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        "description": "# Intake-avro\n\n[![Build Status](https://travis-ci.org/ContinuumIO/intake-avro.svg?branch=master)](https://travis-ci.org/ContinuumIO/intake-avro)\n[![Documentation Status](https://readthedocs.org/projects/intake-avro/badge/?version=latest)](http://intake-avro.readthedocs.io/en/latest/?badge=latest)\n\nThe [Apache Avro](https://avro.apache.org/) format is a popular method for information\nexchange, particularly for message and reord distribution in high-throughput systems.\n\nIn [Intake](https://github.com/ContinuumIO/intake/), there are two plugins provided for reading avro data:\n\n- `avro_table` is appropriate for data which have a schema simple enough to be\n  represented as columns with simple types, i.e., *flat* schema. The output of\n  this plugin are dataframes, and the reading is optimized for speed.\n- `avro_sequence` is more generic and can handle all possible avro schema, but\n  it produces generic python sequences of dictionaries, and is consequently\n  much slower than the table reader.\n\n### Installation\n\nThe conda install instructions are:\n\n```\nconda install -c conda-forge fastavro uavro\nconda install -c intake intake_avro\n```\n\n### Examples\n\nSee the notebook in the examples/ directory.",
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