Metadata-Version: 1.1
Name: smart_open
Version: 1.3.4
Summary: Utils for streaming large files (S3, HDFS, gzip, bz2...)
Home-page: https://github.com/piskvorky/smart_open
Author: Radim Řehůřek
Author-email: me@radimrehurek.com
License: MIT
Download-URL: http://pypi.python.org/pypi/smart_open
Description: =============================================
        smart_open -- utils for streaming large files
        =============================================
        
        |Travis|_
        |License|_
        
        .. |Travis| image:: https://img.shields.io/travis/RaRe-Technologies/smart_open/master.svg
        .. |License| image:: https://img.shields.io/pypi/l/smart_open.svg
        .. _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 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
        
          >>> # 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 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* 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
        
          >>> 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.
        
        .. code-block:: python
        
          >>> smart_open.smart_open('s3://', host='s3.amazonaws.com')
          >>> smart_open.smart_open('s3://', profile_name='my-profile')
        
        These are both passed to `boto.s3_connect()` as keyword arguments.
        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
        ------------
        
        The module has no dependencies beyond Python >= 2.6 (or Python >= 3.3),
        ``boto`` and ``requests``::
        
            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>`_.
        
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 :: 2.6
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: Topic :: System :: Distributed Computing
Classifier: Topic :: Database :: Front-Ends
