".BeautifulSoup(resp.text, ""lxml"")       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";67;1;https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py;>7
+412;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";94;4;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+413;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[";90;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+414;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;")                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text
+            tickers.append(ticker)";63;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;>7
+415;262b4b05988a075ae4b8da20105f8b4cb33305f8;")                   
+    table = soup.find('table', {'class': 'wikitable sortable'})                   
+    tickers = []                   
+    for row in table.findAll('tr')[1:]:                   
+        ticker = row.findAll('td')[0].text.replace('.','-')                   
+        tickers.append(ticker)";74;2;https://github.com/VitzzViperzz/Python-Finance-Machine-Learning-projects/blob/master/extras/google_sp500.py;>7
+416;85b97fc328ba43f86b94d61c8dde310200bc08d7;"://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+        soup = bs4.BeautifulSoup(response.text, 'lxml')                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text";86;2;https://github.com/crauer/econometrics/blob/master/pair_trading.py;>7
+417;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;")                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text
+            tickers.append(ticker)";63;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;>7
+418;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+419;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+420;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:                   
+            ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+421;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')   
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')   
+        table = soup.find('table', {'class': 'wikitable sortable'})   
+        tickers = []   
+        for row in table.findAll('tr')[1:]:   
+            ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+422;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+423;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;")                   
+        table = soup.find('table', {'class': 'wikitable sortable'})                   
+        tickers = []                   
+        for row in table.findAll('tr')[1:]:
+            ticker = row.findAll('td')[0].text
+            tickers.append(ticker)";63;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;>7
+424;a2aac312e637010e12581e09e7287eaf25f81da0;= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', ';67;3;https://github.com/Abhinawk9/test/blob/master/yahooFinance.py;>7
+425;f56204645d2ade470e7792f2d675c5e6e0bd1ba4;".BeautifulSoup(resp.text, ""lxml"")                   
+    table = soup.find('table', {'class': 'wikitable sortable'})                   
+    tickers = []                           
+    for row in table.findAll('tr')[1:]:                   
+        ticker = row.findAll('td')[0].text";67;1;https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py;>7
+426;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+        soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+        table = soup.find('table', {'class': 'wikitable sortable'})       
+        tickers = []       
+        for row in table.findAll('tr')[1:]:       
+            ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+427;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')               
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+    table = soup.find('table', {'class': 'wikitable sortable'})                   
+    tickers = []                   
+    for row in table.findAll('tr')[1:]:                   
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+428;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+       soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+       table = soup.find('table', {'class': 'wikitable sortable'})       
+       tickers = []       
+       for row in table.findAll('tr')[1:]:       
+           ticker = row.findAll('td')[";90;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+429;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+430;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')                   
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')                   
+    table = soup.find('table', {'class': 'wikitable sortable'})                   
+    tickers = []                   
+    for row in table.findAll('tr')[1:]:";79;2;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+431;a7920bc3bdf001ee9e1a9a5c9147b2069782695b;"')       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text       
+        tickers.append(ticker)";64;2;https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py;>7
+432;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";94;4;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+433;f56204645d2ade470e7792f2d675c5e6e0bd1ba4;".BeautifulSoup(resp.text, ""lxml"")       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";67;1;https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py;>7
+434;6bcafa51129e5a18509ab485a4623450ff916b71;"get('https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')       
+    soup = bs4.BeautifulSoup(resp.text, 'lxml')       
+    table = soup.find('table', {'class': 'wikitable sortable'})       
+    tickers = []       
+    for row in table.findAll('tr')[1:]:       
+        ticker = row.findAll('td')[0].text";90;2;https://github.com/juliennassar/stock-analyser/blob/master/server/server.py;>7
+435;510ff56d9ab9b435d1db704b6fe07e95c8afeff6;"""1"", ""2"", ""3"", ""4"", ""5"", ""6"", ""7"", ""8"", ""9"", ""10"", ""11"", ""12"", ""13"", ""14"", ""15"", ""16"", ""17"", ""18"", ""19"", ""20"", ""21"", ""22"", ""23"", ""24""";95;5;https://github.com/shym98/MovieSearch/blob/master/untitled/ChartDirector/pythondemo_cgi/deptharea.py;3
+436;36b2b3e7de8a199d45f713e0cf03cc313f669d21;""", ""g"", ""gs"", ""mp"", ""fg"", ""fga"", ""fg_pct"", ""fg3"", ""fg3a"", ""fg3_pct"", ""fg2"", ""fg2a"", ""fg2_pct"", ""efg_pct"", ""ft"", ""fta"", ""ft_pct"", ""orb"", ""drb"", ""trb"", ""ast";80;3;https://github.com/BrianSchwaz/cashketball/blob/master/finished spider/playerSpider.py;2
+437;88af220957d11212580f0a1eeda46e108ee85b5b;""", ""min"", ""pts"", ""fgm"", ""fga"", ""fg%"", ""3pm"", ""3pa"", ""3p%"", ""ftm"", ""fta"", ""ft%"", ""oreb"", ""dreb"", ""reb"", """;62;1;https://github.com/aniehuser/senior-design-group10/blob/master/demos/example-workflows/scrape_nba.py;2
+438;6ea36698d0c7def644901c69eaaab4937bda9faa;"""G"", ""AB"", ""R"", ""H"", ""2B"", ""3B"", ""HR"", ""RBI"", ""SB"", ""CS"", ""BB"", ""SO"", ""IBB"", ""HBP"", ""SH"", ""SF""";63;2;https://github.com/putsy-caballero/VintageDraft/blob/master/entities/Batter.py;3
+439;36b2b3e7de8a199d45f713e0cf03cc313f669d21;""", ""g"", ""gs"", ""mp"", ""fg"", ""fga"", ""fg_pct"", ""fg3"", ""fg3a"", ""fg3_pct"", ""fg2"", ""fg2a"", ""fg2_pct"", ""efg_pct"", ""ft"", ""fta"", ""ft_pct"", ""orb"", """;71;3;https://github.com/BrianSchwaz/cashketball/blob/master/finished spider/playerSpider.py;3
+440;ed48df6d28b9e3bba82066c250427d78ac5516fc;https://query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22{0}%2C%20{1}%22)&format=json&env=store%3A%2F%2Fdatatables.org%2Falltableswithkeys;88;3;https://github.com/ramrom/haus/blob/master/weather.py;4
+441;944d16400891095f5cba285cc06c64e4aca4a676;"= ""https://query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22"" + city + ""%2C%20"" + state + ""%22)&format=json&env=store%3A%2F%2Fdatatables.org%2Falltableswithkeys""";95;5;https://github.com/aadiuppal/programming/blob/master/data_sc/w.py;4
+442;ed48df6d28b9e3bba82066c250427d78ac5516fc;https://query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22{0}%2C%20{1}%22)&format=json&env=store%3A%2F%2Fdatatables.org%2Falltableswithkeys;88;3;https://github.com/ramrom/haus/blob/master/weather.py;4
+443;944d16400891095f5cba285cc06c64e4aca4a676;"url = ""https://query.yahooapis.com/v1/public/yql?q=select%20*%20from%20weather.forecast%20where%20woeid%20in%20(select%20woeid%20from%20geo.places(1)%20where%20text%3D%22"" + city + ""%2C%20"" + state + ""%22)";77;4;https://github.com/aadiuppal/programming/blob/master/data_sc/w.py;4
+444;43d366138776e9e413c71aa18513ae7c3ea30960;row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22];109;6;https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py;>7
+445;43d366138776e9e413c71aa18513ae7c3ea30960;row[0], row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22];114;6;https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py;>7
+446;c0d8455767ea9e44863ddcfa670ba6a541f5f628;row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13];64;3;https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py;>7
+447;9d4a0ad370818b6caf045c1cc50da0dc6f13c133;row[25], row[26], row[27], row[28], row[29], row[30], row[31], row[32], row[33], row[34], row[35], row[36], row[37], row[38],;70;2;https://github.com/NCTUMUILab/Intelligent_noti/blob/master/script/qualtrics_to_db.py;>7
+448;c2d33909e4cd68f7d83081ccb5bf4608e566607e;row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22], row[23], row[24], row[25], row[;107;5;https://github.com/Change72/gc-python-graduate/blob/master/FeatureCate669/9_1_beforeLearn.py;>7
+449;7a3a71d08098f3d90ecf0152b697ae8f76b89cd5;row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22], row[23], row[24], row[25], row[26], row[27], row[28], row[29], row[30], row[31], row[32], row[33], row[34], row[35], row[36], row[37], row[38], row[39], row[40], row[41], row[42], row[43;193;10;https://github.com/ayman-elgharabawy/DataBaseMigrationScript/blob/master/migrator.py;>7
+450;c0d8455767ea9e44863ddcfa670ba6a541f5f628;, row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15];75;3;https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py;>7
+451;43d366138776e9e413c71aa18513ae7c3ea30960;, row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22];110;6;https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py;>7
+452;43d366138776e9e413c71aa18513ae7c3ea30960;row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15], row[16], row[17], row[18], row[19], row[20], row[21], row[22];109;6;https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py;>7
+453;c0d8455767ea9e44863ddcfa670ba6a541f5f628;row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10], row[11], row[12], row[13], row[14], row[15];74;3;https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py;>7
+454;a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772;= {'a': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'b': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'c': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'd': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'e;108;3;https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py;>7
+455;a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772;= {'a': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'b': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'c': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'd': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];105;3;https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py;>7
+456;a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772;= {'a': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'b': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'c': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'd': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'e;108;3;https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py;>7
+457;971a5155a320a23115a41d16f14b6ccc6ffe9801;1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,;94;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;>7
+458;c8ab7efa564508803170b0877019427c7586b1a6;"window = turtle.Screen()
+    window.bgcolor(""red"")
+    brad = turtle.Turtle()
+    brad.shape(""turtle"")
+    brad.color(""yellow"")
+    brad.speed(2)
+    for i in range(1,37):
+        draw_square(brad)
+        brad.right(10)
+    window.exitonclick()";69;2;https://github.com/JuanBalceda/python-basics/blob/master/udacity/mindstorm.py;1
+459;971a5155a320a23115a41d16f14b6ccc6ffe9801;6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54;97;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;0
+460;4777897fd744ca5e37f4a05b86f01fa66369570f;"rects1 = plt.bar(index, means_men, bar_width,
+                     alpha=opacity,
+                     color='b',
+                     label='Men')
+
+    rects2 = plt.bar(index + bar_width, means_women, bar_width,
+                     alpha=opacity,
+                     color='r',
+                     label='Women')
+
+    plt.xlabel('Group')
+    plt.ylabel('Scores')
+    plt.title('Scores by group and gender')
+    plt.xticks(index + bar_width, ('A', 'B', 'C', 'D', 'E'))
+    plt.legend()
+
+    plt.tight_layout()
+    plt.show()";131;5;https://github.com/AparnaThricovil/data-mining/blob/master/PlotGraph.py;0
+461;662476e59a96a119b89f796faf116e2d1543f13c;, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191,;79;2;https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py;>7
+462;47081907e60f9f9cab0effee35db245a5b7003a6;"(arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) // 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";79;3;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+463;47081907e60f9f9cab0effee35db245a5b7003a6;"pivot = arr[len(arr) // 2]
+        left = [x for x in arr if x < pivot]
+        middle = [x for x in arr if x == pivot]
+        right = [x for x in arr if x > pivot]
+        return quicksort(left) + middle + quicksort(right)";64;2;https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py;2
+464;4118a938ea514437331aa7c8b9a9e0e1a398d8d7;"(arr):
+    if len(arr) <= 1:
+        return arr
+    pivot = arr[len(arr) / 2]
+    left = [x for x in arr if x < pivot]
+    middle = [x for x in arr if x == pivot]
+    right = [x for x in arr if x > pivot]
+    return quicksort(left) + middle + quicksort(right)";78;6;https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py;2
+465;ecad8f91a2f37bcb755ab0b26c91f38e68ac37ae;"plt.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=plt.cm.Paired)
+    plt.xlabel('Sepal length')
+    plt.ylabel('Sepal width')
+    plt.xlim(xx.min(), xx.max())
+    plt.";66;1;https://github.com/ieCecchetti/Python_ML_DL_examples/blob/master/SVM/script/SVM_rbf.py;0
+466;a83652129522d52f93b92cc1943979f6ca1a6ba1;, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V, W, X, Y;100;5;https://github.com/Coder670/random_password_generator/blob/master/random_password_generator.py;0
+467;971a5155a320a23115a41d16f14b6ccc6ffe9801;3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,;100;3;https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py;0
+468;4efe348486874eee36c0eaf2cac672ce8b5ade0b;"two Turtle Doves, "", ""three French Hens, "", ""four Calling Birds, "", ""five Gold Rings, "", ""six Geese-a-Laying, "", ""seven Swans-a-Swimming, "", ""eight Maids-a-Milking, "", ""nine Ladies Dancing, "", ""ten Lords-a-Leaping, "", ""eleven Pipers Piping, "", ""twelve Drummers Drumming, ""]";88;2;https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py;1
+469;4efe348486874eee36c0eaf2cac672ce8b5ade0b;"two Turtle Doves,"", ""three French Hens,"", ""four Calling Birds,"", ""five Gold Rings,"", ""six Geese-a-Laying,"", ""seven Swans-a-Swimming,"", ""eight Maids-a-Milking,"", ""nine Ladies Dancing,"", ""ten Lords-a-Leaping,"", ""eleven Pipers Piping,"", ""twelve Drummers Drumming,""]";88;2;https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py;1
+470;4efe348486874eee36c0eaf2cac672ce8b5ade0b;""", ""three French Hens, "", ""four Calling Birds, "", ""five Gold Rings, "", ""six Geese-a-Laying, "", ""seven Swans-a-Swimming, "", ""eight Maids-a-Milking, "", ""nine Ladies Dancing, "", ""ten Lords-a-Leaping, "", ""eleven Pipers Piping, "", ""twelve Drummers Drumming, ""]";84;2;https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py;1
+471;2b3691d99ac7193d3d9a1be63f7c49065bd5c35b;"2013  Red Hat, Inc.
+#
+# This copyrighted material is made available to anyone wishing to use,
+# modify, copy, or redistribute it subject to the terms and conditions of
+# the GNU General Public License v.2, or (at your option) any later version.
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY expressed";75;4;https://github.com/bcl/anaconda/blob/master/pyanaconda/ui/gui/spokes/software.py;0
+472;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
+473;f18b0ee37075e4e0d5c31dbe7255ecca66830b10;"resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')
+    soup = bs4.BeautifulSoup(resp.text,'lxml')
+    table = soup.find('table',{'class':'wikitable sortable'})
+    tickers = []
+    for row in table.findAll('tr')[1:]:
+        ticker = row.findAll('td')[0].text";94;3;https://github.com/hfk97/edgar_scraping/blob/master/menu.py;>7
\ No newline at end of file
diff --git a/assets/images/help/copilot/plot_buckets.png b/assets/images/help/copilot/plot_buckets.png
new file mode 100644
index 0000000000..6fa1029db3
Binary files /dev/null and b/assets/images/help/copilot/plot_buckets.png differ
diff --git a/assets/images/help/copilot/plot_context.png b/assets/images/help/copilot/plot_context.png
new file mode 100644
index 0000000000..afc05e29af
Binary files /dev/null and b/assets/images/help/copilot/plot_context.png differ
diff --git a/assets/images/help/copilot/plot_copies.png b/assets/images/help/copilot/plot_copies.png
new file mode 100644
index 0000000000..0fc28d4727
Binary files /dev/null and b/assets/images/help/copilot/plot_copies.png differ
diff --git a/assets/images/help/copilot/resources_recitation_example_zen.gif b/assets/images/help/copilot/resources_recitation_example_zen.gif
new file mode 100644
index 0000000000..e823b98914
Binary files /dev/null and b/assets/images/help/copilot/resources_recitation_example_zen.gif differ
diff --git a/assets/images/help/copilot/resources_recitation_example_zen_caw.gif b/assets/images/help/copilot/resources_recitation_example_zen_caw.gif
new file mode 100644
index 0000000000..69250c61db
Binary files /dev/null and b/assets/images/help/copilot/resources_recitation_example_zen_caw.gif differ
diff --git a/content/actions/reference/events-that-trigger-workflows.md b/content/actions/reference/events-that-trigger-workflows.md
index 506794aad4..88a343d641 100644
--- a/content/actions/reference/events-that-trigger-workflows.md
+++ b/content/actions/reference/events-that-trigger-workflows.md
@@ -284,6 +284,48 @@ on:
 
 {% endnote %}
 
+{% ifversion fpt %}
+### `discussion`
+
+Runs your workflow anytime the `discussion` event occurs. {% data reusables.developer-site.multiple_activity_types %} For information about the GraphQL API, see "[Discussions](/graphql/guides/using-the-graphql-api-for-discussions)."
+
+{% data reusables.github-actions.branch-requirement %}
+
+| Webhook event payload | Activity types | `GITHUB_SHA` | `GITHUB_REF` |
+| --------------------- | -------------- | ------------ | -------------|
+| [`discussion`](/webhooks/event-payloads/#discussion) | - `opened`<br/>- `edited`<br/>- `deleted`<br/>- `transferred`<br/>- `pinned`<br/>- `unpinned`<br/>- `labeled`<br/>- `unlabeled`<br/>- `locked`<br/>- `unlocked`<br/>- `category_changed`<br/> - `answered`<br/> - `unanswered` | Last commit on default branch | Default branch |
+
+{% data reusables.developer-site.limit_workflow_to_activity_types %}
+
+For example, you can run a workflow when a discussion has been `opened`, `edited`, or `answered`.
+
+```yaml
+on:
+  discussion:
+    types: [opened, edited, answered]
+```
+
+### `discussion_comment`
+
+Runs your workflow anytime the `discussion_comment` event occurs. {% data reusables.developer-site.multiple_activity_types %} For information about the GraphQL API, see "[Discussions](/graphql/guides/using-the-graphql-api-for-discussions)."
+
+{% data reusables.github-actions.branch-requirement %}
+
+| Webhook event payload | Activity types | `GITHUB_SHA` | `GITHUB_REF` |
+| --------------------- | -------------- | ------------ | -------------|
+| [`discussion_comment`](/developers/webhooks-and-events/webhook-events-and-payloads#discussion_comment) | - `created`<br/>- `edited`<br/>- `deleted`<br/> | Last commit on default branch | Default branch |
+
+{% data reusables.developer-site.limit_workflow_to_activity_types %}
+
+For example, you can run a workflow when an issue comment has been `created` or `deleted`.
+
+```yaml
+on:
+  discussion_comment:
+    types: [created, deleted]
+```
+{% endif %}
+
 ### `fork`
 
 Runs your workflow anytime when someone forks a repository, which triggers the `fork` event. For information about the REST API, see "[Create a fork](/rest/reference/repos#create-a-fork)."
diff --git a/content/github/copilot/about-github-copilot-telemetry.md b/content/github/copilot/about-github-copilot-telemetry.md
new file mode 100644
index 0000000000..989263e8e0
--- /dev/null
+++ b/content/github/copilot/about-github-copilot-telemetry.md
@@ -0,0 +1,43 @@
+---
+title: About GitHub Copilot telemetry
+intro: '{% data variables.product.prodname_dotcom %} Copilot collects and relies on additional telemetry data beyond what other {% data variables.product.prodname_dotcom %} products and services collect.'
+redirect_from:
+  - /early-access/github/copilot/about-github-copilot-telemetry
+versions:
+  fpt: '*'
+---
+
+## What data is collected
+The {% data variables.product.prodname_dotcom %} Copilot collects activity from the user’s Visual Studio Code editor, tied to a timestamp, and metadata. This metadata consists of the extension settings and the standard metadata collected by the [Visual Studio Code extension telemetry package](https://www.npmjs.com/package/vscode-extension-telemetry):
+
+* Visual Studio Code machine ID (pseudonymized identifier)
+* Visual Studio Code session ID (pseudonymized identifier)
+* Visual Studio Code version
+* [Geolocation from IP address](https://docs.microsoft.com/en-us/azure/azure-monitor/app/ip-collection?tabs=net) (country, state/province and city, but not the IP address itself)
+* Operating system and version
+* Extension version
+* The VS Code UI (web or desktop)
+
+The activity collected consists of events that are triggered when:
+
+* An error occurs (it records the error kind and relevant background; e.g. if it’s an authentication error the key expiry date is recorded)
+* Our models are accessed to ask for code suggestions (it records editor state like position of cursor and snippets of code)—this includes cases when the user takes an action to request code suggestions
+* Code suggestions are received or displayed (it records the suggestions, post-processing, and metadata like model certainty and latency)
+* Code suggestions are redacted due to filters that ensure AI safety
+* The user acts on code suggestions (e.g. to accept or reject them)
+* The user has acted on code suggestions and then it records whether or how they persisted in the code
+
+## How the data is used
+This data will only be used by {% data variables.product.company_short %} for:
+
+* Directly improving the product, including assessing different strategies in processing and predicting which suggestions users may find helpful
+* Directly evaluating the product, e.g. by measuring the positive impact it has on the user
+* Improving the underlying code generation models, e.g. by providing positive and negative examples (but always so that your private code is not used as input to suggest code for other users of {% data variables.product.prodname_dotcom %} Copilot)
+* Guiding closely related {% data variables.product.prodname_dotcom %} products
+* Investigating and detecting potential abuse of the {% data variables.product.prodname_dotcom %} Copilot service
+* Other purposes related to improving the {% data variables.product.prodname_dotcom %} Copilot service
+
+## How the data is shared
+The telemetry data is stored securely on {% data variables.product.prodname_dotcom %} systems, with appropriate encryption in place.
+
+We know user edit actions and source code snippets are very sensitive data, and access is strictly controlled. The data can only be accessed by (1) named {% data variables.product.company_short %} personnel (employees and contractors) working on the {% data variables.product.company_short %} Copilot team or on the {% data variables.product.company_short %} platform health team, (2) select Microsoft personnel (employees and contractors) working on or with the {% data variables.product.company_short %} Copilot team, and (3) select employees of OpenAI who work on {% data variables.product.company_short %} Copilot.
diff --git a/content/github/copilot/index.md b/content/github/copilot/index.md
new file mode 100644
index 0000000000..b13f698350
--- /dev/null
+++ b/content/github/copilot/index.md
@@ -0,0 +1,10 @@
+---
+title: GitHub Copilot
+intro: 'You can use {% data variables.product.prodname_dotcom %} Copilot to assist with your programming in Visual Studio Code.'
+versions:
+  fpt: '*'
+children:
+  - /about-github-copilot-telemetry
+  - /telemetry-terms
+  - /research-recitation
+---
diff --git a/content/github/copilot/research-recitation.md b/content/github/copilot/research-recitation.md
new file mode 100644
index 0000000000..86642b0b9f
--- /dev/null
+++ b/content/github/copilot/research-recitation.md
@@ -0,0 +1,141 @@
+---
+title: Research recitation
+intro: 'A first look at rote learning in {% data variables.product.prodname_dotcom %} Copilot suggestions.'
+redirect_from:
+  - /early-access/github/copilot/research-recitation
+versions:
+  fpt: '*'
+---
+
+By: Albert Ziegler (@wunderalbert)
+
+## {% data variables.product.prodname_dotcom %} Copilot: Parrot or Crow?
+A first look at rote learning in {% data variables.product.prodname_dotcom %} Copilot suggestions.
+
+## Introduction
+
+{% data variables.product.prodname_dotcom %} Copilot helps you write code leveraging the collective intelligence of software developers worldwide. Copilot has already read through lots of public code, then it considers your own code, tries to guess what you want to do and comes up with a suggestion for how to get you there. That suggestion is based on your code. But indirectly, it’s informed by the code of those who came before you.
+
+How direct is the relationship between the suggested code and the code that informed it? In a recent thought-provoking paper<sup id="anchor1">[1](#footnote1)</sup>, Bender, Gebru et al. coined the phrase “stochastic parrots” for artificial intelligence systems like the ones that power {% data variables.product.prodname_dotcom %} Copilot. Or as a fellow machine learning engineer at {% data variables.product.company_short %}<sup id="anchor2">[2](#footnote2)</sup> remarked during a water cooler chat: these systems can feel like ”a toddler with a photographic memory.”
+
+These are deliberate oversimplifications. Many {% data variables.product.prodname_dotcom %} Copilot suggestions feel pretty specifically tailored to the particular code base the user is working on. Often, it looks less like a parrot and more like a crow building novel tools out of small blocks<sup id="anchor3">[3](#footnote3)</sup>. But there’s no denying that {% data variables.product.prodname_dotcom %} Copilot has an impressive memory:
+
+![A movie demonstration of Copilot](/assets/images/help/copilot/resources_recitation_example_zen.gif)
+
+Here, I intentionally directed<sup id="anchor4">[4](#footnote4)</sup> {% data variables.product.prodname_dotcom %} Copilot to recite a well known text it obviously knows by heart. I, too, know a couple of texts by heart. For example, I still remember some poems I learnt in school. Yet no matter the topic, not once have I been tempted to derail a conversation by falling into iambic tetrameter and waxing about daffodils.
+
+So is that (or rather the coding equivalent of it) something {% data variables.product.prodname_dotcom %} Copilot is prone to doing? How many of its suggestions are unique, and how often does it just parrot some likely looking code it has seen during training?
+
+## The Experiment
+
+During {% data variables.product.prodname_dotcom %} Copilot’s early development, nearly 300 employees used it in their daily work as part of an internal trial. This trial provided a good dataset to test for recitation. I wanted to find out how often {% data variables.product.prodname_dotcom %} Copilot gave them a suggestion that was quoted from something it had seen before.
+
+I limited the investigation to Python suggestions with a cutoff on May 7, 2021 (the day we started extracting that data). That left 453,780 suggestions spread out over 396 “user weeks”, i.e. calendar weeks during which a user actively used {% data variables.product.prodname_dotcom %} Copilot on Python code.
+
+### Automatic Filtering
+
+453,780 suggestions are a lot, but many of them can be dismissed immediately. To get to the interesting cases, consider sequences of “words” that occur in the suggestion in the same order as in the code {% data variables.product.prodname_dotcom %} Copilot has been trained on. In this context, punctuation, brackets, or other special characters all count as “words”, while tabs, spaces or even line breaks are ignored completely. After all, a quote is still a quote, whether it’s indented by 1 tab or 8 spaces.
+
+For example, one of {% data variables.product.prodname_dotcom %} Copilot’s suggestions was the following regex for numbers separated by whitespace:
+
+```
+r'^\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+\s+\d+'
+```
+
+This would be exactly 100 “words” in the sense above, but it’s a particularly dense example: the average non-empty line of code has only 10 “words.” I’ve restricted this investigation to cases where the overlap with the code {% data variables.product.prodname_dotcom %} Copilot was trained on contains at least 60 such “words”. We have to set the cut somewhere, and I think it’s rather rare that shorter sequences would be of great interest. In fact, most of the interesting cases identified later are well clear of that threshold of 60.
+
+If the overlap extends to what the user has already written, that also counts for the length. After all, the user may have written that context with the help of {% data variables.product.prodname_dotcom %} Copilot as well!
+
+In the following example, the user has started writing a very common snippet. {% data variables.product.prodname_dotcom %} Copilot completes it. Even though the completion itself is rather short, together with the already existing code it clears the threshold and is retained. 
+
+![Example code](/assets/images/help/copilot/example_last_straw.png)
+
+This procedure is permissive enough to let many relatively “boring” examples through, like the two above. But it’s still effective at dialing in the human analysis to the interesting cases, sorting out over 99% of Copilot suggestions.
+
+### Manual Bucketing
+
+After filtering, there were 473 suggestions left. But they came in very different forms:
+
+1. Some were basically just repeats of another case that passed filtering. For example, sometimes {% data variables.product.prodname_dotcom %} Copilot makes a suggestion, the developer types a comment line, and {% data variables.product.prodname_dotcom %} Copilot offers a very similar suggestion again. I removed these cases from the analysis as duplicates.
+2. Some were long, repetitive sequences. Like the following example, where the repeated blocks of `‘<p>’` are of course found somewhere in the training set: <br>![Example repetitions](/assets/images/help/copilot/example_repetitions.png)<br> Such suggestions can be helpful (test cases, regexes) or not helpful (like this case, I suspect). But in any case, they do not fit the idea of rote learning I had in mind when I started this investigation.
+3. Some were standard inventories, like the natural numbers, or the prime numbers, or stock market tickers, or the Greek alphabet: <br>![Example of Greek alphabet](/assets/images/help/copilot/example_greek.png)
+4. Some were common, straightforward ways, perhaps even universal ways, of doing things with very few natural degrees of freedom. For example, the middle part of the following strikes me as very much the standard way of using the BeautifulSoup package to parse a wikipedia list. In fact, the best matching snippet found in {% data variables.product.prodname_dotcom %} Copilot's training data<sup id="anchor5">[5](#footnote5)</sup> uses such code to parse a different article and goes on to do different things with the results. <br>![Example of Beautiful Soup](/assets/images/help/copilot/example_beautiful_soup.png) <br>This doesn’t fit my idea of a quote either. It’s a bit like when someone says “I’m taking out the trash; I’ll be back soon” -- that’s a matter of fact statement, not a quote, even though that particular phrase has been uttered many times before.
+5. And then there are all other cases. Those with at least some specific overlap in either code or comments. These are what interests me most, and what I’m going to concentrate on from now on.
+
+This bucketing necessarily has some edge cases<sup id="anchor6">[6](#footnote6)</sup>, and your mileage may vary in how you think they should be classified. Maybe you even disagree with the whole set of buckets in the first place.
+
+That’s why we’ve open sourced that dataset<sup id="anchor7">[7](#footnote7)</sup>. So if you feel a bit differently about the bucketing, or if you’re interested in other aspects of GitHub Copilot parroting its training set, you’re very welcome to just ignore my next section and draw your own conclusions.
+
+## Results
+
+![Overview Plot](/assets/images/help/copilot/plot_buckets.png)
+
+For most of {% data variables.product.prodname_dotcom %} Copilot's suggestions, our automatic filter didn’t find any significant overlap with the code used for training. But it did bring 473 cases to our attention. Removing the first bucket (cases that look very similar to other cases) left me with 185 suggestions. Of these, 144 got sorted out in buckets 2 - 4. This left 41 cases in the last bucket, the “recitations”, in the meaning of the term I have in mind.
+
+That corresponds to **1 recitation event every 10 user weeks** (95% confidence interval: 7 - 13 weeks, using a Poisson test).
+
+Of course, this was measured on the {% data variables.product.prodname_dotcom %} and Microsoft developers who tried out {% data variables.product.prodname_dotcom %} Copilot. If your coding behaviour is very different from theirs, your results might differ. In particular, some of these developers are only working part time on Python projects —— I could not distinguish that and so counted everyone who writes some Python in a given week as a user.
+
+1 event in 10 weeks doesn’t sound like a lot, but it’s not 0 either. And I found three things that struck me.
+
+### {% data variables.product.prodname_dotcom %} Copilot quotes when it lacks specific context
+
+If I want to learn the lyrics to a song, I have to listen to it many times. {% data variables.product.prodname_dotcom %} Copilot is no different: to learn a snippet of code by heart, it must see that snippet a lot. Each file is only shown to {% data variables.product.prodname_dotcom %} Copilot once, so the snippet needs to exist in many different files in public code.
+
+Of the 41 main cases we singled out during manual labelling, none appear in less than 10 different files. Most (35 cases) appear over a hundred times. Once, {% data variables.product.prodname_dotcom %} Copilot suggested starting an empty file with something it had even seen more than a whopping 700,000 different times during training -- that was the GNU General Public License.
+
+The following plot shows the number of matched files of the results in bucket 5 (one red mark on the bottom for each result) versus buckets 2-4. I left out bucket 1, which is really just a mix of duplicates of bucket 2-4 cases and duplicates of bucket 5 cases. The inferred distribution is displayed as a red line; it peaks between 100 and 1000 matches.
+
+![Number of Matches Plot](/assets/images/help/copilot/plot_copies.png)
+
+### {% data variables.product.prodname_dotcom %} Copilot mostly quotes in generic contexts
+
+As time goes on, each file becomes unique. But {% data variables.product.prodname_dotcom %} Copilot doesn’t wait for that<sup id="anchor8">[8](#footnote8)</sup>: it will offer its solutions while your file is still extremely generic. And in the absence of anything specific to go on, it’s much more likely to quote from somewhere else than it would be otherwise.
+
+![Context Length Plot](/assets/images/help/copilot/plot_context.png)
+
+Of course, software developers spend most of their time deep inside the files, where the context is unique enough that {% data variables.product.prodname_dotcom %} Copilot will offer unique suggestions. In contrast, the suggestions at the beginning are rather hit-and-miss, since {% data variables.product.prodname_dotcom %} Copilot cannot know what the program will be. But sometimes, especially in toy projects or standalone scripts, a modest amount of context can be enough to hazard a reasonable guess of what the user wanted to do. And sometimes it's still generic enough so that {% data variables.product.prodname_dotcom %} Copilot thinks one of the solutions it knows by heart looks promising:
+
+![Example code](/assets/images/help/copilot/example_robot.png)
+
+This is pretty much directly taken from coursework for a robotics class uploaded in different variations<sup id="anchor9">[9](#footnote9)</sup>.
+
+### Detection is only as good as the tool that does the detecting
+
+In its current form, the filter will turn up a good number of uninteresting cases when applied broadly. But it still should not be too much noise. For the internal users in the experiment, it would have been a bit more than one find per week on average (albeit likely in bursts!). Of these, about 17% (95% confidence interval using a binomial test: 14%-21%) would be in the fifth bucket.
+
+And nothing is ever foolproof of course: so this too can be tricked. Some cases are rather hard to detect by the tool we’re building, but still have an obvious source. To return to the Zen of Python:
+
+![Zen Variation](/assets/images/help/copilot/resources_recitation_example_zen_caw.gif)
+
+## Conclusion and Next Steps
+
+This demonstration demonstrates that GitHub Copilot _can_ quote a body of code verbatim, but that it rarely does so, and when it does, it mostly quotes code everybody quotes, and mostly at the beginning of a file, as if to break the ice.
+
+But there’s still one big difference between GitHub Copilot reciting code and me reciting a poem: I _know_ when I’m quoting. I would also like to know when Copilot is echoing existing code rather than coming up with its own ideas. That way, I’m able to look up background information about that code, and to include credit where credit is due.
+
+The answer is obvious: sharing the prefiltering solution we used in this analysis to detect overlap with the training set. When a suggestion contains snippets copied from the training set, the UI should simply tell you where it’s quoted from. You can then either include proper attribution or decide against using that code altogether.
+
+This duplication search is not yet integrated into the technical preview, but we plan to do so. And we will both continue to work on decreasing rates of recitation, and on making its detection more precise.
+
+<br><br>
+
+### Footnotes
+
+<a name="footnote1">1</a>: [On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?](https://dl.acm.org/doi/10.1145/3442188.3445922) [^](#anchor1)
+
+<a name="footnote2">2</a>: [Tiferet Gazit](https://github.com/tiferet) [^](#anchor2)
+
+<a name="footnote3">3</a>: see von Bayern et al. about the creative wisdom of crows: [Compound tool construction by New Caledonian crows](https://www.nature.com/articles/s41598-018-33458-z) [^](#anchor3)
+
+<a name="footnote4">4</a>: see Carlini et al. about deliberately triggering the recall of training data: [Extracting Training Data from Large Language Models](https://arxiv.org/pdf/2012.07805.pdf) [^](#anchor4)
+
+<a name="footnote5">5</a>: jaeteekae: [DelayedTwitter](https://github.com/jaeteekae/DelayedTwitter/blob/0a0b03de74c03cfbf36877ffded0cb1312d59642/get_top_twitter_accounts.py#L21) [^](#anchor5)
+
+<a name="footnote6">6</a>: Probably not _too_ many though. I’ve asked some developers to help me label the cases, and everyone was prompted to flag up any uncertainty with their judgement. That happened in only 34 cases, i.e. less than 10%. [^](#anchor6)
+
+<a name="footnote7">7</a>: In the [public dataset](/assets/images/help/copilot/matched_snippets.csv), I list the part of Copilot's suggestion that was also found in the training set, how often it was found, and a link to an example where it occurs in public code. For privacy reasons, I don't include the not-matched part of the completion or the code context the user had typed (only an indication of its length). [^](#anchor7)
+
+<a name="footnote8">8</a>: In fact, since this experiment has been made, {% data variables.product.prodname_dotcom %} Copilot _has_ changed to require a minimum file content. So some of the suggestions flagged here would not have been shown by the current version. [^](#anchor8)
+
+<a name="footnote9">9</a>: For example jenevans33: [CS8803-1](https://github.com/jenevans33/CS8803-1/blob/eca1bbc27ca6f7355dbc806b2f95964b59381605/src/Final/ekfcode.py#L23) [^](#anchor9)
diff --git a/content/github/copilot/telemetry-terms.md b/content/github/copilot/telemetry-terms.md
new file mode 100644
index 0000000000..427f2daaa7
--- /dev/null
+++ b/content/github/copilot/telemetry-terms.md
@@ -0,0 +1,13 @@
+---
+title: Telemetry terms
+intro: 'Acceptance of the additional telemetry described below is a condition to joining the wait list for the technical preview of {% data variables.product.prodname_dotcom %} Copilot and using {% data variables.product.prodname_dotcom %} Copilot during the technical preview.'
+redirect_from:
+  - /early-access/github/copilot/telemetry-terms
+versions:
+  fpt: '*'
+---
+
+## Additional telemetry
+If you are admitted to the technical preview and use {% data variables.product.prodname_dotcom %} Copilot, the {% data variables.product.prodname_dotcom %} Copilot Visual Studio Code extension will collect usage information about events in Visual Studio Code that are tied to your user account on {% data variables.product.prodname_dotcom %}. These events include {% data variables.product.prodname_dotcom %} Copilot performance, features used, or suggestions accepted or dismissed. {% data variables.product.prodname_dotcom %} collects this information using [Azure Application Insights](https://docs.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview). This information may include your User Personal Information, as defined in the [GitHub Privacy Statement](/github/site-policy/github-privacy-statement).
+
+This usage information is used by {% data variables.product.prodname_dotcom %}, and shared with OpenAI, to develop and improve the {% data variables.product.prodname_dotcom %} Copilot Visual Studio Code extension and related {% data variables.product.prodname_dotcom %} products. OpenAI also uses this usage information to perform other services related to {% data variables.product.prodname_dotcom %} Copilot, such as abuse monitoring. Please note that the usage information may include snippets of code that you use, create, or generate while using {% data variables.product.prodname_dotcom %} Copilot. When you edit files with the {% data variables.product.prodname_dotcom %} Copilot plugin enabled, file content snippets and suggestion results will be shared with {% data variables.product.prodname_dotcom %} and OpenAI and used for diagnostic purposes and to improve suggestions. {% data variables.product.prodname_dotcom %} Copilot relies on file content, for context, both in the file you are editing and potentially other files in the same Visual Studio Code workspace. {% data variables.product.prodname_dotcom %} Copilot does not use your private code as input to suggest code for other users of {% data variables.product.prodname_dotcom %} Copilot. The code snippets are treated as confidential information and accessed on a need-to-know basis. You are prohibited from collecting telemetry data about other users of {% data variables.product.prodname_dotcom %} Copilot from the Visual Studio Code extension. For more details about {% data variables.product.prodname_dotcom %} Copilot telemetry, please see "[About GitHub Copilot telemetry](/github/copilot/about-github-copilot-telemetry)." If you are admitted to the technical preview, you may revoke your consent to the additional telemetry and personal data processing operations described in this paragraph by contacting {% data variables.product.company_short %} and requesting removal from the technical preview.
diff --git a/content/github/index.md b/content/github/index.md
index 084c155e26..013d8ca0fd 100644
--- a/content/github/index.md
+++ b/content/github/index.md
@@ -13,6 +13,7 @@ children:
   - /setting-up-and-managing-your-github-user-account
   - /setting-up-and-managing-your-github-profile
   - /authenticating-to-github
+  - /copilot
   - /managing-subscriptions-and-notifications-on-github
   - /setting-up-and-managing-your-enterprise
   - /writing-on-github
@@ -34,4 +35,3 @@ children:
   - /site-policy
   - /site-policy-deprecated
 ---
-