30d7b0231e
Co-authored-by: Octavia Squidington III <octavia-squidington-iii@users.noreply.github.com>
592 lines
25 KiB
Python
592 lines
25 KiB
Python
#
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# Copyright (c) 2024 Airbyte, Inc., all rights reserved.
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#
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import json
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import logging
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import os
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import sys
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import tempfile
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import traceback
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import urllib
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import zipfile
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from os import environ
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from typing import Iterable
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from urllib.parse import urlparse
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from zipfile import BadZipFile
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import backoff
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import boto3
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import botocore
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import google
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import numpy as np
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import pandas as pd
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import smart_open
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import smart_open.ssh
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from azure.storage.blob import BlobServiceClient
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from genson import SchemaBuilder
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from google.cloud.storage import Client as GCSClient
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from google.oauth2 import service_account
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from openpyxl import load_workbook
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from openpyxl.utils.exceptions import InvalidFileException
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from pandas.errors import ParserError
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from paramiko import SSHException
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from urllib3.exceptions import ProtocolError
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from yaml import safe_load
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from airbyte_cdk.entrypoint import logger
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from airbyte_cdk.models import AirbyteStream, FailureType, SyncMode
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from airbyte_cdk.utils import AirbyteTracedException, is_cloud_environment
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from .utils import LOCAL_STORAGE_NAME, backoff_handler
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SSH_TIMEOUT = 60
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# Force the log level of the smart-open logger to ERROR - https://github.com/airbytehq/airbyte/pull/27157
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logging.getLogger("smart_open").setLevel(logging.ERROR)
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class URLFile:
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"""Class to manage read from file located at different providers
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Supported examples of URL this class can accept are as follows:
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```
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s3://my_bucket/my_key
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s3://my_key:my_secret@my_bucket/my_key
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gs://my_bucket/my_blob
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hdfs:///path/file (not tested)
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hdfs://path/file (not tested)
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webhdfs://host:port/path/file (not tested)
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./local/path/file
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~/local/path/file
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local/path/file
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./local/path/file.gz
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file:///home/user/file
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file:///home/user/file.bz2
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[ssh|scp|sftp]://username@host//path/file
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[ssh|scp|sftp]://username@host/path/file
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[ssh|scp|sftp]://username:password@host/path/file
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```
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"""
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def __init__(self, url: str, provider: dict, binary=None, encoding=None):
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self._url = url
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self._provider = provider
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self._file = None
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self.args = {
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"mode": "rb" if binary else "r",
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"encoding": None if binary else encoding,
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}
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def __enter__(self):
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return self._file
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def __exit__(self, exc_type, exc_val, exc_tb):
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self.close()
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@property
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def full_url(self):
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return f"{self.storage_scheme}{self.url}"
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def close(self):
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if self._file:
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self._file.close()
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self._file = None
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def backoff_giveup(self, error):
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# https://github.com/airbytehq/oncall/issues/1954
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if isinstance(error, SSHException) and str(error).startswith("Error reading SSH protocol banner"):
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# We need to clear smart_open internal _SSH cache from the previous attempt, otherwise:
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# SSHException('SSH session not active')
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# will be raised
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smart_open.ssh._SSH.clear()
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return False
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return True
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def open(self):
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self.close()
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_open = backoff.on_exception(backoff.expo, Exception, max_tries=5, giveup=self.backoff_giveup)(self._open)
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try:
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self._file = _open()
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except google.api_core.exceptions.NotFound as err:
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raise FileNotFoundError(self.url) from err
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return self
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def _open(self):
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storage = self.storage_scheme
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url = self.url
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if storage == "gs://":
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return self._open_gcs_url()
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elif storage == "s3://":
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return self._open_aws_url()
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elif storage == "azure://":
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return self._open_azblob_url()
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elif storage == "webhdfs://":
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host = self._provider["host"]
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port = self._provider["port"]
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return smart_open.open(f"webhdfs://{host}:{port}/{url}", **self.args)
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elif storage in ("ssh://", "scp://", "sftp://"):
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# We need to quote parameters to deal with special characters
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# https://bugs.python.org/issue18140
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user = urllib.parse.quote(self._provider["user"])
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host = urllib.parse.quote(self._provider["host"])
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url = urllib.parse.quote(url)
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# TODO: Remove int casting when https://github.com/airbytehq/airbyte/issues/4952 is addressed
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# TODO: The "port" field in spec.json must also be changed
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_port_value = self._provider.get("port", 22)
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try:
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port = int(_port_value)
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except ValueError as err:
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raise ValueError(f"{_port_value} is not a valid integer for the port") from err
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# Explicitly turn off ssh keys stored in ~/.ssh
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transport_params = {"connect_kwargs": {"look_for_keys": False}, "timeout": SSH_TIMEOUT}
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if "password" in self._provider:
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password = urllib.parse.quote(self._provider["password"])
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uri = f"{storage}{user}:{password}@{host}:{port}/{url}"
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else:
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uri = f"{storage}{user}@{host}:{port}/{url}"
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return smart_open.open(uri, transport_params=transport_params, **self.args)
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elif storage in ("https://", "http://"):
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transport_params = None
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if "user_agent" in self._provider and self._provider["user_agent"]:
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airbyte_version = environ.get("AIRBYTE_VERSION", "0.0")
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transport_params = {"headers": {"Accept-Encoding": "identity", "User-Agent": f"Airbyte/{airbyte_version}"}}
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logger.info(f"TransportParams: {transport_params}")
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return smart_open.open(self.full_url, transport_params=transport_params, **self.args)
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return smart_open.open(self.full_url, **self.args)
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@property
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def url(self) -> str:
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"""Convert URL to remove the URL prefix (scheme)
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:return: the corresponding URL without URL prefix / scheme
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"""
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parse_result = urlparse(self._url)
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if parse_result.scheme:
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return self._url.split("://")[-1]
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else:
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return self._url
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@property
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def storage_scheme(self) -> str:
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"""Convert Storage Names to the proper URL Prefix
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:return: the corresponding URL prefix / scheme
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"""
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storage_name = self._provider["storage"].upper()
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parse_result = urlparse(self._url)
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if storage_name == "GCS":
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return "gs://"
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elif storage_name == "S3":
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return "s3://"
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elif storage_name == "AZBLOB":
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return "azure://"
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elif storage_name == "HTTPS":
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return "https://"
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elif storage_name == "SSH" or storage_name == "SCP":
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return "scp://"
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elif storage_name == "SFTP":
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return "sftp://"
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elif storage_name == "WEBHDFS":
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return "webhdfs://"
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elif storage_name == "LOCAL":
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return "file://"
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elif parse_result.scheme:
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return parse_result.scheme
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logger.error(f"Unknown Storage provider in: {self._url}")
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return ""
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def _open_gcs_url(self) -> object:
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service_account_json = self._provider.get("service_account_json")
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credentials = None
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if service_account_json:
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try:
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credentials = json.loads(self._provider["service_account_json"])
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except json.decoder.JSONDecodeError as err:
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error_msg = f"Failed to parse gcs service account json: {repr(err)}"
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logger.error(f"{error_msg}\n{traceback.format_exc()}")
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raise AirbyteTracedException(message=error_msg, internal_message=error_msg, failure_type=FailureType.config_error) from err
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if credentials:
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credentials = service_account.Credentials.from_service_account_info(credentials)
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client = GCSClient(credentials=credentials, project=credentials._project_id)
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else:
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client = GCSClient.create_anonymous_client()
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file_to_close = smart_open.open(self.full_url, transport_params={"client": client}, **self.args)
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return file_to_close
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def _open_aws_url(self):
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aws_access_key_id = self._provider.get("aws_access_key_id")
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aws_secret_access_key = self._provider.get("aws_secret_access_key")
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use_aws_account = aws_access_key_id and aws_secret_access_key
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if use_aws_account:
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aws_access_key_id = self._provider.get("aws_access_key_id", "")
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aws_secret_access_key = self._provider.get("aws_secret_access_key", "")
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url = f"{self.storage_scheme}{aws_access_key_id}:{aws_secret_access_key}@{self.url}"
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result = smart_open.open(url, **self.args)
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else:
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config = botocore.client.Config(signature_version=botocore.UNSIGNED)
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params = {"client": boto3.client("s3", config=config)}
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result = smart_open.open(self.full_url, transport_params=params, **self.args)
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return result
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def _open_azblob_url(self):
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storage_account = self._provider.get("storage_account")
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storage_acc_url = f"https://{storage_account}.blob.core.windows.net"
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sas_token = self._provider.get("sas_token", None)
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shared_key = self._provider.get("shared_key", None)
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# if both keys are provided, shared_key is preferred as has permissions on entire storage account
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credential = shared_key or sas_token
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if credential:
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client = BlobServiceClient(account_url=storage_acc_url, credential=credential)
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else:
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# assuming anonymous public read access given no credential
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client = BlobServiceClient(account_url=storage_acc_url)
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url = f"{self.storage_scheme}{self.url}"
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return smart_open.open(url, transport_params=dict(client=client), **self.args)
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class Client:
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"""Class that manages reading and parsing data from streams"""
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CSV_CHUNK_SIZE = 10_000
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binary_formats = {"excel", "excel_binary", "feather", "parquet", "orc", "pickle"}
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def __init__(self, dataset_name: str, url: str, provider: dict, format: str = None, reader_options: dict = None):
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self._dataset_name = dataset_name
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self._url = url
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self._provider = provider
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self._reader_format = format or "csv"
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self._reader_options = reader_options or {}
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self._is_zip = url.lower().endswith(".zip")
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self.binary_source = self._reader_format in self.binary_formats or self._is_zip
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self.encoding = self._reader_options.get("encoding")
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@property
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def reader_class(self):
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if is_cloud_environment():
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return URLFileSecure
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return URLFile
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@property
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def stream_name(self) -> str:
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if self._dataset_name:
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return self._dataset_name
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return f"file_{self._provider['storage']}.{self._reader_format}"
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def load_nested_json_schema(self, fp) -> dict:
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# Use Genson Library to take JSON objects and generate schemas that describe them,
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builder = SchemaBuilder()
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if self._reader_format == "jsonl":
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for o in self.read():
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builder.add_object(o)
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else:
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builder.add_object(json.load(fp))
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result = builder.to_schema()
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if "items" in result:
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# this means we have a json list e.g. [{...}, {...}]
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# but need to emit schema of an inside dict
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result = result["items"]
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result["$schema"] = "http://json-schema.org/draft-07/schema#"
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return result
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def load_nested_json(self, fp) -> list:
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if self._reader_format == "jsonl":
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result = []
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line = fp.readline()
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while line:
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result.append(json.loads(line))
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line = fp.readline()
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else:
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result = json.load(fp)
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if not isinstance(result, list):
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result = [result]
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return result
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def load_yaml(self, fp):
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if self._reader_format == "yaml":
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return pd.DataFrame(safe_load(fp))
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def load_dataframes(self, fp, skip_data=False, read_sample_chunk: bool = False) -> Iterable:
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"""load and return the appropriate pandas dataframe.
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:param fp: file-like object to read from
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:param skip_data: limit reading data
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:param read_sample_chunk: indicates whether a single chunk should only be read to generate schema
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:return: a list of dataframe loaded from files described in the configuration
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"""
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readers = {
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# pandas.read_csv additional arguments can be passed to customize how to parse csv.
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# see https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
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"csv": pd.read_csv,
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# We can add option to call to pd.normalize_json to normalize semi-structured JSON data into a flat table
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# by asking user to specify how to flatten the nested columns
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"flat_json": pd.read_json,
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"html": pd.read_html,
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"excel": pd.read_excel,
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"excel_binary": pd.read_excel,
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"fwf": pd.read_fwf,
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"feather": pd.read_feather,
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"parquet": pd.read_parquet,
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"orc": pd.read_orc,
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"pickle": pd.read_pickle,
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}
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try:
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reader = readers[self._reader_format]
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except KeyError as err:
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error_msg = f"Reader {self._reader_format} is not supported."
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logger.error(f"{error_msg}\n{traceback.format_exc()}")
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raise AirbyteTracedException(message=error_msg, internal_message=error_msg, failure_type=FailureType.config_error) from err
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reader_options = {**self._reader_options}
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try:
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if self._reader_format == "csv":
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bytes_read = 0
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reader_options["chunksize"] = self.CSV_CHUNK_SIZE
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if skip_data:
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reader_options["nrows"] = 0
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reader_options["index_col"] = 0
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for record in reader(fp, **reader_options):
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bytes_read += sys.getsizeof(record)
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yield record
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if read_sample_chunk and bytes_read >= self.CSV_CHUNK_SIZE:
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return
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elif self._reader_format == "excel_binary":
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reader_options["engine"] = "pyxlsb"
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yield reader(fp, **reader_options)
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elif self._reader_format == "parquet":
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reader_options["engine"] = "fastparquet"
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yield reader(fp, **reader_options)
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elif self._reader_format == "excel":
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try:
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for df_chunk in self.openpyxl_chunk_reader(fp, **reader_options):
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yield df_chunk
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except (InvalidFileException, BadZipFile):
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yield pd.read_excel(fp, **reader_options)
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else:
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yield reader(fp, **reader_options)
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except ParserError as err:
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error_msg = f"File {fp} can not be parsed. Please check your reader_options. https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html"
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logger.error(f"{error_msg}\n{traceback.format_exc()}")
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raise AirbyteTracedException(message=error_msg, internal_message=error_msg, failure_type=FailureType.config_error) from err
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except UnicodeDecodeError as err:
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error_msg = (
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f"File {fp} can't be parsed with reader of chosen type ({self._reader_format}). "
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f"Please check provided Format and Reader Options. {repr(err)}."
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)
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logger.error(f"{error_msg}\n{traceback.format_exc()}")
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raise AirbyteTracedException(message=error_msg, internal_message=error_msg, failure_type=FailureType.config_error) from err
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@staticmethod
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def dtype_to_json_type(current_type: str, dtype) -> str:
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"""Convert Pandas Dataframe types to Airbyte Types.
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:param current_type: str - one of the following types based on previous dataframes
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:param dtype: Pandas Dataframe type
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:return: Corresponding Airbyte Type
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"""
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number_types = ("int64", "float64")
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if current_type == "string":
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# previous column values was of the string type, no sense to look further
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return current_type
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if dtype == object:
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return "string"
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if dtype in number_types and (not current_type or current_type == "number"):
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return "number"
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if dtype == "bool" and (not current_type or current_type == "boolean"):
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return "boolean"
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if dtype == "datetime64[ns]":
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return "date-time"
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return "string"
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@property
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def reader(self) -> reader_class:
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return self.reader_class(url=self._url, provider=self._provider, binary=self.binary_source, encoding=self.encoding)
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@backoff.on_exception(backoff.expo, ConnectionResetError, on_backoff=backoff_handler, max_tries=5, max_time=60)
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def read(self, fields: Iterable = None) -> Iterable[dict]:
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"""Read data from the stream"""
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with self.reader.open() as fp:
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try:
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if self._reader_format in ["json", "jsonl"]:
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yield from self.load_nested_json(fp)
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elif self._reader_format == "yaml":
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fields = set(fields) if fields else None
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df = self.load_yaml(fp)
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df.columns = df.columns.astype(str)
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columns = fields.intersection(set(df.columns)) if fields else df.columns
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df = df.where(pd.notnull(df), None)
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yield from df[list(columns)].to_dict(orient="records")
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else:
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fields = set(fields) if fields else None
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if self.binary_source:
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fp = self._cache_stream(fp)
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if self._is_zip:
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fp = self._unzip(fp)
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for df in self.load_dataframes(fp):
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df.columns = df.columns.astype(str)
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columns = fields.intersection(set(df.columns)) if fields else df.columns
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df.replace({np.nan: None}, inplace=True)
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yield from df[list(columns)].to_dict(orient="records")
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except ConnectionResetError:
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logger.info(f"Catched `connection reset error - 104`, stream: {self.stream_name} ({self.reader.full_url})")
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raise ConnectionResetError
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except ProtocolError as err:
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error_msg = (
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f"File {fp} can not be opened due to connection issues on provider side. Please check provided links and options"
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)
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logger.error(f"{error_msg}\n{traceback.format_exc()}")
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raise AirbyteTracedException(message=error_msg, internal_message=error_msg, failure_type=FailureType.config_error) from err
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def _unzip(self, fp):
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tmp_dir = tempfile.TemporaryDirectory()
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with zipfile.ZipFile(str(fp.name), "r") as zip_ref:
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zip_ref.extractall(tmp_dir.name)
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logger.info("Temp dir content: " + str(os.listdir(tmp_dir.name)))
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final_file: str = os.path.join(tmp_dir.name, os.listdir(tmp_dir.name)[0])
|
|
logger.info("Pick up first file: " + final_file)
|
|
fp_tmp = open(final_file, "rb")
|
|
return fp_tmp
|
|
|
|
def _cache_stream(self, fp):
|
|
"""cache stream to file"""
|
|
fp_tmp = tempfile.NamedTemporaryFile(mode="w+b")
|
|
fp_tmp.write(fp.read())
|
|
fp_tmp.seek(0)
|
|
fp.close()
|
|
return fp_tmp
|
|
|
|
def _stream_properties(self, fp, empty_schema: bool = False, read_sample_chunk: bool = False):
|
|
"""
|
|
empty_schema param is used to check connectivity, i.e. we only read a header and do not produce stream properties
|
|
read_sample_chunk is used to determine if just one chunk should be read to generate schema
|
|
"""
|
|
if self._reader_format == "yaml":
|
|
df_list = [self.load_yaml(fp)]
|
|
else:
|
|
if self.binary_source:
|
|
fp = self._cache_stream(fp)
|
|
if self._is_zip:
|
|
fp = self._unzip(fp)
|
|
df_list = self.load_dataframes(fp, skip_data=empty_schema, read_sample_chunk=read_sample_chunk)
|
|
fields = {}
|
|
for df in df_list:
|
|
for col in df.columns:
|
|
# if data type of the same column differs in dataframes, we choose the broadest one
|
|
prev_frame_column_type = fields.get(col)
|
|
df_type = df[col].dtype
|
|
fields[col] = self.dtype_to_json_type(prev_frame_column_type, df_type)
|
|
return {
|
|
field: (
|
|
{"type": ["string", "null"], "format": "date-time"} if fields[field] == "date-time" else {"type": [fields[field], "null"]}
|
|
)
|
|
for field in fields
|
|
}
|
|
|
|
def streams(self, empty_schema: bool = False) -> Iterable:
|
|
"""Discovers available streams"""
|
|
# TODO handle discovery of directories of multiple files instead
|
|
with self.reader.open() as fp:
|
|
if self._reader_format in ["json", "jsonl"]:
|
|
json_schema = self.load_nested_json_schema(fp)
|
|
else:
|
|
json_schema = {
|
|
"$schema": "http://json-schema.org/draft-07/schema#",
|
|
"type": "object",
|
|
"properties": self._stream_properties(fp, empty_schema=empty_schema, read_sample_chunk=True),
|
|
}
|
|
yield AirbyteStream(name=self.stream_name, json_schema=json_schema, supported_sync_modes=[SyncMode.full_refresh])
|
|
|
|
def openpyxl_chunk_reader(self, file, **kwargs):
|
|
"""
|
|
Use openpyxl's lazy loading feature to read Excel files (xlsx only) in chunks of 500 lines at a time.
|
|
"""
|
|
# Retrieve reader options
|
|
header = kwargs.get("header", 0)
|
|
skiprows = kwargs.get("skiprows", 0)
|
|
user_provided_column_names = kwargs.get("names")
|
|
chunk_size = 500
|
|
|
|
# Load workbook with data-only to avoid loading formulas
|
|
work_book = load_workbook(filename=file, data_only=True, read_only=True)
|
|
|
|
for sheetname in work_book.sheetnames:
|
|
work_sheet = work_book[sheetname]
|
|
data = list(work_sheet.iter_rows(values_only=True))
|
|
|
|
# Skip rows as specified
|
|
data = data[skiprows:]
|
|
|
|
if len(data) == 0:
|
|
raise AirbyteTracedException(
|
|
message="File does not contain enough rows to process.",
|
|
internal_message=f"Sheet {sheetname} contains no data after applying header and skiprows.",
|
|
failure_type=FailureType.config_error,
|
|
)
|
|
|
|
# Determine column names
|
|
if user_provided_column_names:
|
|
column_names = user_provided_column_names
|
|
elif header is not None:
|
|
if len(data) <= header:
|
|
raise AirbyteTracedException(
|
|
message="File does not contain enough rows to extract headers.",
|
|
internal_message=f"Sheet {sheetname} does not have enough rows for the specified header {header}.",
|
|
failure_type=FailureType.config_error,
|
|
)
|
|
column_names = data[header] # Extract the header row
|
|
data = data[header + 1 :] # Remove the header row and rows above it
|
|
else:
|
|
raise AirbyteTracedException(
|
|
message="Unable to determine column names. Please provide valid reader options.",
|
|
internal_message="No header or column names specified.",
|
|
failure_type=FailureType.config_error,
|
|
)
|
|
|
|
if column_names is None or len(column_names) == 0:
|
|
raise AirbyteTracedException(
|
|
message="Column names could not be determined.",
|
|
internal_message="Column names are empty or invalid.",
|
|
failure_type=FailureType.config_error,
|
|
)
|
|
|
|
if len(data) == 0:
|
|
raise AirbyteTracedException(
|
|
message="File does not contain any data rows.",
|
|
internal_message=f"Sheet {sheetname} contains no data rows after applying header and skiprows.",
|
|
failure_type=FailureType.config_error,
|
|
)
|
|
|
|
chunk = []
|
|
for row in data:
|
|
chunk.append(dict(zip(column_names, row)))
|
|
if len(chunk) == chunk_size:
|
|
yield pd.DataFrame(chunk)
|
|
chunk = []
|
|
|
|
if chunk:
|
|
yield pd.DataFrame(chunk)
|
|
|
|
|
|
class URLFileSecure(URLFile):
|
|
"""Updating of default logic:
|
|
This connector shouldn't work with local files.
|
|
"""
|
|
|
|
def __init__(self, url: str, provider: dict, binary=None, encoding=None):
|
|
storage_name = provider["storage"].lower()
|
|
if url.startswith("file://") or storage_name == LOCAL_STORAGE_NAME:
|
|
raise RuntimeError("the local file storage is not supported by this connector.")
|
|
super().__init__(url, provider, binary, encoding)
|