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https://github.com/jcrobak/parquet-python
python implementation of the parquet columnar file format.
https://github.com/jcrobak/parquet-python
Last synced: 12 days ago
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python implementation of the parquet columnar file format.
- Host: GitHub
- URL: https://github.com/jcrobak/parquet-python
- Owner: jcrobak
- License: apache-2.0
- Created: 2013-09-02T19:17:29.000Z (about 11 years ago)
- Default Branch: master
- Last Pushed: 2021-10-26T04:40:11.000Z (about 3 years ago)
- Last Synced: 2024-10-01T18:06:29.949Z (about 1 month ago)
- Language: Python
- Size: 156 KB
- Stars: 335
- Watchers: 11
- Forks: 256
- Open Issues: 15
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
parquet-python
==============.. image:: https://travis-ci.org/jcrobak/parquet-python.svg?branch=master
:target: https://travis-ci.org/jcrobak/parquet-pythonparquet-python is a pure-python implementation (currently with only
read-support) of the `parquet
format `_. It comes with a
script for reading parquet files and outputting the data to stdout as
JSON or TSV (without the overhead of JVM startup). Performance has not
yet been optimized, but it's useful for debugging and quick viewing of
data in files.Not all parts of the parquet-format have been implemented yet or tested
e.g. nested data—see Todos below for a full list. With that said,
parquet-python is capable of reading all the data files from the
`parquet-compatability `_
project.requirements
============parquet-python has been tested on python 2.7, 3.6, and 3.7. It depends
on ``pythrift2`` and optionally on ``python-snappy`` (for snappy compressed
files, please also install ``parquet-python[snappy]``).getting started
===============parquet-python is available via PyPi and can be installed using
`pip install parquet`. The package includes the `parquet`
command for reading python files, e.g. `parquet test.parquet`.
See `parquet --help` for full usage.Example
-------parquet-python currently has two programatic interfaces with similar
functionality to Python's csv reader. First, it supports a DictReader
which returns a dictionary per row. Second, it has a reader which
returns a list of values for each row. Both function require a file-like
object and support an optional ``columns`` field to only read the
specified columns... code:: python
import parquet
import json## assuming parquet file with two rows and three columns:
## foo bar baz
## 1 2 3
## 4 5 6with open("test.parquet", "rb") as fo:
# prints:
# {"foo": 1, "bar": 2}
# {"foo": 4, "bar": 5}
for row in parquet.DictReader(fo, columns=['foo', 'bar']):
print(json.dumps(row))with open("test.parquet", "rb") as fo:
# prints:
# 1,2
# 4,5
for row in parquet.reader(fo, columns=['foo', 'bar']):
print(",".join([str(r) for r in row]))Todos
=====- Support the deprecated bitpacking
- Fix handling of repetition-levels and definition-levels
- Tests for nested schemas, null data
- Support reading of data from HDFS via snakebite and/or webhdfs.
- Implement writing
- performance evaluation and optimization (i.e. how does it compare to
the c++, java implementations)Contributing
============Is done via Pull Requests. Please include tests with your changes and
follow `pep8 `_.To run the tests you must install and execute ``tox`` (``pip install tox``) to
run for all supported versions. If you want to run just for your current
version, execute: ``pip install -r requirements-development.txt`` and then
``nosetests``.