osos.osos.Osos

class Osos(git_owner, git_repo, pypi_name=None, conda_org=None, conda_name=None)

Bases: object

Base class to handle open source ops and statistics (osos) for a given repo/package.

Parameters:

• git_owner (str) – Github repository owner, e.g. https://github.com/{owner}/{repo}. Case insensitive.

• git_repo (str) – Github repository name, e.g. https://github.com/{owner}/{repo}. Case insensitive.

• pypi_name (str | None) – pypi package name. Note that this should include the prefix for nrel packages e.g. reV -> nrel-rev. This can be None if there is no pypi package. Case insensitive.

• conda_org (str) – Conda organization name, for example: https://anaconda.org/{org}/{name}. Case insensitive.

• conda_name (str) – Conda package name, for example: https://anaconda.org/{org}/{name}. Case insensitive.

Methods

clean_table(table)	Fill nan values and make sure the timeseries index has 14 days.
make_table()	Make the usage and statistics table for the last two weeks.
run_config(config)	Run multiple osos jobs from a csv config.
update(fpath_out)	Update and save the fpath_out file.

clean_table(table)

Fill nan values and make sure the timeseries index has 14 days.

Parameters:

table (pd.DataFrame) – Repository usage and statistics table with datetime.date index for the last two weeks including today and columns for various github and pypi usage metrics.

Returns:

table (pd.DataFrame) – Repository usage and statistics table with datetime.date index for the last two weeks including today and columns for various github and pypi usage metrics.

make_table()

Make the usage and statistics table for the last two weeks.

Returns:

table (pd.DataFrame) – Repository usage and statistics table with datetime.date index for the last two weeks including today and columns for various github and pypi usage metrics.

update(fpath_out)

Update and save the fpath_out file. The current update data will be used if there are duplicates.

Parameters:

fpath_out (str) – Output file to save the osos output table. If the file exists, it will be updated with the latest data. This path can include the keywords “DATA_DIR” and “NAME” which will get replaced by the system location of the /osos/data/ directory and the github repo name, respectively.

Returns:

table (pd.DataFrame) – osos table including the original data from fpath_out (if exists) updated with the currently available data from github and pypi. This is also saved to fpath_out.

classmethod run_config(config)

Run multiple osos jobs from a csv config.

Parameters:

config (str) – Path to .csv config file with columns for git_owner, git_repo, fpath_out, and (optionally) pypi_name, conda_org, and conda_name.