{ "info": { "author": "Fitchain", "author_email": "hello@fitchain.io", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Topic :: Utilities" ], "description": "### What is this repository for? ###\n\n* python based SDK \n* v0.1\n\nThis repo implements the SDK to manage projects and models on a local fitchain pod\n\n### Feedback ###\nReach out and tell us how we can improve this SDK to make it easier for you to work with the pod and build your models.\n\nYou may always drop us a mail at ``` code@fitchain.io ```\n\n\n### Getting Started ###\n#### Prequisites\n\nCreate a virtual environment\n\n``` virtualenv -p python3 venv ```\n\n``` . venv/bin/activate ```\n\nand install all requirements in it\n\n```pip3 install -r requirements.txt```\n\nfrom this virtualenv run the code submitted by data scientist as in\n\n```python ../../fitchain/machine-learning-models/mlp-reuters/train_mlp.py```\n\n\nMake sure libmagic is installed:\n\n```\nbrew install libmagic\n```\n\n####Fitchain sdk\n\nFirst install the fitchain sdk using pip:\n```bash\npip install fitchain\n```\n\nOnce the fitchain sdk has been installed, you can use the library:\n\n```python\nfrom fitchain import Runtime\n\nfc = Runtime()\n```\n\nCall the ```projects()``` method to get an overview of all available projects. You may even enter a query string to\nfilter your results.\n\n```python\nprojects = fc.projects()\n```\n\nOnce a project has been chosen, the datasources linked to the project can be retrieved using the ```datasources``` property\n\n```python\nproject = projects[...]\nproject_datasources = project.datasources\n```\n\nData for a specific datasource can be loaded by calling the ``` load(