Metadata-Version: 1.0
Name: s3peat
Version: 0.4.7
Summary: Fast uploader to S3
Home-page: http://github.com/shakefu/s3peat
Author: Jacob Alheid
Author-email: jake@about.me
License: UNKNOWN
Description: s3peat
        ======
        
        s3peat is a Python module to help upload directories to S3 using parallel
        threads.
        
        The source is hosted at `<http://github.com/shakefu/s3peat/>`_.
        
        .. image:: http://shakefu.s3.amazonaws.com/s3peat/s3peat.jpg
        
        
        Installing
        ----------
        
        s3peat can be installed from PyPI to get the latest release. If you'd like
        development code, you can check out the git repo.
        
        .. code-block:: bash
        
           # Install from PyPI
           $ pip install s3peat
        
           # Install from GitHub
           $ git clone http://github.com/shakefu/s3peat.git
           $ cd s3peat
           $ python setup.py install
        
        Command line usage
        ------------------
        
        When installed via ``pip`` or ``python setup.py install``, a command called
        ``s3peat`` will be added. This command can be used to upload files easily.
        
        .. code-block:: text
        
           $ s3peat --help
           usage: s3peat [--prefix] --bucket [--key] [--secret] [--concurrency]
                 [--exclude] [--include] [--dry-run] [--verbose] [--version]
                 [--help] directory
        
           positional arguments:
             directory            directory to be uploaded
        
           optional arguments:
             --prefix , -p        s3 key prefix
             --bucket , -b        s3 bucket name
             --key , -k           AWS key id
             --secret , -s        AWS secret
             --concurrency , -c   number of threads to use
             --exclude , -e       exclusion regex
             --include , -i       inclusion regex
             --private, -r        do not set ACL public
             --dry-run, -d        print files matched and exit, do not upload
             --verbose, -v        increase verbosity (-vvv means more verbose)
             --version            show program's version number and exit
             --help               display this help and exit
        
        **Example**:
        
        .. code-block:: bash
        
           $ s3peat -b my/bucket -p my/s3/key/prefix -k KEY -s SECRET my-dir/
        
        Configuring
        """""""""""
        
        This library is based around `boto <http://docs.pythonboto.org/>`_. Your *AWS
        Access Key Id* and *AWS Secret Access Key* do not have to be passed on the
        command line - they may be configured using any method that boto supports,
        including environment variables and the ``~/.boto`` config..
        
        **Example using environment variables**:
        
        .. code-block:: bash
        
           $ export AWS_ACCESS_KEY_ID=ABCDEFabcdef01234567
           $ export AWS_SECRET_ACCESS_KEY=ABCDEFabcdef0123456789ABCDEFabcdef012345
           $ s3peat -b my/bucket -p s3/prefix -c 25 some_dir/
        
        **Example ``~/.boto`` config**:
        
        .. code-block:: config
        
           # File: ~/.boto
           [Credentials]
           aws_access_key_id = ABCDEFabcdef01234567
           aws_secret_access_key = ABCDEFabcdef0123456789ABCDEFabcdef012345
        
        
        Including and excluding files
        """""""""""""""""""""""""""""
        
        Using the ``--include`` and ``--exclude`` (``-i`` or ``-e``) parameters, you
        can specify regex patterns to include or exclude from the list of files to be
        uploaded.
        
        These regexes are Python regexes, as applied by ``re.search()``, so if you want
        to match the beginning or end of a filename (including the directory), make
        sure to use the ``^`` or ``$`` metacharacters.
        
        These parameters can be specified multiple times, for example:
        
        .. code-block:: bash
        
           # Upload all .txt and .py files, excluding the test directory
           $ s3peat -b my-bucket -i '.txt$' -i '.py$' -e '^test/' .
        
        Doing a Dry-run
        """""""""""""""
        
        If you're unsure what exactly is in the directory to be uploaded, you can do a
        dry run with the ``--dry-run`` or ``-d`` option.
        
        By default, dry runs only output the number of files found and an error message
        if it cannot connect to the specified S3 bucket. As you increase verbosity,
        more information will be output. See below for examples.
        
        .. code-block:: bash
        
           $ s3peat -b my-bucket . -e '\.git' --dry-run
           21 files found.
        
           $ s3peat -b foo . -e '\.git' --dry-run
           21 files found.
           Error connecting to S3 bucket 'foo'.
        
           $ s3peat -b my-bucket . -e '\.git' --dry-run -v
           21 files found.
           Connected to S3 bucket 'my-bucket' OK.
        
           $ s3peat -b foo . -e '\.git' --dry-run -v
           21 files found.
           Error connecting to S3 bucket 'foo'.
               S3ResponseError: 403 Forbidden
        
           $ s3peat -b my-bucket . -i 'rst$|py$|LICENSE' --dry-run
           5 files found.
        
           $ s3peat -b my-bucket . -i 'rst$|py$|LICENSE' --dry-run -vv
           Finding files in /home/s3peat/github.com/s3peat ...
        
           ./LICENSE
           ./README.rst
           ./setup.py
           ./s3peat/__init__.py
           ./s3peat/scripts.py
        
           5 files found.
        
           Connected to S3 bucket 'my-bucket' OK.
        
        Concurrency
        """""""""""
        
        s3peat is designed to upload to S3 with high concurrency. The only limits are
        the speed of your uplink and the GIL. Python is limited in the number of
        threads that will run concurrently on a single core.
        
        Typically, it seems that more than 50 threads do not add anything to the upload
        speed, but your experiences may differ based on your network and CPU speeds.
        
        If you want to try to tune your concurrency for your platfrom, I suggest using
        the ``time`` command.
        
        **Example**:
        
        .. code-block:: bash
        
           $ time s3peat -b my-bucket -p my/key/ --concurrency 50 my-dir/
           271/271 files uploaded                                                                                                                                                                                                                           
        
           real	0m2.909s
           user	0m0.488s
           sys	0m0.114s
        
        Python API
        ----------
        
        The Python API has inline documentation, which should be good. If there's
        questions, you can open a github issue. Here's an example anyway.
        
        **Example**:
        
        .. code-block:: python
        
            from s3peat import S3Bucket, sync_to_s3
        
            # Create a S3Bucket instance, which is used to create connections to S3
            bucket = S3Bucket('my-bucket', AWS_KEY, AWS_SECRET)
        
            # Call the sync_to_s3 method
            failures = sync_to_s3(directory='my/directory', prefix='my/key',
                bucket=bucket, concurrency=50)
        
            # A list of filenames will be returned if there were failures in uploading
            if not failures:
                print "No failures"
            else:
                print "Failed:", failures
        
        
        Changelog
        ---------
        
        0.4.7
        -----
        
        * Better support for Windows. Thanks to `kevinschaul
          <https://github.com/kevinschaul>`_.
        
        *Released November 20th, 2014*.
        
        Contributors
        ------------
        
        * `shakefu <http://github.com/shakefu>`_ - Creator, maintainer
        * `kevinschaul <https://github.com/kevinschaul>`_
        
        
Platform: UNKNOWN
