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redisai-py is the Python client for RedisAI. Checkout the documentation for API details and examples

Installation

  1. Install Redis 5.0 or above

  2. Install RedisAI

  3. Install the Python client

$ pip install redisai
  1. Install serialization-deserialization utility (optional)

$ pip install ml2rt

Development

  1. Assuming you have virtualenv installed, create a virtualenv to manage your python dependencies, and activate it. `virtualenv -v venv; source venv/bin/activate`

  2. Install [pypoetry](https://python-poetry.org/) to manage your dependencies. `pip install poetry`

  3. Install dependencies. `poetry install --no-root`

[tox](https://tox.readthedocs.io/en/latest/) runs all tests as its default target. Running tox by itself will run unit tests. Ensure you have a running redis, with the module loaded.

Contributing

Prior to submitting a pull request, please ensure you’ve built and installed poetry as above. Then:

  1. Run the linter. `tox -e linters.`

  2. Run the unit tests. This assumes you have a redis server running, with the [RedisAI module](https://redisai.io) already loaded. If you don’t, you may want to install a [docker build](https://hub.docker.com/r/redislabs/redisai/tags). `tox -e tests`

RedisAI example repo shows few examples made using redisai-py under python_client folder. Also, checkout ml2rt for convenient functions those might help in converting models (sparkml, sklearn, xgboost to ONNX), serializing models to disk, loading it back to redisai-py etc.

Release files for redisai 1.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for redisai 1.3.0
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Table of built distributions (wheels) for redisai 1.3.0
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redisai-1.3.0-py3-none-any.whl Python 3 none any Details

Total release size: 32.8 kB

Release files / redisai-1.3.0.tar.gz

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