Metadata-Version: 1.1
Name: fastavro
Version: 0.17.8
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-Content-Type: UNKNOWN
Description: # fastavro
        [![Build Status](https://travis-ci.org/tebeka/fastavro.svg?branch=master)](https://travis-ci.org/tebeka/fastavro)
        
        Because the Apache Python `avro` package is written in pure Python, it is
        relatively slow. In one test case, it takes about 14 seconds to iterate through
        a file of 10,000. By comparison, the JAVA `avro` SDK reads the same file in
        1.9 seconds.
        
        The `fastavro` library was written to offer performance comparable to the Java
        library. With regular CPython, `fastavro` uses C extensions which allow it to
        iterate the same 10,000 record file in 1.7 seconds. With PyPy, this drops to 1.5
        seconds (to be fair, the JAVA benchmark is doing some extra JSON
        encoding/decoding).
        
        `fastavro` supports the following Python versions:
        
        * 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)
        ```
        
        You may also explicitly specify reader schema to perform schema validation:
        
        ```python
        import fastavro as avro
        
        schema = {
            'doc': 'A weather reading.',
            'name': 'Weather',
            'namespace': 'test',
            'type': 'record',
            'fields': [
                {'name': 'station', 'type': 'string'},
                {'name': 'time', 'type': 'long'},
                {'name': 'temp', 'type': 'int'},
            ],
        }
        
        
        with open('weather.avro', 'rb') as fo:
            reader = avro.reader(fo, reader_schema=schema)
        
            # will raise a fastavro.reader.SchemaResolutionError in case of
            # incompatible 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
        
        # 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
        
        ### Releasing
        
        We release both to [pypi][pypi] and to [conda-forge][conda-forge].
        
        We assume you have [twine][twine] installed and that you've created your own
        fork of [fastavro-feedstock][feedstock].
        
        * Make sure the tests pass
        * Copy the windows build artifacts for the new version from
          https://ci.appveyor.com/project/scottbelden/fastavro to the `dist` folder
        * Run `make publish`
        * Note the sha signature emitted at the above
        * Switch to feedstock directory and edit `recipe/meta.yaml`
            - Update `version` and `sha256` variables at the top of the file
            - Run `python recipe/test_recipe.py`
            - Submit a [PR][pr]
        
        [conda-forge]: https://conda-forge.org/
        [feedstock]: https://github.com/conda-forge/fastavro-feedstock
        [pr]: https://conda-forge.org/#update_recipe
        [pypi]: https://pypi.python.org/pypi
        [twine]: https://pypi.python.org/pypi/twine
        
        
        # 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 :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Scientific/Engineering :: Information Analysis
