A tool to intercept dataflows
Project description
Flowcept
Development Environment
Read the Contributing file.
Code Formatting
Flowcept code uses Black, a PEP 8 compliant code formatter, and Flake8, a code style guide enforcement tool. To install the these tools you simply need to run the following:
$ pip install flake8 black
Before every commit, you should run the following:
$ black .
$ flake8 .
If errors are reported by flake8, please fix them before commiting the code.
Running Tests
There are a few dependencies that need to be installed to run the pytest, if you installed the requirements.txt file then this should be covered as well.
$ pip install pytest
From the root directory using pytest we can run:
$ pytest
Redis Server for the Interception Messages
$ docker run -p 6379:6379 --name flowcept_redis -d redis
Redis Server for the local cache
$ docker run -p 60379:6379 --name local_interceptor_cache -d redis
MongoDB
$ docker run --name mongo -d -p 27017:27017 mongo
Plugins-specific info
You can run pip install flowcept[plugin_name] to install requirements for a specific plugin, instead of installing the
whole package.
RabbitMQ for Zambeze plugin
$ docker run -it --rm --name rabbitmq -d -p 5672:5672 -p 15672:15672 rabbitmq:3.11-management
Tensorboard
If you're on mac, pip install may not work out of the box because of Tensorflow library.
You may need to pip install tensorflow-macos instead of the tensorflow lib available in the tensorboard-requirements.
See also
Release history Release notifications | RSS feed
Download files
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Source Distribution
Built Distribution
Hashes for flowcept-0.0.131-py3-none-any.whl
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| BLAKE2b-256 | 94a51615b1f0600cd25767d2be358704224be28e0eafba703591e02804235a09 |
