Metadata-Version: 2.1
Name: smart-open
Version: 1.7.1
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
Description: ======================================================
        smart_open — utils for streaming large files in Python
        ======================================================
        
        |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's a drop-in replacement for Python's built-in ``open()``: it can do anything ``open`` can (100% compatible, falls back to native ``open`` wherever possible), plus lots of nifty extra stuff on top.
        
        ``smart_open`` is well-tested, well-documented and sports a simple, Pythonic API:
        
        .. code-block:: python
        
          >>> from smart_open import smart_open
        
          >>> # stream lines from an S3 object
          >>> for line in smart_open('s3://mybucket/mykey.txt', 'rb'):
          ...    print(line.decode('utf8'))
        
          >>> # stream from/to compressed files, with transparent (de)compression:
          >>> for line in smart_open('./foo.txt.gz', encoding='utf8'):
          ...    print(line)
        
          >>> # can use context managers too:
          >>> with smart_open('/home/radim/foo.txt.bz2', 'wb') as fout:
          ...    fout.write(u"some content\n".encode('utf8'))
        
          >>> with smart_open('s3://mybucket/mykey.txt', 'rb') as fin:
          ...     for line in fin:
          ...         print(line.decode('utf8'))
          ...     fin.seek(0)  # seek to the beginning
          ...     b1000 = fin.read(1000)  # read 1000 bytes
        
          >>> # stream from HDFS
          >>> for line in smart_open('hdfs://user/hadoop/my_file.txt', encoding='utf8'):
          ...     print(line)
        
          >>> # stream from HTTP
          >>> for line in smart_open('http://example.com/index.html'):
          ...     print(line)
        
          >>> # stream from WebHDFS
          >>> for line in smart_open('webhdfs://host:port/user/hadoop/my_file.txt'):
          ...     print(line)
        
          >>> # stream content *into* S3 (write mode):
          >>> with smart_open('s3://mybucket/mykey.txt', 'wb') as fout:
          ...     for line in [b'first line\n', b'second line\n', b'third line\n']:
          ...          fout.write(line)
        
          >>> # stream content *into* HDFS (write mode):
          >>> with smart_open('hdfs://host:port/user/hadoop/my_file.txt', 'wb') as fout:
          ...     for line in [b'first line\n', b'second line\n', b'third line\n']:
          ...          fout.write(line)
        
          >>> # stream content *into* WebHDFS (write mode):
          >>> with smart_open('webhdfs://host:port/user/hadoop/my_file.txt', 'wb') as fout:
          ...     for line in [b'first line\n', b'second line\n', b'third line\n']:
          ...          fout.write(line)
        
          >>> # stream using a completely custom s3 server, like s3proxy:
          >>> for line in smart_open('s3u://user:secret@host:port@mybucket/mykey.txt', 'rb'):
          ...    print(line.decode('utf8'))
        
          >>> # 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(key, 'rb') as fin:
          ...     for line in fin:
          ...         print(line.decode('utf8'))
        
        
        Why?
        ----
        
        Working with large S3 files using Amazon's default Python library, `boto <http://docs.pythonboto.org/en/latest/>`_ and `boto3 <https://boto3.readthedocs.io/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 that is needed for large files, and a lot of boilerplate.
        
        ``smart_open`` shields you from that. It builds on boto3 but offers a cleaner, Pythonic 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.
        
        S3-Specific Options
        -------------------
        
        The S3 reader supports gzipped content transparently, as long as the key is obviously a gzipped file (e.g. ends with ".gz").
        
        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('s3://', host='s3.amazonaws.com')
          >>> 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('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('s3://', s3_upload={ 'ServerSideEncryption': 'AES256' })
        
        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
        
          >>> from smart_open import smart_open, s3_iter_bucket
          >>> # 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)
        
        
        Comments, bug reports
        ---------------------
        
        ``smart_open`` lives on `Github <https://github.com/RaRe-Technologies/smart_open>`_. You can file
        issues or pull requests there. Suggestions, pull requests and improvements welcome!
        
        ----------------
        
        ``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 <https://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 :: 2.7
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
