d780141f89
* #547 oncall Source File: fix schema generation for json files containing arrays * source file: upda changelog * #547 oncall: source file - upgrade source-file-secure * auto-bump connector version [ci skip] Co-authored-by: Octavia Squidington III <octavia-squidington-iii@users.noreply.github.com>
415 lines
16 KiB
Python
415 lines
16 KiB
Python
#
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# Copyright (c) 2022 Airbyte, Inc., all rights reserved.
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#
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import json
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import tempfile
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import traceback
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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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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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from airbyte_cdk.entrypoint import logger
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from airbyte_cdk.models import AirbyteStream, SyncMode
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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 yaml import safe_load
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class ConfigurationError(Exception):
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"""Client mis-configured"""
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class PermissionsError(Exception):
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"""User don't have enough permissions"""
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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": 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 open(self):
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self.close()
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try:
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self._file = self._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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user = self._provider["user"]
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host = self._provider["host"]
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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}}
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if "password" in self._provider:
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password = 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.full_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)}\n{traceback.format_exc()}"
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logger.error(error_msg)
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raise ConfigurationError(error_msg) 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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reader_class = URLFile
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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: str = 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 = {}
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if reader_options:
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try:
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self._reader_options = json.loads(reader_options)
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except json.decoder.JSONDecodeError as err:
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error_msg = f"Failed to parse reader options {repr(err)}\n{reader_options}\n{traceback.format_exc()}"
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logger.error(error_msg)
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raise ConfigurationError(error_msg) from err
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self.binary_source = self._reader_format in self.binary_formats
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self.encoding = self._reader_options.get("encoding")
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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) -> 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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: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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"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\n{traceback.format_exc()}"
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logger.error(error_msg)
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raise ConfigurationError(error_msg) from err
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reader_options = {**self._reader_options}
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if self._reader_format == "csv":
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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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yield from reader(fp, **reader_options)
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elif self._reader_options == "excel_binary":
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reader_options["engine"] = "pyxlsb"
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yield from reader(fp, **reader_options)
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else:
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yield reader(fp, **reader_options)
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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 in number_types):
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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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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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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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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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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[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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for df in self.load_dataframes(fp):
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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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def _cache_stream(self, fp):
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"""cache stream to file"""
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fp_tmp = tempfile.TemporaryFile(mode="w+b")
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fp_tmp.write(fp.read())
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fp_tmp.seek(0)
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fp.close()
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return fp_tmp
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def _stream_properties(self, fp):
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if self._reader_format == "yaml":
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df_list = [self.load_yaml(fp)]
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else:
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if self.binary_source:
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fp = self._cache_stream(fp)
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df_list = self.load_dataframes(fp, skip_data=False)
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fields = {}
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for df in df_list:
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for col in df.columns:
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# if data type of the same column differs in dataframes, we choose the broadest one
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prev_frame_column_type = fields.get(col)
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fields[col] = self.dtype_to_json_type(prev_frame_column_type, df[col].dtype)
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return {field: {"type": [fields[field], "null"]} for field in fields}
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@property
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def streams(self) -> Iterable:
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"""Discovers available streams"""
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# TODO handle discovery of directories of multiple files instead
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with self.reader.open() as fp:
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if self._reader_format in ["json", "jsonl"]:
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json_schema = self.load_nested_json_schema(fp)
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else:
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json_schema = {
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"$schema": "http://json-schema.org/draft-07/schema#",
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"type": "object",
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"properties": self._stream_properties(fp),
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}
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yield AirbyteStream(name=self.stream_name, json_schema=json_schema, supported_sync_modes=[SyncMode.full_refresh])
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