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docs/assets/images/help/copilot/matched_snippets.csv
Sarah Schneider 53ae31ae58 Unhide Copilot docs (#20198) 
* bring over copilot content and assets from docs-early-access

* Remove broken link and update footnotes

* Fix broken link

* Add data set to `docs-internal` and revert footntoes

* add redirects from old early access paths

Co-authored-by: Ethan P <56270045+ethanpalm@users.noreply.github.com>
2021-06-29 13:37:01 -04:00

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1example_idmatching_part_of_suggestionnumber_of_tokens_in_matching_part_of_suggestionnumber_of_matcheslink_to_example_matchnumber_of_lines_of_context
21efa667297f49ca5065e12e0a9743445e00ebd1c2x, 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, n712https://github.com/remifuhriman/numerical_computing/blob/master/Labs/RSA/solutions.py2
32c101dc6dd83eca9260fbfc0369979a7965240df4\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+\971https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py>7
43c101dc6dd83eca9260fbfc0369979a7965240df4\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+991https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py>7
54c101dc6dd83eca9260fbfc0369979a7965240df4\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+\1001https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py>7
657f55777d22c616ae337c2f440e38ddb311907824\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)\s+([0-9.]+)',981https://github.com/dvdylus/treeCl/blob/master/bin/fast_run_raxml.py>7
765d7d7b9e5d18d271ba8065b57b63c11aa62650e4) 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 =756https://github.com/strongio/cerbero/blob/master/examples/cifar10_example/cifar10_multitask.py4
875d7d7b9e5d18d271ba8065b57b63c11aa62650e4) 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 =756https://github.com/strongio/cerbero/blob/master/examples/cifar10_example/cifar10_multitask.py4
988fe8dc24f5255aaa660568e64cf3489b795ed621) 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)612https://github.com/DIS17JTH/displayPiProject/blob/master/data_from_internet.py>7
109f72768d35a1bfee78c27a8c920ca4a80b27f719bof 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.601https://github.com/kd-nguyen/guttag/blob/master/6.00.1x/w5-apply_to_each.py1
111013af40cbffd29607178688e4f935be6af655d203B/C/D/E/F/G/H/I/J/K/L/M/N/O/P/Q/R/S/T/U/V/W/X/Y/Z/0/1/2/3/4/5/6/7/8/9/702https://github.com/IronLanguages/ironpython3/blob/master/Tests/test_stdmodules.py1
12119ceada1552a2619b2ecd33e07321e0e5e45663b8, 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 = "25716https://github.com/nishantpoorswani/motion_detection/blob/master/motion_detector.py1
131210035a5ef46e05f698fced88ff6a520b1fda6943k, 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/743https://github.com/fmasanori/PPZ/blob/master/pi generator.py>7
141310035a5ef46e05f698fced88ff6a520b1fda6943k, 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/743https://github.com/fmasanori/PPZ/blob/master/pi generator.py>7
151410035a5ef46e05f698fced88ff6a520b1fda6943k, 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/743https://github.com/fmasanori/PPZ/blob/master/pi generator.py>7
161587d22e982aec01dbba1e64a84b0937cad199bda8q, r, t, k, m, x = 10*q, 10*(r-m*t), t, k, (10*(3*q+r))//t - 10*m, x501https://github.com/steven-cutting/maths/blob/master/maths/otherpie.py>7
171687d22e982aec01dbba1e64a84b0937cad199bda8q, r, t, k, m, x = q*k, (2*q+r)*x, t*x, k+1, (q*(7*k+2)+r*x)//(t*x), x+2601https://github.com/steven-cutting/maths/blob/master/maths/otherpie.py>7
1817a4c3d2c979c489e47c250f5fd3402328044f19fa""" 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 km1135https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py6
19182c50c483254cf60b00a276cd01eb5a5f4ae91bdcdlat = 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))793https://github.com/kyb3r/majorproject/blob/master/server/core/route_generation.py6
20198c76f07cfbfa90928d72dcf76029b44d8e9eb21c""" 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 * r1246https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py6
2120a4c3d2c979c489e47c250f5fd3402328044f19fa""" 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 km1135https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py6
22218c76f07cfbfa90928d72dcf76029b44d8e9eb21c""" 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 * r1246https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py6
2322f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
2423f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
2524f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
2625023ba10b2acf76024e495c08ef92741a5c95480bprint(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)601https://github.com/raoniteixeira/algoritmos_te/blob/master/unidade_4/2.py>7
272616be96e3c6cc6ac83349eee9632bb7f9765e99e8a = 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 = 26782https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py>7
282716be96e3c6cc6ac83349eee9632bb7f9765e99e8a = 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 = 26782https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py>7
29288ea4e63c0d203860c4f59de75d87344671a383ec/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%722https://github.com/sirinenisaikiran/Python/blob/master/Traning/PyQs-master/PyQs-master/python-initial-reference/ToBeShared/reference/Code/web/flask/weather.py>7
30296b5df31137bd436722936c6357a8dfe955215a86Return 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 time752https://github.com/asha952/cs-1.3_algorithms/blob/master/linked_list.py2
31306b5df31137bd436722936c6357a8dfe955215a86Return 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.head722https://github.com/asha952/cs-1.3_algorithms/blob/master/linked_list.py4
32315d1cabb5ea56ef3ac8607c9ea420c56678ae6e7b,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,812https://github.com/JulienAndres/p_androidKilobot/blob/master/mEDEA/stats_robot/test.py>7
3332aa914b233c39f2bba9f9ca3425eb0adb631a43fc) 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)715https://github.com/pziajski/ZRecognition/blob/master/AzureImageRecognition.py>7
3433c94cf9a0235e7137f88385ab5c88ae6369e736c8headers = {'Ocp-Apim-Subscription-Key': subscription_key, 'Content-Type': 'application/octet-stream'} params = {'language': 'unk', 'detectOrientation ': 'true'} data = {'url': image_url} response = requests.post(633https://github.com/aayushvats/med_id/blob/master/ocr.py>7
353400f38ab64ac06074049b0dde2efdba6d52214313image_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()1466https://github.com/vishnoitanuj/Azure-tutorials/blob/master/Video_Analysis.py>7
3635910dc45b477682df33a75979ecb8932612776c35" 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()914https://github.com/nrjvarshney/QuoteFromPic/blob/master/quotesServer/quotesServer/quoteapi/views.py>7
3736f0bc867888c48e59d98da85a88da423465d13d10vision_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'}793https://github.com/Ujjwal0501/hallucinators/blob/master/Text_Gen.py>7
383702fce827f849a37fd59ba18a70852fa1bca546af) 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)713https://github.com/WeiShi78/Xbuyer/blob/master/test/Test.py>7
3938910dc45b477682df33a75979ecb8932612776c35assert 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()1235https://github.com/nrjvarshney/QuoteFromPic/blob/master/quotesServer/quotesServer/quoteapi/views.py>7
4039f75875be86f0f17fc3e9aae98f743f02982e444a= ["2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015", "2016", "2017"]742https://github.com/DaviPolita/Dashboards/blob/master/Plotly_Graphs/Animated_Scatter/gender_ineq.py>7
4140876ad13e615cda2592f907c2739e09faa21477d4"2016", "2015", "2014", "2013", "2012", "2011", "2010", "2009", "2008", "2007", "2006", "2005", "2004", "2003", "2002", "2001", "2000", "1999", "1998", "1997"792https://github.com/abhinavbansal19961996/Advocatefinal/blob/master/update.py>7
42414118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
434247081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
44435e9c280ba82bbe9237fe3f8dff0c82dce3bdcf5e): 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) return682https://github.com/morganhowell95/Algorithms/blob/master/Comparison-Sorts/quick_sort.py2
45444118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
464547081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
47464118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
484747081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
49484118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
504921f646e28b5aa5d074688a587f8cc16d2d05a5b0a): 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)782https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py2
51502edbc61bf0f23c785b94c3dd6b178bbc94127f35lista): 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) +663https://github.com/AAMergulhao/Sort_Algorithms/blob/master/algorithms.py2
52517457f881c1b82d80957b8acf1859a4a73a7e88b4array): 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)784https://github.com/fali007/basic-programming/blob/master/sorting/quicksort.py2
53524118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
54534118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
55547457f881c1b82d80957b8acf1859a4a73a7e88b4array): 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)784https://github.com/fali007/basic-programming/blob/master/sorting/quicksort.py2
5655d730f06e052b92b5241b0feb5b7436ad708f79b1arr): 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)796https://github.com/yvprashanth/python-google-tutorial/blob/master/basic/quicksort.py2
575647081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
585747081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
5958be05fb926bf6d0f5b10addd65a7bd26bf41a466e# 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].892https://github.com/mszhai/nlp_algo/blob/master/test/pd.py1
6059c054698149636d13ae8ad1ed97459812d0d1ebbcfig = 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)1155https://github.com/afding/mylab/blob/master/algrithm/3dplot.demo.py0
6160f4e6dcf3008410acb9d95b2ba78645b12f5eebf8]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()27914https://github.com/v3ss0n/scikit-learn/blob/master/examples/svm/plot_svm_iris.py0
6261a80fef7436689974cff2664b4a0e8160c74a06a2from 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)855https://github.com/kmandli/ML-python-code-without-LIBRARIES/blob/master/linear_regression_cost_function.py0
6362c690d3284caf91996572b047fbe5425c93d8e25e') # 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='813https://github.com/TheRealMarcusChiu/PythonMasterExample/blob/master/src/third-party/03_graphs/3d/scatter.py0
64639303cf4b43f8b33a958f1b0025bd2a07f2798e80# 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 =34122https://github.com/ranasingh-gkp/Machine-Learning/blob/master/Part 3 - Classification/Section 16 - Support Vector Machine (SVM)/Python_SVM.py0
65645e9c280ba82bbe9237fe3f8dff0c82dce3bdcf5e): 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) return682https://github.com/morganhowell95/Algorithms/blob/master/Comparison-Sorts/quick_sort.py2
666547081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
676647081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
686768813c1284352872db9a5abdaaaabf8c8e21c16d['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','1063https://github.com/parsa3000/SE18/blob/master/stockgame2/home/listofstockscrypto.py>7
69686bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
70693a162697d1abaa9ffb4d3f14ff97828c642ea427= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','DD','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','992https://github.com/quentintruong/Stocks-Scraper/blob/master/stocks/spiders/stocks_spider.py>7
71704992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
7271fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
73724992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
7473886bc47941eadd52a758206094854c8505d85410', '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'1015https://github.com/andrewmagis/docker/blob/master/ipython-dev/Qiime/qiime/split_libraries_fastq.py0
75745b2bf24b4ae3a8c68dc4e52c1e5bdca89af216c4= {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, 24:1003https://github.com/cnrat/dec-eve-serenity/blob/master/client/encodings/cp864.py1
76755b2bf24b4ae3a8c68dc4e52c1e5bdca89af216c4= {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, 24:1003https://github.com/cnrat/dec-eve-serenity/blob/master/client/encodings/cp864.py1
7776971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 48,963https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
7877af4b00fee4953dec519c7e35e3163f60609466dcs[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]894https://github.com/wjwainwright/Capstone/blob/master/IsoFitv18.py>7
7978eb3ae194c4c2eb8719db5c353485c3e31831f1acVALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", tuple(644https://github.com/labopvlab/PythonDataAnalyzer/blob/master/apps/mergingDBs_v1.py>7
80798f0abf15d48fe3c7357ed453ba8bb45dbd536d07lon1, 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 * 1000836https://github.com/TimothyLx/Mining-method-based-on-semantic-trajectory-frequent-pattern-and-carpooling-application/blob/master/distance_calculate.py6
8180a4c3d2c979c489e47c250f5fd3402328044f19fa""" 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 km1135https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py6
8281a4c3d2c979c489e47c250f5fd3402328044f19fa""" 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 km1135https://github.com/NervosaX/reparser/blob/master/modules/gmaps.py6
83828c76f07cfbfa90928d72dcf76029b44d8e9eb21c# 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 * r1015https://github.com/sarbjot-14/SFU/blob/master/cmpt353/e3/GPS_Tracks/calc_distance.py6
8483b3326f25c405bab05ae8898a978dcd1bb27358b0parser = 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()775https://github.com/THULimy/pytorch-Hscore/blob/master/cifar-resnet.py1
858421f646e28b5aa5d074688a587f8cc16d2d05a5b0a): 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)782https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py1
86854118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
87864118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
888747081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
898847081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
9089fde8fae9d13625d97b7d39342bbc9100a42cf8d9= ['Date/Time', 'Temp (°C)', 'Dew Point Temp (°C)', 'Rel Hum (%)', 'Wind Dir (10s deg)', 'Wind Spd (km/h)', 'Visibility (km)', 'Stn Press (kPa)', '694https://github.com/patrickacheung/weather-tod-predictor/blob/master/clean_weather.py>7
9190f2ed15c0121fc4d4ab8d3c0c87c3c745aa05853f= ['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 Dir763https://github.com/iss4e/webike-toolchain/blob/master/webike/data/WeatherGC.py>7
92918288745b3d457294b33551ac7a3d6d8d391c44faheaders = { '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)652https://github.com/ZhekunInc/football-wiki/blob/master/src/scraping/management/commands/fifa_country.py4
93924118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
94934118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
959447081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
96954118a938ea514437331aa7c8b9a9e0e1a398d8d7arr): 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)776https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
979647081907e60f9f9cab0effee35db245a5b7003a6arr): 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)783https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
989747081907e60f9f9cab0effee35db245a5b7003a6: 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)763https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
999847081907e60f9f9cab0effee35db245a5b7003a6: 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)763https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
1009947081907e60f9f9cab0effee35db245a5b7003a6: 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)763https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
1011004118a938ea514437331aa7c8b9a9e0e1a398d8d7if 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)746https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
10210147081907e60f9f9cab0effee35db245a5b7003a6if 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)753https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
10310247081907e60f9f9cab0effee35db245a5b7003a6if 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)753https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
10410347081907e60f9f9cab0effee35db245a5b7003a6if 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)753https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py1
1051044118a938ea514437331aa7c8b9a9e0e1a398d8d7if 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)746https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py1
106105971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49973https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py4
10710643d142060c012adf5436e71991f17b8e81168311[-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, -1,4391https://github.com/youngminpark2559/temp_for_study/blob/master/study_huggingface_NLP/examples/My_test/Test_BERT_LM_model.py1
1081079ebe0da4eabfbbd56a5cdd9704fb6c3872162936Config(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(1304https://github.com/vitalii-levko/microblog/blob/master/microblog/config.py2
1091089ebe0da4eabfbbd56a5cdd9704fb6c3872162936Config(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(1304https://github.com/vitalii-levko/microblog/blob/master/microblog/config.py2
11010959b316cdb58c43d28de33d284ed7b8ac9bab06baif 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 != '752https://github.com/duongd08/CECS-174-Spring-2018/blob/master/Uno.py>7
1111108b515e8a34021fe09632bd8387ef3a9734bb1c1b', 'AMD', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT682https://github.com/rorygwozdz/coding/blob/master/finance/gcg/image_creator.py>7
1121117ebb786cd066594187910cfba3b3e58c3603b02d', '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', '22315https://github.com/Shiva-gs/Project3/blob/master/stock_data.py>7
1131127ebb786cd066594187910cfba3b3e58c3603b02d', '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',22410https://github.com/Shiva-gs/Project3/blob/master/stock_data.py>7
1141137ebb786cd066594187910cfba3b3e58c3603b02d', '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', '31919https://github.com/Shiva-gs/Project3/blob/master/stock_data.py>7
115114687774b16d0478f4bf1aca760b628253d21d3267if 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 False743https://github.com/redmechanic/My-Project-Euler-Solutions/blob/master/Problem 27/prime_quadratic.py2
116115c61d42e2a6eaf8c9c9b03d4ebc15e6a9ec999768print(now.strftime("%Y-%m-%d %H:%M:%S")) print(now.strftime("%Y-%m-%d")) print(now.strftime("%H:%M:%S"))622https://github.com/contsman/pythonweb/blob/master/testpython/Commonly_used_builtin_module.py>7
117116964357c438769c177a2c14743aa82fa875ac2d80, "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", "1408https://github.com/da-woods/cython/blob/master/setup.py>7
118117964357c438769c177a2c14743aa82fa875ac2d80", "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",1196https://github.com/da-woods/cython/blob/master/setup.py>7
1191181324ed920d6ad53fd3322f862703051161d16b4f@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 :: 3663https://github.com/ylathouris/glossy/blob/master/setup.py>7
1201199da3365c7b91281b7073c07c495ff3033dfaa543(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 edge39618https://github.com/bachiraoun/pdbparser/blob/master/Utilities/Collection.py2
1211209da3365c7b91281b7073c07c495ff3033dfaa543(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 is36717https://github.com/bachiraoun/pdbparser/blob/master/Utilities/Collection.py2
122121b32657aa5d791091bd6992730a1a48d8b4b1152f= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),611https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py3
123122209e809060efff74c137c9b7c69d5d5168bff92a2, 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, 13913https://github.com/odolan/Game-of-War-Predictor-/blob/master/War Predictor/GameOfWar.py>7
124123bd0d429e0742b94a8b820221dd64c909f7b47c13, 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, 10,732https://github.com/rogerkenny/pystuff/blob/master/Solutions.py>7
125124b32657aa5d791091bd6992730a1a48d8b4b1152f= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),611https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py3
126125b32657aa5d791091bd6992730a1a48d8b4b1152f= {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Minsu','Jack','Lee','David','Gasper','Betina','Andres']),611https://github.com/wojiaolds/python-test/blob/master/pandas_test/dataframe_base.py3
127126eb52f02463b6ed46f0ffbbe2e15a65998cc778d4\\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\\t1412https://github.com/dbc1040/WeiboCrawler/blob/master/weibocrawler/proc_user_pages.py1
12812746a01cf8cb75ac9b2b7e223e22f1575d0cf1320dobject. 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)863https://github.com/munishgarg-02/GoogleAPI/blob/master/google-cloud-sdk/lib/googlecloudsdk/third_party/apis/dialogflow/v2/dialogflow_v2_messages.py0
129128971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,1003https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py0
130129e0dead7e27af4a6122ccff07904c4d91137f59d9(): 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)1015https://github.com/RajputJay41/python-for-finance/blob/master/automating and getting s&p list.py6
131130971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47933https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
13213124657fc9722b450bcb7afda9c2cbfa54d356d80fhome_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 =461https://github.com/lucaspbordignon/sgbcloud/blob/master/src/nlp.py>7
133132287df0f319785e386cb64eda635766799a1b731d?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""", (row[0], row[1], row[2], row[3], row[4], row[5], row[6], row[7], row[8], row[9], row[10]812https://github.com/devichs/Python-Bball-Stats/blob/master/shotStat.py>7
134133507245517ceb9d0e901a142ad45a421ee0cc008b', '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://793https://github.com/lianghq7/get_url/blob/master/qunaer/qunaer.py>7
13513445074562bee9d4f6d264fe9a484446a6ab78dd34# 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, MockOptions33124https://github.com/auroranockert/webkit/blob/master/Tools/Scripts/webkitpy/tool/commands/rebaseline_unittest.py0
1361353a066157e3ff2c9b6b148ae7da3f4f6887c6379d#!/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"36023https://github.com/roelvanderburg/Sentiment-Analysis/blob/master/tweet_tokenizer.py0
137136c101dc6dd83eca9260fbfc0369979a7965240df4s+\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+\d1001https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py4
138137a805fae6363210162f97e35e88cd8aec0ac453a9Permission 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:862https://github.com/rckirby/loopy/blob/master/loopy/diagnostic.py3
139138a805fae6363210162f97e35e88cd8aec0ac453a9Permission 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:862https://github.com/rckirby/loopy/blob/master/loopy/diagnostic.py3
140139971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 50,1003https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
14114034819bf6e7c8d452fbd0c131403c453a11338308(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))1284https://github.com/jumpscale7/web/blob/master/pythonlib/argh/assembling.py>7
142141971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,983https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
143142971a5155a320a23115a41d16f14b6ccc6ffe9801,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,531003https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
144143146055c776a42d50e98ffd46b5e6fbe5aca46707The 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. # * Redistributions621https://github.com/tadiphone-caf/bootable_bootloader_edk2/blob/master/QcomModulePkg/Tools/image_header.py0
145144b180c23466aeb19f0e063e72e078778ffc9918b5>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>', '<p>1031https://github.com/DixonShen/paper_work1/blob/master/v3/v3_utils.py1
146145971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,983https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
147146e2ed4a8c5b4df153be23cdfe09e9753c21631f56[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.dfs632https://github.com/varun21290/leetcode_solutions/blob/master/Course Schedule/Solution.py2
14814729e7bb8572b9d802dda47c3dda901f3c44a5504d'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',1003https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py0
149148d3fd8267c90805fcb17e609d7f96a6fc376eb881'2018', '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', '1990'1154https://github.com/pnxenopoulos/cs-communities/blob/master/prepare-data/process_data.py0
15014929e7bb8572b9d802dda47c3dda901f3c44a5504d2022', '2023', '2024', '2025', '2026', '2027', '2028', '2029', '2030', '2031', '2032', '2033', '2034', '2035', '2036', '2037', '2038', '2039', '2040', '2041', '2042', '2043', '2044', '2045', '2046', '1003https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py0
151150d3fd8267c90805fcb17e609d7f96a6fc376eb881'2018', '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', '1990'1154https://github.com/pnxenopoulos/cs-communities/blob/master/prepare-data/process_data.py0
15215129e7bb8572b9d802dda47c3dda901f3c44a5504d'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',1003https://github.com/HauHe/OSeMBEtoREEEMdb/blob/master/results_processing/txt_to_df.py0
153152fc6fc80b7defa2838dc26c92a245648646d24f17(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]?)$"913https://github.com/Zenithar/cuckoo-modified/blob/master/web/web/settings.py>7
154153fc6fc80b7defa2838dc26c92a245648646d24f17(r"^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01753https://github.com/Zenithar/cuckoo-modified/blob/master/web/web/settings.py>7
1551540b72bbb9d93a63b5da7c49c438e6cd10df9283e5', 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',1134https://github.com/dominicrodger/djangofinance/blob/master/setup.py0
1561550e3d2aa266b13e6a7f62b708d8fb4ba0a43cdb25#!/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, POCBase1063https://github.com/vulscanteam/vulscan/blob/master/vul/49-Nginx-Remote-Integer-Overflow.py0
157156ec98dbafc2251a08cb676e29f9af05b779fbf542# -*- 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 *1769https://github.com/BackupTheBerlios/destar-svn/blob/master/branches/icom-avatar/cfg_app_meetme.py0
158157640099e1563924a7ab8373807462716eb43273e7HANGMAN = ( """ ------ | | | | | | | | | ---------- """, """ ------ | | | O | | | | | | ---------- """, """ ------ | | | O | -+- | | | | | ---------- """, """ ------ | | | O | /-+- | | | | | ---------- """, """ ------ | | | O | /-+-/ | | | | | ---------- """, """ ------ | | | O | /-+-/ | | | | | | ---------- """, """ ------ | | | O | /-+-/ | | | | | | | | | ---------- """, """ ------ | | | O | /-+-/ | | | | | | | | | | | ---------- """) MAX_WRONG = len(HANGMAN) - 1 WORDS = ("OVERUSED", "CLAM", "GUAM", "TAFFETA", "PYTHON")22310https://github.com/theglitchmitch/M3-Learning-Python/blob/master/Chapter_5/Hangman_Game.py5
1591580fc3a34d1254d5dc319c792ea0b8c0c9a15ee786HANGMAN_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()27215https://github.com/ShulinLiu/PythonNote/blob/master/Games/hangman.py5
160159aa88d5324a6c0b45becff4fac72e7b92c753684a, '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) ==622https://github.com/jaeteekae/DelayedTwitter/blob/master/get_top_twitter_accounts.py5
161160c4a3a88b9fccb47902fd5b19acb79c98865d0ac80.68, 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, 0.92,1005https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
162161e47ed3a97799388b6100bb67048e6ad8c0e4da5fi[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],i22612https://github.com/genezonxiii/Population_Data/blob/master/population_data/age_education.py>7
16316226baf8973a6c2bb1a52ea72d6da4a2e552a10ebc.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')})1144https://github.com/rishikksh20/matplotlib/blob/master/customizationExamples.py6
1641630837e9d3e9367fd29476288ee8a1bad8d45f24660.02, 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, 0.26,1005https://github.com/samta/nonlinear_regression/blob/master/data.py>7
1651646bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
16616581c282288dfee4875a4f8e004d5f3a6ccdd2a49f= ['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','1153https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py>7
1671664992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
1681674992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
169168a272bcee535cdfdaeb6c1472e475e76cb0e2e3fa= ['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'1173https://github.com/seantrinh/thewolvesofwallstreet/blob/master/copy_run.py>7
170169fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
1711704992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','953https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
17217180e251e4e9f8b0f9ac0207bf84a036f040e10cb2) 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)19712https://github.com/SombrHeroQc/Finance101/blob/master/investing101.py>7
1731727ebb786cd066594187910cfba3b3e58c3603b02d= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', 'LNT1004https://github.com/Shiva-gs/Project3/blob/master/stock_data.py>7
1741736bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
17517481c282288dfee4875a4f8e004d5f3a6ccdd2a49f= ['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','1153https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py>7
176175fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
17717681c282288dfee4875a4f8e004d5f3a6ccdd2a49f= ['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','1153https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py>7
1781774992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
17917881c282288dfee4875a4f8e004d5f3a6ccdd2a49f= ['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','1153https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py>7
180179fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
1811804992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
182181fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
1831824992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
1841836bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
185184fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
186185fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
1871864992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
188187fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
189188fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
19018968813c1284352872db9a5abdaaaabf8c8e21c16d['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', '1023https://github.com/parsa3000/SE18/blob/master/stockgame2/home/listofstockscrypto.py>7
1911904992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','953https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
1921914992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','953https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
1931924992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','953https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
194193971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 47933https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
195194ef289839bba660b1ea8e7dfbf6ede70578ead0e3# 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 # 651305https://github.com/MReneBrown/Python-Course/blob/master/Function_Syntax.py>7
196195ef289839bba660b1ea8e7dfbf6ede70578ead0e3# 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 # 641285https://github.com/MReneBrown/Python-Course/blob/master/Function_Syntax.py>7
1971964c950265f099c64e88b64082cea5a8d91ba5e08fT1", "T2", "T3", "T4", "T5", "T6", "T7", "T8", "T9", "T10", "T11", "T12", "T13", "T14", "T15", "T16", "T17", "T18", "T19", "T20", "T21", "T22", "T23", "T24", "T25", "1004https://github.com/AndresGarciaEscalante/Schnell-Language/blob/master/Schnell.py2
1981974c950265f099c64e88b64082cea5a8d91ba5e08fT1", "T2", "T3", "T4", "T5", "T6", "T7", "T8", "T9", "T10", "T11", "T12", "T13", "T14", "T15", "T16", "T17", "T18", "T19", "T20", "T21", "T22", "T23", "T24", "T25", "1004https://github.com/AndresGarciaEscalante/Schnell-Language/blob/master/Schnell.py2
199198cbf3fa5bd72d753c2018a0f797cb3b65d5dea3d5A", "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", "71333https://github.com/EdwinUrbina-13/CipherGUI/blob/master/MorseCodeCipher.py2
200199506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefb", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"852https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py2
2012006dc7fe0605c4c500e135fb4760bf9116a131239e1", "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", "341337https://github.com/kevinwlip/Automation/blob/master/lib/common/zbAlertTemplates.py2
202201506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefbA", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U"821https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py2
2032028d7c80312dc967564c5e1cf3df26468097be232ed.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.801https://github.com/schottkey7/codewars/blob/master/Strings/domain_name_validator.py2
20420396826b181bdcae40df1006b93a8b4fe5b83ad735: 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\n4182https://github.com/elodietheelectronicfairy/blood_runner/blob/master/blood_runner_for_embedd.py5
2052049b7fae8909304d7d462d3800e5dbe8d23ed4c342(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)612https://github.com/stembl/sigproc/blob/master/asp/workspace/A2/A2Part3.py2
20620543981045ad2ae677328bfec2fb4d28db1d1b0fd9get_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 duplicates1719https://github.com/coej/social-analytics/blob/master/twitter_dl.py1
20720643981045ad2ae677328bfec2fb4d28db1d1b0fd9get_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 prevent1709https://github.com/coej/social-analytics/blob/master/twitter_dl.py1
2082075c9798600f20016bc7878a7cfbcf29dec327f0a1") 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("622https://github.com/mikelei8291/LearnPython/blob/master/lpthw/ex1.py1
209208f955f9cd2d4b2ddeb44349c2716b17dfa3f7ef3c].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) # %%835https://github.com/KaziSabrinaSonnet/Essential_Tremor_Detection/blob/master/Feature_Extracting/Classifier/Classifier_LR.py>7
210209c4a3a88b9fccb47902fd5b19acb79c98865d0ac80.43, 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, 0.67,1003https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
211210c4a3a88b9fccb47902fd5b19acb79c98865d0ac80.43, 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, 0.67,1003https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
212211c4a3a88b9fccb47902fd5b19acb79c98865d0ac843, 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, 0.1003https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
2132123f99df658c409d54d612943f38b9c8263059704b46, 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, 0.1003https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py>7
2142133f99df658c409d54d612943f38b9c8263059704b0.48, 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, 0.96,1003https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py>7
2152143f99df658c409d54d612943f38b9c8263059704b0.5, 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, 0.98,1003https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py>7
216215c4a3a88b9fccb47902fd5b19acb79c98865d0ac80.43, 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, 0.67993https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
2172163f99df658c409d54d612943f38b9c8263059704b44, 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, 0.1003https://github.com/BetterWang/QWChargeCorr/blob/master/test/qwcumu_pPb16_MB_eff_v1.py>7
218217c4a3a88b9fccb47902fd5b19acb79c98865d0ac843, 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, 0.1003https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
219218c4a3a88b9fccb47902fd5b19acb79c98865d0ac845, 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, 0.1006https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
220219c4a3a88b9fccb47902fd5b19acb79c98865d0ac80.44, 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, 0.68,1003https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
221220c4a3a88b9fccb47902fd5b19acb79c98865d0ac844, 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, 0.1004https://github.com/samuelleblanc/python_codes/blob/master/Mie_Calc.py>7
222221371419a87b9319fba36391e8005c806e75a639d3import 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():803https://github.com/monicashver/PongAI/blob/master/PongAIvAI.py>7
223222371419a87b9319fba36391e8005c806e75a639d3import 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():803https://github.com/monicashver/PongAI/blob/master/PongAIvAI.py>7
22422358458902e8132d42fc3ec0fb6495937d1f63357eimport 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(833https://github.com/angelfish91/web-crawler/blob/master/baidu-image.py>7
225224d86d3e0a8905ba466258ab06f1a8d8811832dc9bimport 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 result733https://github.com/cnelsonsic/public_drown_scanner/blob/master/scanner.py>7
226225d86d3e0a8905ba466258ab06f1a8d8811832dc9bimport 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 result733https://github.com/cnelsonsic/public_drown_scanner/blob/master/scanner.py>7
2272264bfe52bdc8fdc752a0d278665c62155c81273f860.1, 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, 2.903https://github.com/bkargoll/TriggerStudies/blob/master/turnOnTauProducer.py>7
22822787ea0a8e40da6e6d9671275b4a0c345009f695fffor 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] = key602https://github.com/cjh5414/sort-with-python/blob/master/insertion-sort.py0
22922867046ceffbef8e95b72daaa339225e8634694fa7: 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 array621https://github.com/xyang57/LeetCode/blob/master/all_sorts.py0
2302298ec0d022ae4f38b9e6d535435488a680b65f1645if not re.match("^[a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+@[a-zA-Z0-9-]+(?:\.[a-zA-Z0-9-]+)*$",713https://github.com/OliverJ20/Team-Rocket-Website-IFB299/blob/master/app/testfunctions.py0
23123099d65b9588838b2879ab981458b79dc8a434d232.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('smtp753https://github.com/sgoodwin90/work/blob/master/ZendeskAPI.py4
2322311f11d7da7ffc7a04c263f7ac1d19ef5d3ccdba3aserver_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, message673https://github.com/antowe001253/STOCKS/blob/master/Python34/old/best_play.py4
2332326e4a00787ce01b50c584f048d8dd13192b64f96eattachment = 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)693https://github.com/Presto412/VIT-Timetable-Scraper/blob/master/SendEmail.py4
2342335218aed8cf46e2ca6f38b96a56c76b381add047a# 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"1435https://github.com/spatwardhan7/Disaster-Management-Mobile-Web-App-/blob/master/sendemail.py4
23523490b47ef628f14b678d612f1d24960af0b6b68391(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 True641https://github.com/skalam02/Crypto/blob/master/rsa.py1
236235adcedfe70ca347338148f2049eb9671d22f334d4"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"655https://github.com/WatsonLee/python-small-tools/blob/master/upload.py4
237236795c84b13e59790cd5e8fe2b61b8a3e69c722c4eheader = {'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[0:14111https://github.com/apiss2/Polka-dot/blob/master/im_search.py>7
238237795c84b13e59790cd5e8fe2b61b8a3e69c722c4eheader = {'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))1268https://github.com/apiss2/Polka-dot/blob/master/im_search.py>7
239238d2e6309f96f7a621a36b42174489c5a494336fe9.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'}673https://github.com/baileye/azure-custom-vision-siggraph/blob/master/azurevision.py0
240239dc53ab4c451394227f75e0f9efa2633b445f8ce8vision_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':682https://github.com/xodhr98/hello/blob/master/main.py0
241240b31e66e793acc8639668f9c8b5ac939b5e128191.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': '603https://github.com/andybbruno/Mobile/blob/master/Client/test_no_opencv.py0
2422411e133669861afa9b7565378aa03d79259afddb98} 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()733https://github.com/xiechen0692/Computer-vision/blob/master/Intelligent_home/Iot_Project1.py0
243242ef496219f168d0a706bbba504682869e30baea2a} 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)913https://github.com/thetime50/ocr/blob/master/ocr_ms/print.py0
244243c47a16aef42e78cfdcf126d9a9ac129a457af617('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('19210https://github.com/eschlon/uther/blob/master/uther/uther.py0
2452447fcb86edfddd0bb8fde6e53dc22f364c663617abi = 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 -= 1944https://github.com/qijiayin/jiayin_practice/blob/master/88.py0
246245eac35f84b641852e2893d17a79aa0e00fb067dafwith 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.')1135https://github.com/NilsBlach/AirplaneBoarding/blob/master/code/AirplaneBoarding/measurements.py0
247246067c3c43ff91c2c19ff20715e61c5786a13e9ed8= ['__abs__', '__add__', '__and__', '__call__', '__cmp__', '__coerce__', '__contains__', '__delitem__', '__delslice__', '__div__', '__divmod__', '__eq__', '__float__', '__floordiv__', '__ge__', '__getitem__', '__getslice__682https://github.com/cyisfor/media-tagger/blob/master/proxy.py>7
248247a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772= {'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]791https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py3
24924889d6b0e1c01b7070b218dfed327575e26464e2fc: 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.')843https://github.com/abhinav2127/ProblemStatements-Python/blob/master/ConvertReadCsvUTF16ToUTF8/converter.py0
25024989d6b0e1c01b7070b218dfed327575e26464e2fc: 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.')843https://github.com/abhinav2127/ProblemStatements-Python/blob/master/ConvertReadCsvUTF16ToUTF8/converter.py0
2512509061ffa7d967c6ff59217b36a9b608f1ecfa9e45'C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9', 'C10', 'C11', 'C12', 'C13', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21', 'C22', 'C23', 'C24',965https://github.com/DownyPrio/xDeepFM/blob/master/exdeepfm/convert_ffm_process.py3
252251f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
2532524992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
254253fba9c49e384d6e3bb736c3f5c161afd2f0d1506d= ['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','1114https://github.com/1kc2/Minimal-Correlation-Portfolio/blob/master/stocks.py>7
25525433c156f0d7710a8d91218dfc2c46d643a0a6bd84[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[662https://github.com/holyrocklee/Internship/blob/master/WebAutomation/test/webtest.py>7
25625516be96e3c6cc6ac83349eee9632bb7f9765e99e8a = 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 = 26783https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py3
25725672a565623c7ae62b6488db3ddfe11b6de53ffb34", "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"711https://github.com/rxkt/Ama_Raid_Bot/blob/master/amabot.py>7
25825787d694589ac4f070de7ddb8de182c7359a4172be"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"]842https://github.com/faical-yannick-congo/news-backend/blob/master/news-service/news/endpoints/coverage_endpoint.py>7
259258a1ec0be5df1321ae12b2e74acc601a181af0532e"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",1203https://github.com/Schlegen/Microgrid-Manager/blob/master/tools.py>7
260259662476e59a96a119b89f796faf116e2d1543f13c= [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, 227,1003https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
261260a00de22eb0c4a03289b3ece804b2e7dd0de1b66eif 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 True942https://github.com/hkws/atcoder/blob/master/ABC142/D.py>7
262261a00de22eb0c4a03289b3ece804b2e7dd0de1b66eif 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 True942https://github.com/hkws/atcoder/blob/master/ABC142/D.py>7
26326290b47ef628f14b678d612f1d24960af0b6b68391if 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 True601https://github.com/skalam02/Crypto/blob/master/rsa.py>7
2642630fcee6e1cf3e8ccf71a129b3a2e7be174ca28ee0if 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 True601https://github.com/thbertoldi/trustcode_desafio/blob/master/fourth.py>7
265264a00de22eb0c4a03289b3ece804b2e7dd0de1b66eif 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 True942https://github.com/hkws/atcoder/blob/master/ABC142/D.py>7
266265662476e59a96a119b89f796faf116e2d1543f13c[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, 2291003https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
267266662476e59a96a119b89f796faf116e2d1543f13c[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, 2291003https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
268267662476e59a96a119b89f796faf116e2d1543f13c, 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, 499902https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
269268662476e59a96a119b89f796faf116e2d1543f13c, 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]1478https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
270269f0374e36670fa34a2c3264679ae2a608cc8b051a# 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_filename772https://github.com/yeony102/DTW2018/blob/master/Week06/pinterest.py>7
271270c858f69d234ae6fdf3c9240ea1c57a080d0163a0image_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()1217https://github.com/feniculi/Azure/blob/master/jumple-cognitive-services-633bdce3da9e/Test Computer Vision/riconocimento_immagine_locale.py4
272271a34690a93f7e38c8de2c4f333bd147d39441c1ecfor 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):602https://github.com/ljeabmreosn/projecteuler/blob/master/python/pe205.py2
273272971a5155a320a23115a41d16f14b6ccc6ffe980110, 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, 54893https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
274273971a5155a320a23115a41d16f14b6ccc6ffe980110, 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, 52852https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
27527485df0d22a300a937b676a185f6da4d658e61c522# 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.591https://github.com/blkart/glance/blob/master/glance/async/utils.py0
276275c834b0254318ff35a015d0e79f7ddfba6f7368f9Copyright (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.611https://github.com/zhongxia96/MGSum/blob/master/fairseq/tasks/abstractive_and_extractive.py0
2772765c2b775890ed9d5219db155e56656d9fc53152cc# 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 <http742https://github.com/kevinspaceyvn/odoo-clearcorp/blob/master/TODO-9.0/project_subproject/project_project.py0
278277c101dc6dd83eca9260fbfc0369979a7965240df4\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+\d771https://github.com/lucamassarelli/AMFC-BRCT/blob/master/core/MetricsCollector.py>7
27927832cae5b3f480c11171b1162046f11fcb1a27270f['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']20510https://github.com/rcally72/501Project1/blob/master/501Project1_Part2 v3.py5
280279971a5155a320a23115a41d16f14b6ccc6ffe9801,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54983https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
28128027ea56215171eda10f2b8dafa08ae4c8ff75e2c8/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 / 10001599https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py>7
28228127ea56215171eda10f2b8dafa08ae4c8ff75e2c8/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 / 10001599https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py>7
28328266bc4cdb34b19d1c00c02dd980d8ea139b170094if 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) / 1000.0632https://github.com/heuristik1/eai_brms/blob/master/tempsensor/readtemp.py>7
28428315c61c768eb373210b4686ef71c948b0acc20fc3() 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 + 32.0932https://github.com/sejgit/fishtank/blob/master/fishtank.py>7
285284425ddffd44b7825c94c77c2e1d35a333a81035ef0x00, 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, 0x00,2302https://github.com/sbhklr/Brutus/blob/master/RPi-Core/gfx/logo.py>7
28628527ea56215171eda10f2b8dafa08ae4c8ff75e2c8/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.1549https://github.com/haloosirnate/pitemp/blob/master/usr/local/bin/gettemp_probe4.py>7
287286e74fbd2de9afeacf9f43249f451e262e560852a5def __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(self35320https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py5
288287e74fbd2de9afeacf9f43249f451e262e560852a5""" 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 forward602https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py5
289288e74fbd2de9afeacf9f43249f451e262e560852a5def __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(35220https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py5
290289e74fbd2de9afeacf9f43249f451e262e560852a5def __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(35220https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py5
291290e74fbd2de9afeacf9f43249f451e262e560852a5def __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(self35320https://github.com/jenevans33/CS8803-1/blob/master/src/Final/ekfcode.py5
292291b84be4250873fec8f80b0194f70170020bfd5720.0, 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(663https://github.com/clover1967/pj_graphic/blob/master/pj2/teapot.py>7
293292971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 45,903https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
294293971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 48953https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
2952946f6654aeec5d798a590781b5c69fdfffb0f91548(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)1264https://github.com/Aiman-Jabaren/Image-Captioning-using-LSTM-network/blob/master/pretrained_embedding.py0
296295c16151c80c7598b36ad40fd178926c8dda5196052], [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]1104.0https://github.com/sony/nnabla-examples/blob/master/GANs/reenactgan/utils/preprocess_utils.py>7
297296971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 47933.0https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
2982977ebb786cd066594187910cfba3b3e58c3603b02d= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', 'ALK', 'ALB', 'ARE', 'ALXN', 'ALGN', 'ALLE', 'AGN', 'ADS', '994https://github.com/Shiva-gs/Project3/blob/master/stock_data.py>7
2992989382a1faf862ff3c879e84459dbce7ddba467ef5) 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, 121310https://github.com/Nibba2018/gluppy/blob/master/trans_rot_cube.py>7
3002996bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
3013006bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
3023016bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
3033026bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
3043036bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
3053046bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
30630581c282288dfee4875a4f8e004d5f3a6ccdd2a49f= ['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','1153https://github.com/ctcpbl2004/Machine_Learning_For_Investment/blob/master/Volatility Classification.py>7
3073066bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
308307f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
309308f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
310309f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
311310f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
312311f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
3133124992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['MMM','AXP','AAPL','BA','CAT','CVX','CSCO','KO','DIS','XOM','GE','GS','HD','IBM','INTC','JNJ','JPM','MCD','MRK','MSFT','NKE','PFE','PG','953https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
314313099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
315314099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3163155940ba60408240b861d1371d7df60df1fc31835cif 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)745https://github.com/gaowenhao/PythonAlgorithm/blob/master/sort/quick_sort.py1
317316099c9271fb7cad9c165584be13e16d396017aecapivot = 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)642https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3183179b3598903f3e1a54a5319dce6b56d92b6889bb64less = [] 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 + more846https://github.com/maxgardiner/sorting-algorthms/blob/master/sorting_algorithms.py1
319318099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3203190198c9dba18ccdd13c2092a1ee70fb4d9f90b0ebif 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)662https://github.com/mrdulin/python-codelab/blob/master/src/algorithm/quick_sort.py1
321320099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
322321099c9271fb7cad9c165584be13e16d396017aecapivot = 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)642https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
323322099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3243239b3598903f3e1a54a5319dce6b56d92b6889bb64less = [] 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 + more846https://github.com/maxgardiner/sorting-algorthms/blob/master/sorting_algorithms.py1
325324099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3263252252b5bd0da7241aec6675c8898e18c3e4dddfc7less = [] 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 + more846https://github.com/garciaae/median50/blob/master/sorting/quicksort.py1
327326099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
328327099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
329328099c9271fb7cad9c165584be13e16d396017aeca: 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)763https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
330329abd2a5bc34797016cf29ad70805a629175962b85: 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)721https://github.com/HanifCarroll/DSA-Practice/blob/master/python/sorting/quick_sort.py1
331330099c9271fb7cad9c165584be13e16d396017aeca: 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)763https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
3323316ea15d729be6e3fa7ac9a454f483d54d5f63ad66list): 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)713https://github.com/kahee/Python-Study/blob/master/data_structure/sort/quick_sort.py1
333332099c9271fb7cad9c165584be13e16d396017aecaarr): 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)783https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
334333099c9271fb7cad9c165584be13e16d396017aecaif 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)753https://github.com/Stuming/Harbor/blob/master/Sorting/sorting.py1
33533421f646e28b5aa5d074688a587f8cc16d2d05a5b0a): 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] return672https://github.com/chitn/Algorithms-illustrated-by-Python/blob/master/example/quick_sort.py1
3363356866b3eef9754b93a23047b81b0b6d7064a989edpw[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]692https://github.com/RelyingEarth87/PracticePython/blob/master/passwordgenerator.py3
337336ef64dcb139235e9eaee8d75108fe8ba5c5ef8fee.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("20911https://github.com/noeleon930/firetruckingHWs/blob/master/WSM/Project1/codes/VectorSpace.py3
3383373b81ee5a96ea9b5b5a0ec3ea35bd3895947fd7d8required 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.params621https://github.com/angystardust/ansible/blob/master/lib/ansible/modules/cloud/amazon/cloudformation.py3
3393385a625b09081aca8c504d9ee48c61a15cf4173045"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", "633https://github.com/qiuxianZz/qq_spider/blob/master/weixin/test1.py>7
3403395a625b09081aca8c504d9ee48c61a15cf4173045"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", "633https://github.com/qiuxianZz/qq_spider/blob/master/weixin/test1.py>7
341340f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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.findAll692https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
3423414992ed94b48a8e1e5d77f8c13a21258f20e616bb= ['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','1073https://github.com/jiewwantan/StarTrader/blob/master/compare.py>7
3433425ceada08cfab615035f6a845610f25e4bd50b246'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', 'on1306https://github.com/shayneobrien/conversational-analysis/blob/master/src/utils.py>7
344343bc6a870dbfef043d927eff793af24291cc7268e2", "he", "him", "his", "himself", "she", "her", "hers", "herself", "it", "its", "itself", "they", "them", "their", "theirs", "themselves", "what", "which", "751https://github.com/ammar188/jobAssignment/blob/master/nlp/nlp.py>7
345344077a277acd2e9431ffb39e07c10d9707e3ee344b"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"1034https://github.com/Villager-Dev/hypixel-stats/blob/master/cogs/cmds/settings.py>7
346345bd0d429e0742b94a8b820221dd64c909f7b47c1310, 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, 10,1001https://github.com/rogerkenny/pystuff/blob/master/Solutions.py>7
3473468b06b6b0365888726b12724e05a6da81fc1ad47f'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':1185https://github.com/fabiocaccamo/python-codicefiscale/blob/master/codicefiscale/codicefiscale.py>7
348347a7920bc3bdf001ee9e1a9a5c9147b2069782695b(): 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('tr752https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py0
349348a7920bc3bdf001ee9e1a9a5c9147b2069782695b(): 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)1034https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py0
35034973ebdd2f75a8ca79dd317ae39c5285fb7c2c4365() 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))1556https://github.com/infiniteloop91/Python_Projects/blob/master/S&P_Scraper.py>7
351350971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,983https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
3523518a08651c753c2c5d40ab282024384e108eb8b5d8values (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""",664https://github.com/kbalsamy/eallot/blob/master/eallot/portal/api.py>7
353352c6540a8a78181301d8e00c27331a12a26e9f469a,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,p34662https://github.com/outofink/twisted-pentago/blob/master/gamedb.py0
3543534d13d1320e6f71fcac284159f5443962443ceb50# 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]]30916https://github.com/ArturoBlazquez/Project-Euler/blob/master/10.py0
355354f26a638e6f0e5c795f679fb1bf040962839cdd39{ 0: "C", 1: "C#", 2: "D", 3: "D#", 4: "E", 5: "F", 6: "F#", 7: "G", 8: "G#", 9: "A", 10: "A#", 11: "B" }783https://github.com/vrnmthr/CptGen/blob/master/CptGen/CptGen/utils.py0
35635596826b181bdcae40df1006b93a8b4fe5b83ad735(): 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\4992https://github.com/elodietheelectronicfairy/blood_runner/blob/master/blood_runner_for_embedd.py>7
3573567a28d2ce8c0641197d5927debf7e2d961e165c54def 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 = '774https://github.com/Paddy420/pybot/blob/master/pybot.py4
358357971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 49,983https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py2
359358d03c6a562fb23b5afcd5175a1cacd19cb37806a5[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],[0,01167https://github.com/marcusljx/python-sandbox/blob/master/puzzles/TowerOfHanoi/HanoiTower.py>7
360359ee44cf1b6b1805f8ae909b88840460baf21af333Let 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 10000.1406https://github.com/alistair-clark/project-euler/blob/master/problem21.py0
361360e445c6716afdb916d46e4c111cd0ba00f1994fac""" 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. """1475https://github.com/tofu-rocketry/project-euler/blob/master/ProjectEulerAnswers.py0
362361a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89Let 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 10000.1416https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py0
363362a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89Let 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 10000.1416https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py0
364363ee44cf1b6b1805f8ae909b88840460baf21af333Let 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 10000.1407https://github.com/alistair-clark/project-euler/blob/master/problem21.py0
365364e445c6716afdb916d46e4c111cd0ba00f1994fac""" 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. """1475https://github.com/tofu-rocketry/project-euler/blob/master/ProjectEulerAnswers.py0
366365a90f0fad8b7b3a10ba7d72a201658e0ad67c8e89Let 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 10000.1417https://github.com/pcalcao/ProjectEuler/blob/master/prob_21.py0
367366971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 46913https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py1
368367971a5155a320a23115a41d16f14b6ccc6ffe98011, 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, 49973https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py1
3693685d30bbfdf55673e86b167fe3560491f89b24bed0, 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, 1528,631https://github.com/darklinden/python_algorithm_test/blob/master/01/test.py1
3703697ea30a2d47d5a31e795a0c8fdd20752170392e0c0:0,1:0,2:0,3:0,4:0,5:0,6:0,7:0,8:0,9:0,10:0,11:0,12:0,13:0,14:0,15:0,16:0,17:0,18:0,19:0,20:0,21:0,22:0,23:0,24:0994https://github.com/gluoNNet/NineQuantumsMorris/blob/master/NNMM-cenk/main_da.py>7
371370d8f4622aadb86ed48a927146ebf0fa1407812e4fweights = {'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)23712https://github.com/brosand/JetStuff/blob/master/TensorFlow/test7.py4
372371dd0ad60f515961f60b9db7959953384839e98d6bembeddings = 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_embeddings22711https://github.com/taki17/onlab/blob/master/graph_vis.py4
373372506ad7e777fc2a30edc5d9f6817b0d4d5b6bbefb"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"1033https://github.com/qzq2514/DNNCode/blob/master/textRecognition/DWCNN_CTCLoss_plateRec/evalPB.py>7
37437378fbbe00a6715e2471ad747cf604691c70940176make_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)601https://github.com/cintiamh/PythonCrashCourse/blob/master/src/pizza.py6
37537416be96e3c6cc6ac83349eee9632bb7f9765e99e8a = 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 = 26782https://github.com/Wisetorsk/INF-200-Notes/blob/master/Python/ENIGMA_ord.py>7
3763754d1c070ea37c961d457192dbe530edef1cf1c135with 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)602https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py2
3773764d1c070ea37c961d457192dbe530edef1cf1c135with 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)602https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py2
3783774d1c070ea37c961d457192dbe530edef1cf1c135with 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)601https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py2
3793784d1c070ea37c961d457192dbe530edef1cf1c135with 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)601https://github.com/SqlAndWood/Python/blob/master/Python Script Files/urlopen.py2
3803796633a1db9eab30dff587a42b588fddc460dc1177Reverse 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'] """1407https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3813806633a1db9eab30dff587a42b588fddc460dc1177Reverse 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'] """1407https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3823816633a1db9eab30dff587a42b588fddc460dc1177Reverse 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 = [1015https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3833826633a1db9eab30dff587a42b588fddc460dc1177Reverse 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 = [1014https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3843836633a1db9eab30dff587a42b588fddc460dc1177Reverse 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 = [1015https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3853846633a1db9eab30dff587a42b588fddc460dc1177Reverse 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'] """1407https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3863856633a1db9eab30dff587a42b588fddc460dc1177Reverse 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'] """1407https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3873866633a1db9eab30dff587a42b588fddc460dc1177Reverse 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 = [1014https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
3883876633a1db9eab30dff587a42b588fddc460dc1177Reverse 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 = [1015https://github.com/manishapme/hb_assessments/blob/master/1_assessment/lists/solution/practice.py2
389388c6011f18f52e7f644a0ca14a635db4575db30ac8) @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.28622https://github.com/Alysius/Nanachi/blob/master/bot.py0
390389c6011f18f52e7f644a0ca14a635db4575db30ac8) @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 link27020https://github.com/Alysius/Nanachi/blob/master/bot.py0
3913901b88840bbb595e30cb7664fdd72be9e2119e898aimport 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('18811https://github.com/tylergibbs2/async2rewrite/blob/master/sample_code.py0
392391d993499b1a03faa99c8404845bb88c8bebe39206import 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 (34919https://github.com/ThalesM/Bot-acoes-analise/blob/master/Main.py>7
393392971a5155a320a23115a41d16f14b6ccc6ffe98016, 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, 54973https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
3943932b1e7fac0b18d53b38f6131236d347a9c0ed588a: 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)602https://github.com/jouni-kantola/algo-practice/blob/master/quick-sort/quick_sort.py2
395394ec31a82cecfdc9b1ef85e66d2da5f2b729af0b5e""" 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)782https://github.com/e2crawfo/spectral_dagger/blob/master/spectral_dagger/datasets/uni_dep.py>7
39639525e00ef311572329f7e2180566c310c2f303f4fa'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's',762https://github.com/austinguo550/Hangman-AI/blob/master/challenge.py>7
3973966d16bdd5c9dc10eb858815d3dc8825e241c38878], 2: [], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: []1165https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py1
3983976d16bdd5c9dc10eb858815d3dc8825e241c38878[], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: []1125https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py1
3993986d16bdd5c9dc10eb858815d3dc8825e241c38878[], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: []1125https://github.com/IPPI-FSKTM-FDKRM/IPPI-Smart-Intelligence-System/blob/master/Flask/SocialMediaProfiler/Facebook.py1
400399d78808b7a10918d43a105d591d6bc3e2a89ec1c1data3, 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, data35,662https://github.com/yfchenaa/k-means-and-assets-allocation-/blob/master/k-means.py4
4014001ec27f7a818531166771c359e15f8c3dfd401b32, 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, 180622https://github.com/jpherrenknecht/serveur_vr/blob/master/test_numba.py2
4024016bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
403402f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
4044036bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
4054046bcafa51129e5a18509ab485a4623450ff916b71get('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.641https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
4064056bcafa51129e5a18509ab485a4623450ff916b71get('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 table631https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
407406a7920bc3bdf001ee9e1a9a5c9147b2069782695b) table = soup.find('table', {'class':'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text tickers.append(ticker)632https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py>7
4084076bcafa51129e5a18509ab485a4623450ff916b71get('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')[862https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
409408f56204645d2ade470e7792f2d675c5e6e0bd1ba4.BeautifulSoup(resp.text, "lxml") table = soup.find('table', {'class' : 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text671https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py>7
410409f56204645d2ade470e7792f2d675c5e6e0bd1ba4.BeautifulSoup(resp.text, "lxml") table = soup.find('table', {'class' : 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text671https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py>7
41141075512293896435423873fc22605f93fe01577389') 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) tickers793https://github.com/kmjacinto2145/financial-markets-simulator/blob/master/Live Financial Markets Simulator.py>7
412411f56204645d2ade470e7792f2d675c5e6e0bd1ba4.BeautifulSoup(resp.text, "lxml") table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text671https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py>7
413412f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text944https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
414413f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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')[903https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
415414a7920bc3bdf001ee9e1a9a5c9147b2069782695b) table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text tickers.append(ticker)632https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py>7
416415262b4b05988a075ae4b8da20105f8b4cb33305f8) 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)742https://github.com/VitzzViperzz/Python-Finance-Machine-Learning-projects/blob/master/extras/google_sp500.py>7
41741685b97fc328ba43f86b94d61c8dde310200bc08d7://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].text862https://github.com/crauer/econometrics/blob/master/pair_trading.py>7
418417a7920bc3bdf001ee9e1a9a5c9147b2069782695b) table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text tickers.append(ticker)632https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py>7
419418f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
420419f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
4214206bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
4224216bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
423422f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
424423a7920bc3bdf001ee9e1a9a5c9147b2069782695b) table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text tickers.append(ticker)632https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py>7
425424a2aac312e637010e12581e09e7287eaf25f81da0= ['MMM', 'ABT', 'ABBV', 'ACN', 'ATVI', 'AYI', 'ADBE', 'AMD', 'AAP', 'AES', 'AET', 'AMG', 'AFL', 'A', 'APD', 'AKAM', '673https://github.com/Abhinawk9/test/blob/master/yahooFinance.py>7
426425f56204645d2ade470e7792f2d675c5e6e0bd1ba4.BeautifulSoup(resp.text, "lxml") table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text671https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py>7
427426f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
4284276bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
429428f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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')[903https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
430429f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
431430f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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:]:792https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
432431a7920bc3bdf001ee9e1a9a5c9147b2069782695b') table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text tickers.append(ticker)642https://github.com/scaratozzolo/RandomPortfolios/blob/master/gettickers.py>7
433432f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text944https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
434433f56204645d2ade470e7792f2d675c5e6e0bd1ba4.BeautifulSoup(resp.text, "lxml") table = soup.find('table', {'class': 'wikitable sortable'}) tickers = [] for row in table.findAll('tr')[1:]: ticker = row.findAll('td')[0].text671https://github.com/SegnorAlberto/Python-In-Business-Areas/blob/master/Finance/AA_stock charting-Sentex/Part4.py>7
4354346bcafa51129e5a18509ab485a4623450ff916b71get('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].text902https://github.com/juliennassar/stock-analyser/blob/master/server/server.py>7
436435510ff56d9ab9b435d1db704b6fe07e95c8afeff6"1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24"955https://github.com/shym98/MovieSearch/blob/master/untitled/ChartDirector/pythondemo_cgi/deptharea.py3
43743636b2b3e7de8a199d45f713e0cf03cc313f669d21", "g", "gs", "mp", "fg", "fga", "fg_pct", "fg3", "fg3a", "fg3_pct", "fg2", "fg2a", "fg2_pct", "efg_pct", "ft", "fta", "ft_pct", "orb", "drb", "trb", "ast803https://github.com/BrianSchwaz/cashketball/blob/master/finished spider/playerSpider.py2
43843788af220957d11212580f0a1eeda46e108ee85b5b", "min", "pts", "fgm", "fga", "fg%", "3pm", "3pa", "3p%", "ftm", "fta", "ft%", "oreb", "dreb", "reb", "621https://github.com/aniehuser/senior-design-group10/blob/master/demos/example-workflows/scrape_nba.py2
4394386ea36698d0c7def644901c69eaaab4937bda9faa"G", "AB", "R", "H", "2B", "3B", "HR", "RBI", "SB", "CS", "BB", "SO", "IBB", "HBP", "SH", "SF"632https://github.com/putsy-caballero/VintageDraft/blob/master/entities/Batter.py3
44043936b2b3e7de8a199d45f713e0cf03cc313f669d21", "g", "gs", "mp", "fg", "fga", "fg_pct", "fg3", "fg3a", "fg3_pct", "fg2", "fg2a", "fg2_pct", "efg_pct", "ft", "fta", "ft_pct", "orb", "713https://github.com/BrianSchwaz/cashketball/blob/master/finished spider/playerSpider.py3
441440ed48df6d28b9e3bba82066c250427d78ac5516fchttps://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%2Falltableswithkeys883https://github.com/ramrom/haus/blob/master/weather.py4
442441944d16400891095f5cba285cc06c64e4aca4a676= "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"955https://github.com/aadiuppal/programming/blob/master/data_sc/w.py4
443442ed48df6d28b9e3bba82066c250427d78ac5516fchttps://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%2Falltableswithkeys883https://github.com/ramrom/haus/blob/master/weather.py4
444443944d16400891095f5cba285cc06c64e4aca4a676url = "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)774https://github.com/aadiuppal/programming/blob/master/data_sc/w.py4
44544443d366138776e9e413c71aa18513ae7c3ea30960row[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]1096https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py>7
44644543d366138776e9e413c71aa18513ae7c3ea30960row[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]1146https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py>7
447446c0d8455767ea9e44863ddcfa670ba6a541f5f628row[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]643https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py>7
4484479d4a0ad370818b6caf045c1cc50da0dc6f13c133row[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],702https://github.com/NCTUMUILab/Intelligent_noti/blob/master/script/qualtrics_to_db.py>7
449448c2d33909e4cd68f7d83081ccb5bf4608e566607erow[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[1075https://github.com/Change72/gc-python-graduate/blob/master/FeatureCate669/9_1_beforeLearn.py>7
4504497a3a71d08098f3d90ecf0152b697ae8f76b89cd5row[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[4319310https://github.com/ayman-elgharabawy/DataBaseMigrationScript/blob/master/migrator.py>7
451450c0d8455767ea9e44863ddcfa670ba6a541f5f628, 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]753https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py>7
45245143d366138776e9e413c71aa18513ae7c3ea30960, 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]1106https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py>7
45345243d366138776e9e413c71aa18513ae7c3ea30960row[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]1096https://github.com/MatsDahlberg/PythonCourse/blob/master/wangSandberg.py>7
454453c0d8455767ea9e44863ddcfa670ba6a541f5f628row[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]743https://github.com/carthage-college/django-djschoology/blob/master/djschoology/bin/schoology.py>7
455454a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772= {'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], 'e1083https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py>7
456455a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772= {'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]1053https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py>7
457456a9ccf29675c693c92bb3ca7ad8bd777cb4dfc772= {'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], 'e1083https://github.com/rrsalian/My_Coding_World/blob/master/Python_ABC/python_Prth/python_abc/ticketBookingSystem.py>7
458457971a5155a320a23115a41d16f14b6ccc6ffe98011,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,943https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py>7
459458c8ab7efa564508803170b0877019427c7586b1a6window = 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()692https://github.com/JuanBalceda/python-basics/blob/master/udacity/mindstorm.py1
460459971a5155a320a23115a41d16f14b6ccc6ffe98016, 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, 54973https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py0
4614604777897fd744ca5e37f4a05b86f01fa66369570frects1 = 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()1315https://github.com/AparnaThricovil/data-mining/blob/master/PlotGraph.py0
462461662476e59a96a119b89f796faf116e2d1543f13c, 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, 191,792https://github.com/DamonAnderson/paillier/blob/master/rabinMiller.py>7
46346247081907e60f9f9cab0effee35db245a5b7003a6(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)793https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
46446347081907e60f9f9cab0effee35db245a5b7003a6pivot = 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)642https://github.com/Tryking/DeepLearning/blob/master/cs231n/assignment1/1_python_numpy_tutorial/1_python.py2
4654644118a938ea514437331aa7c8b9a9e0e1a398d8d7(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)786https://github.com/Muzijiajian/AppliedMathmaticsForComputer/blob/master/hw0/python_tutorial.py2
466465ecad8f91a2f37bcb755ab0b26c91f38e68ac37aeplt.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.661https://github.com/ieCecchetti/Python_ML_DL_examples/blob/master/SVM/script/SVM_rbf.py0
467466a83652129522d52f93b92cc1943979f6ca1a6ba1, 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, Y1005https://github.com/Coder670/random_password_generator/blob/master/random_password_generator.py0
468467971a5155a320a23115a41d16f14b6ccc6ffe98013, 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, 52,1003https://github.com/peruzzim/cmg-cmssw/blob/master/HLTrigger/Configuration/test/OnLine_HLT_PRef.py0
4694684efe348486874eee36c0eaf2cac672ce8b5ade0btwo 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, "]882https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py1
4704694efe348486874eee36c0eaf2cac672ce8b5ade0btwo 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,"]882https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py1
4714704efe348486874eee36c0eaf2cac672ce8b5ade0b", "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, "]842https://github.com/Khainguyen1349/Exercism/blob/master/python/twelve-days/twelve_days.py1
4724712b3691d99ac7193d3d9a1be63f7c49065bd5c35b2013 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 expressed754https://github.com/bcl/anaconda/blob/master/pyanaconda/ui/gui/spokes/software.py0
473472f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
474473f18b0ee37075e4e0d5c31dbe7255ecca66830b10resp = 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].text943https://github.com/hfk97/edgar_scraping/blob/master/menu.py>7
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