Skip to main content

Fast read/write of AVRO files

Project description

fastavro
========

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 3.5b2
* 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 = [
{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


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)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fastavro-0.9.8.tar.gz (283.5 kB view details)

Uploaded Source

Built Distributions

fastavro-0.9.8-py3.5-linux-x86_64.egg (714.4 kB view details)

Uploaded Source

fastavro-0.9.8-py2.7-linux-x86_64.egg (236.6 kB view details)

Uploaded Source

File details

Details for the file fastavro-0.9.8.tar.gz.

File metadata

  • Download URL: fastavro-0.9.8.tar.gz
  • Upload date:
  • Size: 283.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for fastavro-0.9.8.tar.gz
Algorithm Hash digest
SHA256 d6404f006e5b734021baed993c957ba12e98ef330a07ad9075c221738567f0cb
MD5 af74d03d1fd3a2384ca655e08650ce76
BLAKE2b-256 7d914e0c766e49f2dfbfbb726b97aa29a8e3a0daefc53683e4c03251ce9ea3b2

See more details on using hashes here.

File details

Details for the file fastavro-0.9.8-py3.5-linux-x86_64.egg.

File metadata

File hashes

Hashes for fastavro-0.9.8-py3.5-linux-x86_64.egg
Algorithm Hash digest
SHA256 d452e49a753739758652ecfee06c8238b46787421c67ff534000f02774df02e2
MD5 450c9b22b38fda1d983e9b82ebc3e2d5
BLAKE2b-256 9bbec88bf82ece9c90a2011f765d23a8d2d4468caa320a098da67ce3ea4f09bd

See more details on using hashes here.

File details

Details for the file fastavro-0.9.8-py2.7-linux-x86_64.egg.

File metadata

File hashes

Hashes for fastavro-0.9.8-py2.7-linux-x86_64.egg
Algorithm Hash digest
SHA256 904f79e94d12a8f239822a89d412c0f3fb8351f202e73cfd203abfb390b9fd6d
MD5 4b7ada6ead697218f12f92f6731ee209
BLAKE2b-256 96ffc1639e6ab808461933277b9b65e7eb3223ebc2f12061bafdc02cbac967b9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page