DecentralML Python client

The python client offers an interface to access the functionalities of the DecentraML node throught scripts.

└── decentralml
    ├── __init__.py
    ├── assign_task.py
    ├── create_task.py
    ├── examples.py
    ├── main.py
    ├── script.py
    ├── send_task_result.py
    ├── settings.py
    ├── storage_ipfs.py
    └── utilities.py

There are several python scripts that correlate to create_task, assign_task, send_task_result, validate_task_result, accept_task_result, reject_task_result, list_tasks, list_task_results which allows interaction with Substrate DecentralML node and custom pallets.

The scripts correspond to the task described Insert gitbook link here.

The client exposes and provides methods to communicate to fund actors involved and execute several tasks on the node.

To use the client, the best method is to use the docker container following the instruction here.

Installation and local testing

NOTE The docker containers are the advised method of testing. If you decide to test locally on your own machine, please be advised that some errors might occur and that some adjustments might be needed to the following commands, according to your system.

Python (version >= 3.10), pip and poetry packages are required to run the script.

• Install python https://www.datacamp.com/blog/how-to-install-python

• Install pip https://pip.pypa.io/en/stable/installation/

Then, after cloning the repository, switch to the decentraml/substrate-client-decentralml directory.

cd DecentralML/substrate-client-decentralml/

Create a python environment:

python -m venv .venv

Activate the environment:

source .venv/bin/activate

After that, install poetry with:

pip install poetry

Poetry is a python packaging and dependencies management system that facilitate the installation of python code as packages. More info can be found at https://python-poetry.org/docs/.

Then install the client with:

poetry install

After this, making sure that a node is running, either with a docker or locally on the machine, you can run the examples with the following command:

python -m decentralml.examples

Or you can launch the main menu for each role:

python -m decentralml.main

NOTE If you run the client locally (NOT in the docker), make sure that you place your shell in the root directory of the project. This is required for the assets folder to be found at substrate-client-decentralml/assets

Any other script can be run as part of the module decentralml with:

python -m decentralml.xxxx

where xxxx is one of the script in the module.