{
    "info": {
        "author": "Open Knowledge Foundation",
        "author_email": "info@okfn.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.7",
            "Topic :: Internet :: WWW/HTTP :: Dynamic Content",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "# dataflows-aws\n\n[![Travis](https://travis-ci.org/frictionlessdata/dataflows-aws.svg?branch=master)](https://travis-ci.org/frictionlessdata/dataflows-aws)\n[![Coveralls](http://img.shields.io/coveralls/frictionlessdata/dataflows-aws.svg?branch=master)](https://coveralls.io/r/frictionlessdata/dataflows-aws?branch=master)\n\nDataflows's processors to work with AWS\n\n## Features\n\n- `dump_to_s3` processor\n- `change_acl_on_s3` processor\n\n## Contents\n\n<!--TOC-->\n\n  - [Getting Started](#getting-started)\n    - [Installation](#installation)\n    - [Examples](#examples)\n  - [Documentation](#documentation)\n    - [dump_to_s3](#dump_to_s3)\n    - [change_acl_on_s3](#change_acl_on_s3)\n  - [Contributing](#contributing)\n  - [Changelog](#changelog)\n\n<!--TOC-->\n\n## Getting Started\n\n### Installation\n\nThe package use semantic versioning. It means that major versions  could include breaking changes. It's recommended to specify `package` version range in your `setup/requirements` file e.g. `package>=1.0,<2.0`.\n\n```bash\n$ pip install dataflows-aws\n```\n\n### Examples\n\nThese processors have to be used as a part of data flow. For example:\n\n```python\nflow = Flow(\n    load('data/data.csv'),\n    dump_to_s3(\n        bucket=bucket,\n        acl='private',\n        path='my/datapackage',\n        endpoint_url=os.environ['S3_ENDPOINT_URL'],\n    ),\n)\nflow.process()\n```\n\n## Documentation\n\n### dump_to_s3\n\nSaves the DataPackage to AWS S3.\n\n#### Parameters\n\n- `bucket` - Name of the bucket where DataPackage will be stored (should already be created!)\n- `acl` - ACL to provide the uploaded files. Default is 'public-read' (see [boto3 docs](http://boto3.readthedocs.io/en/latest/reference/services/s3.html#S3.Client.put_object) for more info).\n- `path` - Path (key/prefix) to the DataPackage. May contain format string available for `datapackage.json` Eg: `my/example/path/{owner}/{name}/{version}`\n- `content_type` - content type to use when storing files in S3. Defaults to text/plain (usual S3 default is binary/octet-stream but we prefer text/plain).\n- `endpoint_url` - api endpoint to allow using S3 compatible services (e.g. 'https://ams3.digitaloceanspaces.com')\n\n### change_acl_on_s3\n\nChanges ACL of object in given Bucket with given path aka prefix.\n\n#### Parameters\n\n- `bucket` - Name of the bucket where objects are stored\n- `acl` - Available options `'private'|'public-read'|'public-read-write'|'authenticated-read'|'aws-exec-read'|'bucket-owner-read'|'bucket-owner-full-control'`\n- `path` - Path (key/prefix) to the DataPackage.\n- `endpoint_url` - api endpoint to allow using S3 compatible services (e.g. 'https://ams3.digitaloceanspaces.com')\n\n## Contributing\n\nThe project follows the [Open Knowledge International coding standards](https://github.com/okfn/coding-standards).\n\nThe recommended way to get started is to create and activate a project virtual environment.\nTo install package and development dependencies into your active environment:\n\n```\n$ make install\n```\n\nTo run tests with linting and coverage:\n\n```bash\n$ make test\n```\n\nFor linting, `pylama` (configured in `pylama.ini`) is used. At this stage it's already\ninstalled into your environment and could be used separately with more fine-grained control\nas described in documentation - https://pylama.readthedocs.io/en/latest/.\n\nFor example to sort results by error type:\n\n```bash\n$ pylama --sort <path>\n```\n\nFor testing, `tox` (configured in `tox.ini`) is used.\nIt's already installed into your environment and could be used separately with more fine-grained control as described in documentation - https://testrun.org/tox/latest/.\n\nFor example to check subset of tests against Python 2 environment with increased verbosity.\nAll positional arguments and options after `--` will be passed to `py.test`:\n\n```bash\ntox -e py37 -- -v tests/<path>\n```\n\nUnder the hood `tox` uses `pytest` (configured in `pytest.ini`), `coverage`\nand `mock` packages. These packages are available only in tox envionments.\n\n## Changelog\n\nHere described only breaking and the most important changes. The full changelog and documentation for all released versions can be found in the nicely formatted [commit history](https://github.com/frictionlessdata/dataflows-aws/commits/master).\n\n#### v0.x\n\n- an initial processors implementation\n\n",
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        "keywords": "frictionless data,open data,json schema,table schema,data package,tabular data package",
        "license": "MIT",
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        "name": "dataflows-aws",
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        "summary": "A utility library for working with Table Schema in Python",
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