Quantified self using Python
I keep a text file that acts as my "daily log". Anything of interest gets added, with the entries headed by a datetime stamp (using a keycode shortcut in neovim).
One item I track is my weight, and I have more than a thousand measurements taken over several years. To analyse this data, I created track, a Python program that scans a text file and matches regex values with corresponding calendar dates, and returns results as a dictionary, a two-column display, or generates a scatter plot viewable in a web browser ...
$ track.py -h
usage: track.py [-h] [-d regex] [-v regex] [-m num] [-q] [-r type] [-t title] [-l label] FILE
Scan FILE and match regex values with corresponding calendar dates
positional arguments:
FILE A readable file
optional arguments:
-h, --help show this help message and exit
-d regex, --date regex
A regex pattern to find dates (default: ^20\d\d-\d\d-\d\d)
-v regex, --value regex
A regex pattern to find values (default: ^\d)
-m num, --matchgroup num
0 matches entire value regex; > 0 is which part of regex, enclosed in parentheses, to match (default: 0)
-q, --quiet suppress non-error messages (default: False)
-r type, --results type
Display results as: dictionary, columns, scatterplot (default: dictionary)
-t title, --title title
A title for match results (default: Matches)
-l label, --label label
Subtitle for values (default: Values)
With all the heavy lifting done by track, it becomes easy to import this module into scripts and create a second tracking program, a third, etc. by changing options and regex search patterns.
Sources: track.py
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