Getting useful data from your source control management tool is really a 2 steps process: first you need to get the log entries (e.g. svn log or git log) as a pandas.DataFrame, then process this output with the functions described below.
The pandas.DataFrame returned by each SCM specific function contains colums corresponding to the fields of codemetrics.scm.LogEntry:
codemetrics.scm.LogEntry
Common logic for source control management tools.
codemetrics.scm
Getting your data from Subversion.
codemetrics.svn
Getting your data from git.
codemetrics.git
The main functions are located in core but can be accessed directly from the main module.
For instance:
>>>import codemetrics as cm
>>>import cm.svn
>>>log_df = cm.svn.get_svn_log()
>>>ages_df = cm.get_ages(log_df)codemetrics.core
Brdges visualization in Jupyter notebooks with Vega and Altair.
codemetrics.vega