laywerrobot/lib/python3.6/site-packages/smart_open-1.6.0.dist-info/METADATA

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Metadata-Version: 2.1
Name: smart-open
Version: 1.6.0
Summary: Utils for streaming large files (S3, HDFS, gzip, bz2...)
Home-page: https://github.com/piskvorky/smart_open
Author: Radim Rehurek
Author-email: me@radimrehurek.com
Maintainer: Radim Rehurek
Maintainer-email: me@radimrehurek.com
License: MIT
Download-URL: http://pypi.python.org/pypi/smart_open
Keywords: file streaming,s3,hdfs
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: Database :: Front-Ends
Provides-Extra: test
Requires-Dist: boto (>=2.32)
Requires-Dist: bz2file
Requires-Dist: requests
Requires-Dist: boto3
Provides-Extra: test
Requires-Dist: mock; extra == 'test'
Requires-Dist: moto (==0.4.31); extra == 'test'
Requires-Dist: pathlib2; extra == 'test'
Requires-Dist: responses; extra == 'test'
=============================================
smart_open -- utils for streaming large files
=============================================
|License|_ |Travis|_
.. |License| image:: https://img.shields.io/pypi/l/smart_open.svg
.. |Travis| image:: https://travis-ci.org/RaRe-Technologies/smart_open.svg?branch=master
.. _Travis: https://travis-ci.org/RaRe-Technologies/smart_open
.. _License: https://github.com/RaRe-Technologies/smart_open/blob/master/LICENSE
What?
=====
``smart_open`` is a Python 2 & Python 3 library for **efficient streaming of very large files** from/to S3, HDFS, WebHDFS, HTTP, or local (compressed) files.
It is well tested (using `moto <https://github.com/spulec/moto>`_), well documented and sports a simple, Pythonic API:
.. code-block:: python
>>> # stream lines from an S3 object
>>> for line in smart_open.smart_open('s3://mybucket/mykey.txt'):
... print line
>>> # using a completely custom s3 server, like s3proxy:
>>> for line in smart_open.smart_open('s3u://user:secret@host:port@mybucket/mykey.txt'):
... print line
>>> # you can also use a boto.s3.key.Key instance directly:
>>> key = boto.connect_s3().get_bucket("my_bucket").get_key("my_key")
>>> with smart_open.smart_open(key) as fin:
... for line in fin:
... print line
>>> # can use context managers too:
>>> with smart_open.smart_open('s3://mybucket/mykey.txt') as fin:
... for line in fin:
... print line
... fin.seek(0) # seek to the beginning
... print fin.read(1000) # read 1000 bytes
>>> # stream from HDFS
>>> for line in smart_open.smart_open('hdfs://user/hadoop/my_file.txt'):
... print line
>>> # stream from HTTP
>>> for line in smart_open.smart_open('http://example.com/index.html'):
... print line
>>> # stream from WebHDFS
>>> for line in smart_open.smart_open('webhdfs://host:port/user/hadoop/my_file.txt'):
... print line
>>> # stream content *into* S3 (write mode):
>>> with smart_open.smart_open('s3://mybucket/mykey.txt', 'wb') as fout:
... for line in ['first line', 'second line', 'third line']:
... fout.write(line + '\n')
>>> # stream content *into* HDFS (write mode):
>>> with smart_open.smart_open('hdfs://host:port/user/hadoop/my_file.txt', 'wb') as fout:
... for line in ['first line', 'second line', 'third line']:
... fout.write(line + '\n')
>>> # stream content *into* WebHDFS (write mode):
>>> with smart_open.smart_open('webhdfs://host:port/user/hadoop/my_file.txt', 'wb') as fout:
... for line in ['first line', 'second line', 'third line']:
... fout.write(line + '\n')
>>> # stream from/to local compressed files:
>>> for line in smart_open.smart_open('./foo.txt.gz'):
... print line
>>> with smart_open.smart_open('/home/radim/foo.txt.bz2', 'wb') as fout:
... fout.write("some content\n")
Since going over all (or select) keys in an S3 bucket is a very common operation,
there's also an extra method ``smart_open.s3_iter_bucket()`` that does this efficiently,
**processing the bucket keys in parallel** (using multiprocessing):
.. code-block:: python
>>> # get all JSON files under "mybucket/foo/"
>>> bucket = boto.connect_s3().get_bucket('mybucket')
>>> for key, content in s3_iter_bucket(bucket, prefix='foo/', accept_key=lambda key: key.endswith('.json')):
... print key, len(content)
For more info (S3 credentials in URI, minimum S3 part size...) and full method signatures, check out the API docs:
.. code-block:: python
>>> import smart_open
>>> help(smart_open.smart_open_lib)
S3-Specific Options
-------------------
There are a few optional keyword arguments that are useful only for S3 access.
The **host** and **profile** arguments are both passed to `boto.s3_connect()` as keyword arguments:
.. code-block:: python
>>> smart_open.smart_open('s3://', host='s3.amazonaws.com')
>>> smart_open.smart_open('s3://', profile_name='my-profile')
The **s3_session** argument allows you to provide a custom `boto3.Session` instance for connecting to S3:
.. code-block:: python
>>> smart_open.smart_open('s3://', s3_session=boto3.Session())
The **s3_upload** argument accepts a dict of any parameters accepted by `initiate_multipart_upload <https://boto3.readthedocs.io/en/latest/reference/services/s3.html#S3.ObjectSummary.initiate_multipart_upload/>`_:
.. code-block:: python
>>> smart_open.smart_open('s3://', s3_upload={ 'ServerSideEncryption': 'AES256' })
The S3 reader supports gzipped content, as long as the key is obviously a gzipped file (e.g. ends with ".gz").
Why?
----
Working with large S3 files using Amazon's default Python library, `boto <http://docs.pythonboto.org/en/latest/>`_, is a pain. Its ``key.set_contents_from_string()`` and ``key.get_contents_as_string()`` methods only work for small files (loaded in RAM, no streaming).
There are nasty hidden gotchas when using ``boto``'s multipart upload functionality, and a lot of boilerplate.
``smart_open`` shields you from that. It builds on boto but offers a cleaner API. The result is less code for you to write and fewer bugs to make.
Installation
------------
::
pip install smart_open
Or, if you prefer to install from the `source tar.gz <http://pypi.python.org/pypi/smart_open>`_::
python setup.py test # run unit tests
python setup.py install
To run the unit tests (optional), you'll also need to install `mock <https://pypi.python.org/pypi/mock>`_ , `moto <https://github.com/spulec/moto>`_ and `responses <https://github.com/getsentry/responses>` (``pip install mock moto responses``). The tests are also run automatically with `Travis CI <https://travis-ci.org/RaRe-Technologies/smart_open>`_ on every commit push & pull request.
Todo
----
``smart_open`` is an ongoing effort. Suggestions, pull request and improvements welcome!
On the roadmap:
* better documentation for the default ``file://`` scheme
Comments, bug reports
---------------------
``smart_open`` lives on `github <https://github.com/RaRe-Technologies/smart_open>`_. You can file
issues or pull requests there.
----------------
``smart_open`` is open source software released under the `MIT license <https://github.com/piskvorky/smart_open/blob/master/LICENSE>`_.
Copyright (c) 2015-now `Radim Řehůřek <http://radimrehurek.com>`_.