Metadata-Version: 1.1
Name: fastavro
Version: 0.14.3
Summary: Fast read/write of AVRO files
Home-page: https://github.com/tebeka/fastavro
Author: Miki Tebeka
Author-email: miki.tebeka@gmail.com
License: MIT
Description: fastavro
        ========
        
        **If you're interested in maintaining this package - please drop me a line**
        
        The current Python `avro` package is packed with features but dog slow.
        
        On a test case of about 10K records, it takes about 14sec to iterate over all of
        them. In comparison the JAVA `avro` SDK does it in about 1.9sec.
        
        `fastavro` is less feature complete than `avro`, however it's much faster. It
        iterates over the same 10K records in 2.9sec, and if you use it with PyPy it'll
        do it in 1.5sec (to be fair, the JAVA benchmark is doing some extra JSON
        encoding/decoding).
        
        If the optional C extension (generated by [Cython][cython]) is available, then
        `fastavro` will be even faster. For the same 10K records it'll run in about
        1.7sec.
        
        `fastavro` supports the following Python versions:
        
        * Python 2.6
        * Python 2.7
        * Python 3.4
        * Python 3.5
        * Python 3.6
        * PyPy
        * PyPy3
        
        [Cython]: http://cython.org/
        
        Usage
        =====
        
        Reading
        -------
        
        
        ```python
        
            import fastavro as avro
        
            with open('weather.avro', 'rb') as fo:
                reader = avro.reader(fo)
                schema = reader.schema
        
                for record in reader:
                    process_record(record)
        
        ```
        
        Writing
        -------
        
        ```python
            from fastavro import writer
        
            schema = {
                'doc': 'A weather reading.',
                'name': 'Weather',
                'namespace': 'test',
                'type': 'record',
                'fields': [
                    {'name': 'station', 'type': 'string'},
                    {'name': 'time', 'type': 'long'},
                    {'name': 'temp', 'type': 'int'},
                ],
            }
            
            # 'records' can be any iterable (including a generator)
            records = [
                {u'station': u'011990-99999', u'temp': 0, u'time': 1433269388},
                {u'station': u'011990-99999', u'temp': 22, u'time': 1433270389},
                {u'station': u'011990-99999', u'temp': -11, u'time': 1433273379},
                {u'station': u'012650-99999', u'temp': 111, u'time': 1433275478},
            ]
        
            with open('weather.avro', 'wb') as out:
                writer(out, schema, records)
        
        ```
        
        You can also use the `fastavro` script from the command line to dump `avro`
        files.
        
            fastavro weather.avro
        
        By default fastavro prints one JSON object per line, you can use the `--pretty`
        flag to change this.
        
        You can also dump the avro schema
        
            fastavro --schema weather.avro
        
        
        Here's the full command line help
        
            usage: fastavro [-h] [--schema] [--codecs] [--version] [-p] [file [file ...]]
        
            iter over avro file, emit records as JSON
        
            positional arguments:
              file          file(s) to parse
        
            optional arguments:
              -h, --help    show this help message and exit
              --schema      dump schema instead of records
              --codecs      print supported codecs
              --version     show program's version number and exit
              -p, --pretty  pretty print json
        
        Installing
        ==========
        `fastavro` is available both on [PyPi](http://pypi.python.org/pypi) 
        
            pip install fastavro
        
        and on [conda-forge](https://conda-forge.github.io) `conda` channel.
        
            conda install -c conda-forge fastavro
        
        Limitations
        ===========
        
        * No reader schema
        
        Hacking
        =======
        
        As recommended by Cython, the C files output is distributed. This has the
        advantage that the end user does not need to have Cython installed. However it
        means that every time you change `fastavro/pyfastavro.py` you need to run
        `make`.
        
        For `make` to succeed you need both python and Python 3 installed, Cython on both
        of them. For `./test-install.sh` you'll need [virtualenv][venv].
        
        [venv]: http://pypi.python.org/pypi/virtualenv
        
        Builds
        ======
        
        We're currently using [travis.ci](http://travis-ci.org/#!/tebeka/fastavro)
        
        [![Build Status](https://travis-ci.org/tebeka/fastavro.svg?branch=master)](https://travis-ci.org/tebeka/fastavro)
        
        
        Changes
        =======
        
        See the [ChangeLog]
        
        [ChangeLog]: https://github.com/tebeka/fastavro/blob/master/ChangeLog
        
        Contact
        =======
        
        [Project Home](https://github.com/tebeka/fastavro)
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
