[ot][spam][crazy] log: hobby chart of removal requests
i'd kind of like to make charts showing the removal requests i'm seeing i think they would make a pleasant linear line with some jitter that relates to network latency. they could be more interesting than that, i don't know. some time ago i figured out how to access my email programmatically, but i don't remember well how or where that was. i have inhibition around it, relates to archival of personal evidence. but i bet my email is already set up for imap access. maybe a python imap library
turns out google has a library at https://developers.google.com/gmail/api/quickstart/python i'm pausing this goal now
ok: the temporary goal now is to figure out what kind of statistical distribution the jitter in the removal requests has. it's 1634 UTC-5. 1634 and i'm installing the google library 1635 and i've pasted their example into a file 1635. i need a file called 'credentials.json' to log in. better learn what format it has. 1636 i skimmed the text and it looks like it's supposed to prompt me if token.json doesn't exist. 1636 i tried setting DISPLAY but still no prompt 1637 i found this problem is discussed at https://developers.google.com/gmail/api/quickstart/python#file_not_found_err... 1638 it looks like this library is for google cloud platform. i guess i'd rather use a normal imap library then. 1639 this sounds pretty familiar. https://docs.python.org/3/library/imaplib.html
i'm pausing this goal because i worry it could be rude to analyse somebody's statistical distribution however i expect it to come up again as a fun goal
we can form a hypothesis and pretend we are researchers or scientists or something. i hypothesize that it could be a uniform distribution within set ranges. the null hypothesis then would be that it is _not_ a uniform distribution, but instead some other shape. how can we test this? we would need _data_
what could be even more fun might be reproducing a script that would create removal requests with the same statistical properties ! like reverse engineering the requests.
then maybe we could look at the script and try to guess how the author feels that they are running it. it seems it is maybe not the best way, but it exists.
i like the idea of turning the behavior of programs back into code. it's been a theme.
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