{ "info": { "author": "Josh Szepietowski", "author_email": "joshszep@yelp.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "Natural Language :: English", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: Implementation :: PyPy" ], "description": "# Data Pipeline Avro Util\n\n\nWhat is it?\n-----------\nThe Data Pipeline Avro utility package provides a Pythonic interface\nfor reading and writing Avro schemas. It also provides an enum class\nfor metadata that we've found useful to include in our schemas.\n\n\nDownload and Install\n---------------------------\n```\ngit clone git@github.com:Yelp/data_pipeline_avro_util.git\npip install data_pipeline_avro_util\n```\n\n\nTests\n-----\nRunning unit tests\n```\nmake test\n```\n\n\nUsage\n-----\nUsing Avro Schema Builder::\n```\nfrom data_pipeline_avro_util.avro_builder import AvroSchemaBuilder\nfrom data_pipeline_avro_util.data_pipeline.avro_meta_data import AvroMetaDataKeys\n\navro_builder = AvroSchemaBuilder()\navro_builder.begin_record(\n name=\"test_name\",\n namespace=\"test_namespace\",\n doc=\"test_doc\"\n)\navro_builder.add_field(\n name = \"key1\",\n typ = \"string\", # datatype of this field is string\n doc=\"test_doc1\",\n metadata={\n AvroMetaDataKeys.PRIMARY_KEY: 1 # first primary key\n }\n)\navro_builder.add_field(\n name = \"key2\",\n typ = \"string\",\n doc=\"test_doc2\"\n)\nrecord_json = avro_builder.end()\nprint record_json\n\n {\n \"type\": \"record\",\n \"namespace\": \"test_namespace\",\n \"name\": \"test_name\",\n \"doc\": \"test_doc\",\n \"fields\": [\n {\"type\": \"string\", \"doc\": \"test_doc1\", \"name\": \"key1\", \"pkey\": True},\n {\"type\": \"string\", \"doc\": \"test_doc2\", \"name\": \"key2\"}\n ]\n }\n```\n\n\nDisclaimer\n-------\nWe're still in the process of setting up this package as a stand-alone. There may be additional work required to run code and integrate with other applications.\n\n\nLicense\n-------\nData Pipeline Avro Util is licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0\n\n\nContributing\n------------\nEveryone is encouraged to contribute to Data Pipeline Avro Util by forking the Github repository and making a pull request or opening an issue.\n\n\n\nDocumentation\n-------------\n\nThe full documentation is at\nTODO (DATAPIPE-2030|abrar): upload servicedocs to public server.\n\n\n\nHistory\n-------\n\n0.1.0 (2015-01-29)\n++++++++++++++++++\n\n* First release.", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/Yelp/data_pipeline_avro_util", "keywords": "data_pipeline_avro_util", "license": "UNKNOWN", "maintainer": null, "maintainer_email": null, "name": "data_pipeline_avro_util", "package_url": "https://pypi.org/project/data_pipeline_avro_util/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/data_pipeline_avro_util/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/Yelp/data_pipeline_avro_util" }, "release_url": "https://pypi.org/project/data_pipeline_avro_util/0.2.3/", "requires_dist": null, "requires_python": null, "summary": "Common functionality build on top of Apache Avro", "version": "0.2.3" }, "last_serial": 2490678, "releases": { "0.2.2": [], "0.2.3": [ { "comment_text": "", "digests": { "md5": "660b6821e79d077c5cde734295555efa", "sha256": "d7720bb1c303014ca87423b3cc006a1ecb0ad63454ab364a2deafa2d0397dad3" }, "downloads": -1, "filename": "data_pipeline_avro_util-0.2.3-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "660b6821e79d077c5cde734295555efa", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 16199, "upload_time": "2016-11-17T22:02:38", "url": "https://files.pythonhosted.org/packages/e4/3c/1b537e17ae2b6920a7d3cd7eb0e56aa2fd0dbdb5332601f1fd2621aec56d/data_pipeline_avro_util-0.2.3-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "c034e81a65e111eaf4dc8ffadc5ca346", "sha256": "b632b6ecf8d139d3958ddc669a48395cbc49e95b1680fbe8269c0b7b1e64fb4e" }, "downloads": -1, "filename": "data_pipeline_avro_util-0.2.3.tar.gz", "has_sig": false, "md5_digest": "c034e81a65e111eaf4dc8ffadc5ca346", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12565, "upload_time": "2016-11-17T22:02:40", "url": "https://files.pythonhosted.org/packages/f1/7f/bed3543da77253e7bbc59c910ab18eeb58630ff162ca48a270484456966d/data_pipeline_avro_util-0.2.3.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "660b6821e79d077c5cde734295555efa", "sha256": "d7720bb1c303014ca87423b3cc006a1ecb0ad63454ab364a2deafa2d0397dad3" }, "downloads": -1, "filename": "data_pipeline_avro_util-0.2.3-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "660b6821e79d077c5cde734295555efa", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 16199, "upload_time": "2016-11-17T22:02:38", "url": "https://files.pythonhosted.org/packages/e4/3c/1b537e17ae2b6920a7d3cd7eb0e56aa2fd0dbdb5332601f1fd2621aec56d/data_pipeline_avro_util-0.2.3-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "c034e81a65e111eaf4dc8ffadc5ca346", "sha256": "b632b6ecf8d139d3958ddc669a48395cbc49e95b1680fbe8269c0b7b1e64fb4e" }, "downloads": -1, "filename": "data_pipeline_avro_util-0.2.3.tar.gz", "has_sig": false, "md5_digest": "c034e81a65e111eaf4dc8ffadc5ca346", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12565, "upload_time": "2016-11-17T22:02:40", "url": "https://files.pythonhosted.org/packages/f1/7f/bed3543da77253e7bbc59c910ab18eeb58630ff162ca48a270484456966d/data_pipeline_avro_util-0.2.3.tar.gz" } ] }