ramp up time metric, __init__ files created, readme updated, requirements.txt updated. #17
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treats src as a python package, allowing for importing of submodules
allows for metrics to be a submodule of src, allowing dynamic loader in run file to import metric files
We operationalized ramp-up time as the ease with which a new user can begin using a model. We approximate this using README features: documentation length (up to 0.4 points), presence of an installation section (0.35 points), and presence of runnable code snippets (0.25 points). We weighted installation most heavily, followed by code snippets, since these are the strongest indicators of quick onboarding. Length alone is insufficient and is weighted least
requests install allows for remote README fetch, essentially, try to grab the README file straight from GitHub/Hugging Face over the internet if no local copy exists
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install pytest in your directory with the project. create a venv in that same directory and then run the run script like normal "python run.py test". number of cases passed is still harcoded to be x/y but the percentage updates acccordingly.
accidental additional init file
instructs pytest to always use python path as src
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ramp up time metric created. testing notes are available in my chatgpt converstation. see readme for how it works/requirements satisfied. unsure of how well the actual metric will work at large scale due to how each repo is checked (local cloning vs remote pulling)