flowcept 0.0.123

A tool to intercept dataflows

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

• Zambeze Repository