hledger/examples/self-tracking
2023-06-27 18:55:08 -10:00
..
a.dat ;examples: self-tracking 2023-06-27 17:56:09 -10:00
a.tsv ;examples: self-tracking 2023-06-27 17:56:09 -10:00
b.dat ;examples: self-tracking 2023-06-27 17:56:09 -10:00
c.tsv ;examples: self-tracking 2023-06-27 17:56:09 -10:00
c.tsv.rules ;examples: self-tracking 2023-06-27 17:56:09 -10:00
d.csv ;examples:self-tracking: add missing files 2023-06-27 18:55:08 -10:00
d.csv.rules ;examples:self-tracking: add missing files 2023-06-27 18:55:08 -10:00
d.dat ;examples:self-tracking: add missing files 2023-06-27 18:55:08 -10:00
README.md ;examples:self-tracking: updates 2023-06-27 18:53:18 -10:00

Some examples of working with the https://www.gibney.org/a_syntax_for_self-tracking logging format (discussion: https://news.ycombinator.com/item?id=36492033).

If you have a.dat:

2020-05-28 18:41 Eat Pizza
2020-05-29 09:00 Slept with the window open
2020-05-29 09:00 Headaches

This is close enough to hledger's timedot format to do some reporting. Each line is interpreted as an empty transaction:

$ hledger -f timedot:a.dat print 
2020-05-28 * 18:41 Eat Pizza

2020-05-29 * 09:00 Slept with the window open

2020-05-29 * 09:00 Headaches

And you could query those by date or description:

$ hledger -f timedot:a.dat print date:2020/5/28
2020-05-28 * 18:41 Eat Pizza

$ hledger -f timedot:a.dat print desc:eat
2020-05-28 * 18:41 Eat Pizza

Or by tag, if you added tags like so:

2020-05-28 18:41 Eat Pizza  ; food:
2020-05-29 09:00 Slept with the window open  ; body:, sleep:
2020-05-29 09:00 Headaches  ; body:
$ hledger -f timedot:b.dat print tag:sleep
2020-05-29 * 09:00 Slept with the window open  ; body:, sleep:

You could transform your format to a plain text accounting format with quantities. Eg, make it TSV or CSV:

$ perl -pe '$c=0; $c++ while $c < 2 && s/ /\t/' a.dat > c.tsv
$ cat c.tsv
2020-05-28	18:41	Eat Pizza
2020-05-29	09:00	Slept with the window open
2020-05-29	09:00	Headaches

and use hledger CSV conversion rules to customise and enrich it:

$ cat c.tsv.rules
fields date, time, description

# save the time as a tag
comment time:%time

# count each item as one "event" by default
account1 (events)
amount1  1

# special cases
if pizza
 account1 (food)
 amount1  200 cal

Now you have a (single entry) accounting journal:

$ hledger -f c.tsv print

2020-05-28 Eat Pizza  ; time:18:41
    (food)         200 cal

2020-05-29 Slept with the window open  ; time:09:00
    (events)               1

2020-05-29 Headaches  ; time:09:00
    (events)               1

Allowing quantity reports:

$ hledger -f c.tsv balance -MATS cur:cal

Balance changes in 2020-05:

      ||     May    Total  Average 
======++===========================
 food || 200 cal  200 cal  200 cal 
------++---------------------------
      || 200 cal  200 cal  200 cal 
$ hledger -f c.tsv activity -D desc:headache
2020-05-28 
2020-05-29 *
$ hledger-bar -v -f c.tsv cur:cal
2020-05	       200 ++
$ hledger-ui --all -f c.tsv   # explore with a TUI

Or, with d.dat:

2023-06-27 06:40 Wakeup
2023-06-27 06:40 Last_night_sleep_time: 07h21
2023-06-27 06:40 Last_night_sleep_interruptions: 1
2023-06-27 06:40 Yesterdays_Steps: 11898
2023-06-27 08:49 Temperature: 24.8
2023-06-27 08:49 Humidity: 40%
2023-06-27 09:21 Take_Iron? No
2023-06-27 09:21 Take_VitaminD3? No

Convert to character-separated values again (using pipe this time):

$ cat d.dat | perl -pe '$c=0; $c++ while $c < 2 && s/ /|/' | perl -pe 's/: /|/; s/\? /?|/' > d.csv
$ cat d.csv
2023-06-27|06:40|Wakeup
2023-06-27|06:40|Last_night_sleep_time|07h21
2023-06-27|06:40|Last_night_sleep_interruptions|1
2023-06-27|06:40|Yesterdays_Steps|11898
2023-06-27|08:49|Temperature|24.8
2023-06-27|08:49|Humidity|40%
2023-06-27|09:21|Take_Iron?|No
2023-06-27|09:21|Take_VitaminD3?|No

Again, use rules to convert/enrich (or, add more structure in the source data, requiring less enrichment):

$ cat d.csv.rules
separator |
fields date, time, description, value

comment time:%time, value:%value

account1 (events)

amount1  1
if %value ^[0-9]+$
 amount1 %value
if steps
 amount1 %value steps
if %value no
 amount1 0
if %value yes
 amount1 1

if
wake
sleep
 account1 (body:sleep)

if
steps
 account1 (body:exercise)

if
iron
vitamin
 account1 (body:supplements)

if
pizza
 account1 (food)
 amount1  200 cal
$ hledger -f d.csv print
2023-06-27 Wakeup  ; time:06:40, value:
    (body:sleep)               1

2023-06-27 Last_night_sleep_time  ; time:06:40, value:07h21
    (body:sleep)               1

2023-06-27 Last_night_sleep_interruptions  ; time:06:40, value:1
    (body:sleep)               1

2023-06-27 Yesterdays_Steps  ; time:06:40, value:11898
    (body:exercise)     11898 steps

2023-06-27 Temperature  ; time:08:49, value:24.8
    (events)               1

2023-06-27 Humidity  ; time:08:49, value:40%
    (events)               1

2023-06-27 Take_Iron?  ; time:09:21, value:No
    (body:supplements)               0

2023-06-27 Take_VitaminD3?  ; time:09:21, value:No
    (body:supplements)               0

$ hledger -f d.csv register sleep
2023-06-27 Wakeup               (body:sleep)                     1             1
2023-06-27 Last_night_sleep_..  (body:sleep)                     1             2
2023-06-27 Last_night_sleep_..  (body:sleep)                     1             3

Current hledger has a csv tags parsing bug; reparse the conversion to work around:

$ hledger -f d.csv tags

$ hledger -f d.csv print | hledger -f- tags
time
value

hledger's data model doesn't include time, but we can pivot on the time tag and take advantage of the colon to summarise activities by hour each day (eg):

$ hledger -f d.csv print | hledger -f- bal --pivot=time --depth 1 -DAE

Balance changes in 2023-06-27:

    ||            2023-06-27                Average 
====++==============================================
 06 || 3 events, 11898 steps  3 events, 11898 steps 
 08 ||              2 events               2 events 
 09 ||                     0                      0 
----++----------------------------------------------
    || 5 events, 11898 steps  5 events, 11898 steps