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import os
import sys
from typing import Dict, Set
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import setuptools
is_py37_or_newer = sys.version_info >= (3, 7)
package_metadata: dict = {}
with open("./src/datahub/__init__.py") as fp:
exec(fp.read(), package_metadata)
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def get_long_description():
root = os.path.dirname(__file__)
with open(os.path.join(root, "README.md")) as f:
description = f.read()
return description
base_requirements = {
# Compatability.
"dataclasses>=0.6; python_version < '3.7'",
# Typing extension should be >=3.10.0.2 ideally but we can't restrict due to Airflow 2.0.2 dependency conflict
"typing_extensions>=3.7.4.3 ; python_version < '3.8'",
"typing_extensions>=3.10.0.2 ; python_version >= '3.8'",
"mypy_extensions>=0.4.3",
# Actual dependencies.
"typing-inspect",
"pydantic>=1.5.1",
"mixpanel>=4.9.0",
}
framework_common = {
"click>=6.0.0",
"click-default-group",
"PyYAML",
"toml>=0.10.0",
"entrypoints",
"docker",
"expandvars>=0.6.5",
"avro-gen3==0.7.2",
"avro>=1.10.2,<1.11",
"python-dateutil>=2.8.0",
"stackprinter",
"tabulate",
"progressbar2",
"termcolor>=1.0.0",
"types-termcolor>=1.0.0",
"psutil>=5.8.0",
"ratelimiter",
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# Markupsafe breaking change broke Jinja and some other libs
# Pinning it to a version which works even though we are not using explicitly
# https://github.com/aws/aws-sam-cli/issues/3661
# Airflow compatibility: https://github.com/apache/airflow/blob/2.2.2/setup.cfg#L125
"markupsafe>=1.1.1,<=2.0.1",
"Deprecated",
"types-Deprecated",
}
kafka_common = {
# We currently require both Avro libraries. The codegen uses avro-python3 (above)
# schema parsers at runtime for generating and reading JSON into Python objects.
# At the same time, we use Kafka's AvroSerializer, which internally relies on
# fastavro for serialization. We do not use confluent_kafka[avro], since it
# is incompatible with its own dep on avro-python3.
"confluent_kafka>=1.5.0",
"fastavro>=1.2.0",
}
kafka_protobuf = (
{
"networkx>=2.6.2",
# Required to generate protobuf python modules from the schema downloaded from the schema registry
"grpcio==1.44.0",
"grpcio-tools==1.44.0",
"types-protobuf",
}
if is_py37_or_newer
else {
"types-protobuf",
}
)
sql_common = {
# Required for all SQL sources.
"sqlalchemy==1.3.24",
# Required for SQL profiling.
"great-expectations>=0.14.11,<0.15.3",
# datahub does not depend on Jinja2 directly but great expectations does. With Jinja2 3.1.0 GE 0.14.11 is breaking
"Jinja2<3.1.0",
"greenlet",
}
aws_common = {
# AWS Python SDK
"boto3",
# Deal with a version incompatibility between botocore (used by boto3) and urllib3.
# See https://github.com/boto/botocore/pull/2563.
"botocore!=1.23.0",
}
looker_common = {
# Looker Python SDK
"looker-sdk==22.2.1"
}
bigquery_common = {
# Google cloud logging library
"google-cloud-logging",
"google-cloud-bigquery",
"more-itertools>=8.12.0",
# we do not use protobuf directly but newer version caused bigquery connector to fail
"protobuf<=3.20.1",
}
snowflake_common = {
# Snowflake plugin utilizes sql common
*sql_common,
# Required for all Snowflake sources
"snowflake-sqlalchemy<=1.2.4",
"cryptography",
}
trino = {
"trino>=0.308",
"trino[sqlalchemy]>=0.308",
}
microsoft_common = {"msal==1.16.0"}
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data_lake_base = {
*aws_common,
"parse>=1.19.0",
"pyarrow>=6.0.1",
"tableschema>=1.20.2",
"ujson>=4.3.0",
"types-ujson>=4.2.1",
"smart-open[s3]>=5.2.1",
}
data_lake_profiling = {
"pydeequ==1.0.1",
"pyspark==3.0.3",
}
s3_base = {
*data_lake_base,
"moto[s3]",
"wcmatch",
}
usage_common = {
"sqlparse",
}
# Note: for all of these, framework_common will be added.
plugins: Dict[str, Set[str]] = {
# Sink plugins.
"datahub-kafka": kafka_common,
"datahub-rest": {"requests"},
# Integrations.
"airflow": {
"apache-airflow >= 1.10.2",
},
"great-expectations": sql_common | {"sqllineage==1.3.4"},
# Source plugins
# PyAthena is pinned with exact version because we use private method in PyAthena
"athena": sql_common | {"PyAthena[SQLAlchemy]==2.4.1"},
"azure-ad": set(),
"bigquery": sql_common
| bigquery_common
| {"sqlalchemy-bigquery>=1.4.1", "sqllineage==1.3.4", "sqlparse"},
"bigquery-usage": bigquery_common | usage_common | {"cachetools"},
"clickhouse": sql_common | {"clickhouse-sqlalchemy==0.1.8"},
"clickhouse-usage": sql_common
| usage_common
| {
"clickhouse-sqlalchemy==0.1.8",
},
"datahub-lineage-file": set(),
"datahub-business-glossary": set(),
"data-lake": {*data_lake_base, *data_lake_profiling},
"s3": {*s3_base, *data_lake_profiling},
"dbt": {"requests"} | aws_common,
feat(ingest): Feast ingestion integration (#2605) * Add feast testing setup * Init Feast test script * Add feast to dependencies * Update feast descriptors * Sort integrations * Working feast pytest * Clean up feast docker-compose file * Expand Feast tests * Setup feast classes * Add continuous and bytes data to feature types * Update field type mapping * Add PDLs * Add MLFeatureSetUrn.java * Comment out feast setup * Add snapshot file and update inits * Init Feast golden files generation * Clean up Feast ingest * Feast testing comments * Yield Feature snapshots * Fix Feature URN naming * Update feast MCE * Update Feature URN prefix * Add MLEntity * Update golden files with entities * Specify feast sources * Add feast source configs * Working feast docker ingestion * List entities and features before adding tables * Add featureset names * Remove unused * Rename feast image * Update README * Add env to feast URNs * Fix URN naming * Remove redundant URN names * Fix enum backcompatibility * Move feast testing to docker * Move URN generators to mce_builder * Add source for features * Switch TypeClass -> enum_type * Rename source -> sourceDataset * Add local Feast ingest image builds * Rename Entity -> MLPrimaryKey * Restore features and keys for each featureset * Do not json encode source configs * Remove old source properties from feature sets * Regenerate golden file * Fix race condition with Feast tests * Exclude unknown source * Update feature datatype enum * Update README and fix typos * Fix Entity typo * Fix path to local docker image * Specify feast config and version * Fix feast env variables * PR fixes * Refactor feast ingest constants * Make feature sources optional for back-compatibility * Remove unused GCP files * adding docker publish workflow * Simplify name+namespace in PrimaryKeys * adding docker publish workflow * debug * final attempt * final final attempt * final final final commit * Switch to published ingestion image * Update name and namespace in java files * Rename FeatureSet -> FeatureTable * Regenerate codegen * Fix initial generation errors * Update snapshot jsons * Regenerated schemas * Fix URN formats * Revise builds * Clean up feast URN builders * Fix naming typos * Fix Feature Set -> Feature Table * Fix comments * PR fixes * All you need is Urn * Regenerate snapshots and update validation * Add UNKNOWN data type * URNs for source types * Add note on docker requirement * Fix typo * Reorder aspect unions * Refactor feast ingest functions * Update snapshot jsons * Rebuild Co-authored-by: Shirshanka Das <shirshanka@apache.org>
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"druid": sql_common | {"pydruid>=0.6.2"},
# Starting with 7.14.0 python client is checking if it is connected to elasticsearch client. If its not it throws
# UnsupportedProductError
# https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/release-notes.html#rn-7-14-0
# https://github.com/elastic/elasticsearch-py/issues/1639#issuecomment-883587433
"elasticsearch": {"elasticsearch==7.13.4"},
"feast-legacy": {"docker"},
"feast": {"feast==0.18.0", "flask-openid>=1.3.0"},
"glue": aws_common,
"hive": sql_common
| {
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# Acryl Data maintains a fork of PyHive
# - 0.6.11 adds support for table comments and column comments,
# and also releases HTTP and HTTPS transport schemes
# - 0.6.12 adds support for Spark Thrift Server
"acryl-pyhive[hive]>=0.6.13"
},
"kafka": {*kafka_common, *kafka_protobuf},
"kafka-connect": sql_common | {"requests", "JPype1"},
feat(ingest): Feast ingestion integration (#2605) * Add feast testing setup * Init Feast test script * Add feast to dependencies * Update feast descriptors * Sort integrations * Working feast pytest * Clean up feast docker-compose file * Expand Feast tests * Setup feast classes * Add continuous and bytes data to feature types * Update field type mapping * Add PDLs * Add MLFeatureSetUrn.java * Comment out feast setup * Add snapshot file and update inits * Init Feast golden files generation * Clean up Feast ingest * Feast testing comments * Yield Feature snapshots * Fix Feature URN naming * Update feast MCE * Update Feature URN prefix * Add MLEntity * Update golden files with entities * Specify feast sources * Add feast source configs * Working feast docker ingestion * List entities and features before adding tables * Add featureset names * Remove unused * Rename feast image * Update README * Add env to feast URNs * Fix URN naming * Remove redundant URN names * Fix enum backcompatibility * Move feast testing to docker * Move URN generators to mce_builder * Add source for features * Switch TypeClass -> enum_type * Rename source -> sourceDataset * Add local Feast ingest image builds * Rename Entity -> MLPrimaryKey * Restore features and keys for each featureset * Do not json encode source configs * Remove old source properties from feature sets * Regenerate golden file * Fix race condition with Feast tests * Exclude unknown source * Update feature datatype enum * Update README and fix typos * Fix Entity typo * Fix path to local docker image * Specify feast config and version * Fix feast env variables * PR fixes * Refactor feast ingest constants * Make feature sources optional for back-compatibility * Remove unused GCP files * adding docker publish workflow * Simplify name+namespace in PrimaryKeys * adding docker publish workflow * debug * final attempt * final final attempt * final final final commit * Switch to published ingestion image * Update name and namespace in java files * Rename FeatureSet -> FeatureTable * Regenerate codegen * Fix initial generation errors * Update snapshot jsons * Regenerated schemas * Fix URN formats * Revise builds * Clean up feast URN builders * Fix naming typos * Fix Feature Set -> Feature Table * Fix comments * PR fixes * All you need is Urn * Regenerate snapshots and update validation * Add UNKNOWN data type * URNs for source types * Add note on docker requirement * Fix typo * Reorder aspect unions * Refactor feast ingest functions * Update snapshot jsons * Rebuild Co-authored-by: Shirshanka Das <shirshanka@apache.org>
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"ldap": {"python-ldap>=2.4"},
"looker": looker_common,
# lkml>=1.1.2 is required to support the sql_preamble expression in LookML
"lookml": looker_common
| {"lkml>=1.1.2", "sql-metadata==2.2.2", "sqllineage==1.3.4"},
"metabase": {"requests", "sqllineage==1.3.4"},
"mode": {"requests", "sqllineage==1.3.4", "tenacity>=8.0.1"},
"mongodb": {"pymongo>=3.11", "packaging"},
"mssql": sql_common | {"sqlalchemy-pytds>=0.3"},
"mssql-odbc": sql_common | {"pyodbc"},
"mysql": sql_common | {"pymysql>=1.0.2"},
# mariadb should have same dependency as mysql
"mariadb": sql_common | {"pymysql>=1.0.2"},
"okta": {"okta~=1.7.0"},
feat(ingest): Feast ingestion integration (#2605) * Add feast testing setup * Init Feast test script * Add feast to dependencies * Update feast descriptors * Sort integrations * Working feast pytest * Clean up feast docker-compose file * Expand Feast tests * Setup feast classes * Add continuous and bytes data to feature types * Update field type mapping * Add PDLs * Add MLFeatureSetUrn.java * Comment out feast setup * Add snapshot file and update inits * Init Feast golden files generation * Clean up Feast ingest * Feast testing comments * Yield Feature snapshots * Fix Feature URN naming * Update feast MCE * Update Feature URN prefix * Add MLEntity * Update golden files with entities * Specify feast sources * Add feast source configs * Working feast docker ingestion * List entities and features before adding tables * Add featureset names * Remove unused * Rename feast image * Update README * Add env to feast URNs * Fix URN naming * Remove redundant URN names * Fix enum backcompatibility * Move feast testing to docker * Move URN generators to mce_builder * Add source for features * Switch TypeClass -> enum_type * Rename source -> sourceDataset * Add local Feast ingest image builds * Rename Entity -> MLPrimaryKey * Restore features and keys for each featureset * Do not json encode source configs * Remove old source properties from feature sets * Regenerate golden file * Fix race condition with Feast tests * Exclude unknown source * Update feature datatype enum * Update README and fix typos * Fix Entity typo * Fix path to local docker image * Specify feast config and version * Fix feast env variables * PR fixes * Refactor feast ingest constants * Make feature sources optional for back-compatibility * Remove unused GCP files * adding docker publish workflow * Simplify name+namespace in PrimaryKeys * adding docker publish workflow * debug * final attempt * final final attempt * final final final commit * Switch to published ingestion image * Update name and namespace in java files * Rename FeatureSet -> FeatureTable * Regenerate codegen * Fix initial generation errors * Update snapshot jsons * Regenerated schemas * Fix URN formats * Revise builds * Clean up feast URN builders * Fix naming typos * Fix Feature Set -> Feature Table * Fix comments * PR fixes * All you need is Urn * Regenerate snapshots and update validation * Add UNKNOWN data type * URNs for source types * Add note on docker requirement * Fix typo * Reorder aspect unions * Refactor feast ingest functions * Update snapshot jsons * Rebuild Co-authored-by: Shirshanka Das <shirshanka@apache.org>
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"oracle": sql_common | {"cx_Oracle"},
"postgres": sql_common | {"psycopg2-binary", "GeoAlchemy2"},
"presto-on-hive": sql_common
| {"psycopg2-binary", "acryl-pyhive[hive]>=0.6.12", "pymysql>=1.0.2"},
"pulsar": {"requests"},
"redash": {"redash-toolbelt", "sql-metadata", "sqllineage==1.3.4"},
"redshift": sql_common
| {"sqlalchemy-redshift", "psycopg2-binary", "GeoAlchemy2", "sqllineage==1.3.4"},
"redshift-usage": sql_common
| usage_common
| {
"sqlalchemy-redshift",
"psycopg2-binary",
"GeoAlchemy2",
"sqllineage==1.3.4",
},
"sagemaker": aws_common,
"snowflake": snowflake_common,
"snowflake-usage": snowflake_common
| usage_common
| {
"more-itertools>=8.12.0",
},
"sqlalchemy": sql_common,
"superset": {
"requests",
"sqlalchemy",
"great_expectations",
"greenlet",
"Jinja2<3.1.0",
},
"tableau": {"tableauserverclient>=0.17.0"},
"trino": sql_common | trino,
"starburst-trino-usage": sql_common | usage_common | trino,
"nifi": {"requests", "packaging"},
"powerbi": {"orderedset"} | microsoft_common,
"vertica": sql_common | {"sqlalchemy-vertica[vertica-python]==0.0.5"},
}
all_exclude_plugins: Set[str] = {
# SQL Server ODBC requires additional drivers, and so we don't want to keep
# it included in the default "all" installation.
"mssql-odbc",
}
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mypy_stubs = {
"types-dataclasses",
"sqlalchemy-stubs",
"types-pkg_resources",
"types-six",
"types-python-dateutil",
"types-requests",
"types-toml",
"types-PyMySQL",
"types-PyYAML",
"types-freezegun",
"types-cachetools",
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# versions 0.1.13 and 0.1.14 seem to have issues
"types-click==0.1.12",
"boto3-stubs[s3,glue,sagemaker]",
"types-tabulate",
# avrogen package requires this
"types-pytz",
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}
base_dev_requirements = {
*base_requirements,
*framework_common,
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*mypy_stubs,
*s3_base,
"black>=21.12b0",
"coverage>=5.1",
"flake8>=3.8.3",
"flake8-tidy-imports>=4.3.0",
"isort>=5.7.0",
"mypy>=0.920",
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# pydantic 1.8.2 is incompatible with mypy 0.910.
# See https://github.com/samuelcolvin/pydantic/pull/3175#issuecomment-995382910.
"pydantic>=1.9.0",
"pytest>=6.2.2",
"pytest-asyncio>=0.16.0",
"pytest-cov>=2.8.1",
"pytest-docker>=0.10.3,<0.12",
"tox",
"deepdiff",
"requests-mock",
"freezegun",
"jsonpickle",
"build",
"twine",
"packaging",
*list(
dependency
for plugin in [
"bigquery",
"bigquery-usage",
"clickhouse",
"clickhouse-usage",
"druid",
"elasticsearch",
"ldap",
"looker",
"glue",
"mariadb",
"okta",
"oracle",
"postgres",
"sagemaker",
"kafka",
"datahub-rest",
"redash",
"redshift",
"redshift-usage",
"data-lake",
"s3",
"tableau",
"trino",
"hive",
"starburst-trino-usage",
"powerbi",
"vertica",
# airflow is added below
]
for dependency in plugins[plugin]
),
}
base_dev_requirements_airflow_1 = base_dev_requirements.copy()
if is_py37_or_newer:
# These plugins only work on Python 3.7 or newer.
base_dev_requirements = base_dev_requirements.union(
{
dependency
for plugin in [
"feast",
"lookml",
]
for dependency in plugins[plugin]
}
)
# These plugins are compatible with Airflow 1.
base_dev_requirements_airflow_1 = base_dev_requirements_airflow_1.union(
{
dependency
for plugin in [
"lookml",
]
for dependency in plugins[plugin]
}
)
dev_requirements = {
*base_dev_requirements,
"apache-airflow[snowflake]>=2.0.2", # snowflake is used in example dags
"snowflake-sqlalchemy<=1.2.4", # make constraint consistent with extras
}
dev_requirements_airflow_1_base = {
"apache-airflow==1.10.15",
"apache-airflow-backport-providers-snowflake",
"snowflake-sqlalchemy<=1.2.4", # make constraint consistent with extras
"WTForms==2.3.3", # make constraint consistent with extras
}
dev_requirements_airflow_1 = {
*base_dev_requirements_airflow_1,
*dev_requirements_airflow_1_base,
}
full_test_dev_requirements = {
*list(
dependency
for plugin in [
"clickhouse",
"druid",
"feast-legacy",
"hive",
"ldap",
"mongodb",
"mssql",
"mysql",
"mariadb",
"snowflake",
"redash",
"kafka-connect",
"vertica",
]
for dependency in plugins[plugin]
),
}
if is_py37_or_newer:
# These plugins only work on Python 3.7 or newer.
full_test_dev_requirements = full_test_dev_requirements.union(
{
dependency
for plugin in [
"athena",
"feast",
]
for dependency in plugins[plugin]
}
)
entry_points = {
"console_scripts": ["datahub = datahub.entrypoints:main"],
"datahub.ingestion.source.plugins": [
"file = datahub.ingestion.source.file:GenericFileSource",
"sqlalchemy = datahub.ingestion.source.sql.sql_generic:SQLAlchemyGenericSource",
"athena = datahub.ingestion.source.sql.athena:AthenaSource",
"azure-ad = datahub.ingestion.source.identity.azure_ad:AzureADSource",
"bigquery = datahub.ingestion.source.sql.bigquery:BigQuerySource",
"bigquery-usage = datahub.ingestion.source.usage.bigquery_usage:BigQueryUsageSource",
"clickhouse = datahub.ingestion.source.sql.clickhouse:ClickHouseSource",
"clickhouse-usage = datahub.ingestion.source.usage.clickhouse_usage:ClickHouseUsageSource",
"data-lake = datahub.ingestion.source.data_lake:DataLakeSource",
"s3 = datahub.ingestion.source.s3:S3Source",
"dbt = datahub.ingestion.source.dbt:DBTSource",
"druid = datahub.ingestion.source.sql.druid:DruidSource",
"elasticsearch = datahub.ingestion.source.elastic_search:ElasticsearchSource",
"feast-legacy = datahub.ingestion.source.feast_legacy:FeastSource",
"feast = datahub.ingestion.source.feast:FeastRepositorySource",
"glue = datahub.ingestion.source.aws.glue:GlueSource",
"sagemaker = datahub.ingestion.source.aws.sagemaker:SagemakerSource",
"hive = datahub.ingestion.source.sql.hive:HiveSource",
"kafka = datahub.ingestion.source.kafka:KafkaSource",
"kafka-connect = datahub.ingestion.source.kafka_connect:KafkaConnectSource",
"ldap = datahub.ingestion.source.ldap:LDAPSource",
"looker = datahub.ingestion.source.looker:LookerDashboardSource",
"lookml = datahub.ingestion.source.lookml:LookMLSource",
"datahub-lineage-file = datahub.ingestion.source.metadata.lineage:LineageFileSource",
"datahub-business-glossary = datahub.ingestion.source.metadata.business_glossary:BusinessGlossaryFileSource",
"mode = datahub.ingestion.source.mode:ModeSource",
"mongodb = datahub.ingestion.source.mongodb:MongoDBSource",
"mssql = datahub.ingestion.source.sql.mssql:SQLServerSource",
"mysql = datahub.ingestion.source.sql.mysql:MySQLSource",
"mariadb = datahub.ingestion.source.sql.mariadb.MariaDBSource",
"okta = datahub.ingestion.source.identity.okta:OktaSource",
"oracle = datahub.ingestion.source.sql.oracle:OracleSource",
"postgres = datahub.ingestion.source.sql.postgres:PostgresSource",
"redash = datahub.ingestion.source.redash:RedashSource",
"redshift = datahub.ingestion.source.sql.redshift:RedshiftSource",
"redshift-usage = datahub.ingestion.source.usage.redshift_usage:RedshiftUsageSource",
"snowflake = datahub.ingestion.source.sql.snowflake:SnowflakeSource",
"snowflake-usage = datahub.ingestion.source.usage.snowflake_usage:SnowflakeUsageSource",
"superset = datahub.ingestion.source.superset:SupersetSource",
"tableau = datahub.ingestion.source.tableau:TableauSource",
"openapi = datahub.ingestion.source.openapi:OpenApiSource",
"metabase = datahub.ingestion.source.metabase:MetabaseSource",
"trino = datahub.ingestion.source.sql.trino:TrinoSource",
"starburst-trino-usage = datahub.ingestion.source.usage.starburst_trino_usage:TrinoUsageSource",
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"nifi = datahub.ingestion.source.nifi:NifiSource",
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"powerbi = datahub.ingestion.source.powerbi:PowerBiDashboardSource",
"vertica = datahub.ingestion.source.sql.vertica:VerticaSource",
"presto-on-hive = datahub.ingestion.source.sql.presto_on_hive:PrestoOnHiveSource",
"pulsar = datahub.ingestion.source.pulsar:PulsarSource",
],
"datahub.ingestion.sink.plugins": [
"file = datahub.ingestion.sink.file:FileSink",
"console = datahub.ingestion.sink.console:ConsoleSink",
"datahub-kafka = datahub.ingestion.sink.datahub_kafka:DatahubKafkaSink",
"datahub-rest = datahub.ingestion.sink.datahub_rest:DatahubRestSink",
],
"datahub.ingestion.checkpointing_provider.plugins": [
"datahub = datahub.ingestion.source.state_provider.datahub_ingestion_checkpointing_provider:DatahubIngestionCheckpointingProvider",
],
"datahub.ingestion.reporting_provider.plugins": [
"datahub = datahub.ingestion.reporting.datahub_ingestion_reporting_provider:DatahubIngestionReportingProvider",
],
"apache_airflow_provider": ["provider_info=datahub_provider:get_provider_info"],
}
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setuptools.setup(
# Package metadata.
name=package_metadata["__package_name__"],
version=package_metadata["__version__"],
url="https://datahubproject.io/",
project_urls={
"Documentation": "https://datahubproject.io/docs/",
"Source": "https://github.com/datahub-project/datahub",
"Changelog": "https://github.com/datahub-project/datahub/releases",
},
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license="Apache License 2.0",
description="A CLI to work with DataHub metadata",
long_description=get_long_description(),
long_description_content_type="text/markdown",
classifiers=[
"Development Status :: 5 - Production/Stable",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3 :: Only",
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Intended Audience :: Developers",
"Intended Audience :: Information Technology",
"Intended Audience :: System Administrators",
"License :: OSI Approved",
"License :: OSI Approved :: Apache Software License",
"Operating System :: Unix",
"Operating System :: POSIX :: Linux",
"Environment :: Console",
"Environment :: MacOS X",
"Topic :: Software Development",
],
# Package info.
zip_safe=False,
python_requires=">=3.6",
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package_dir={"": "src"},
packages=setuptools.find_namespace_packages(where="./src"),
package_data={
"datahub": ["py.typed"],
"datahub.metadata": ["schema.avsc"],
"datahub.metadata.schemas": ["*.avsc"],
"datahub.ingestion.source.feast_image": ["Dockerfile", "requirements.txt"],
},
entry_points=entry_points,
# Dependencies.
install_requires=list(base_requirements | framework_common),
extras_require={
"base": list(framework_common),
**{
plugin: list(framework_common | dependencies)
for (plugin, dependencies) in plugins.items()
},
"all": list(
framework_common.union(
*[
requirements
for plugin, requirements in plugins.items()
if plugin not in all_exclude_plugins
]
)
),
"dev": list(dev_requirements),
"dev-airflow1-base": list(dev_requirements_airflow_1_base),
"dev-airflow1": list(dev_requirements_airflow_1),
"integration-tests": list(full_test_dev_requirements),
},
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)