have colab and/or github.dev env ready try
djay opened this issue · 5 comments
Would have all the data loaded so you can explore it with some example plots in a notebook
or give you a starter development environment to add new plots or run pytest or add a scraper.
tried out
# Tests Plots
df = scrape_and_combine()
save_tests_plots(df)
from covid_plot.py
but got
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/Users/kahnwong/.pyenv/versions/3.8.6/lib/python3.8/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/Users/kahnwong/Git/covidthailand/covid_data_dash.py", line 123, in dash_daily
assert df[df['Recovered'] == 0.0].empty
AssertionError
"""
The above exception was the direct cause of the following exception:
AssertionError Traceback (most recent call last)
/var/folders/mc/1bzxsp8x6x1dl12nd62j64s40000gn/T/ipykernel_90632/3364214411.py in <module>
8
9 # Tests Plots
---> 10 df = scrape_and_combine()
11 save_tests_plots(df)
~/Git/covidthailand/covid_data.py in scrape_and_combine()
263 en_situation = en_situation.get()
264
--> 265 dash_daily = dash_daily.get()
266 dash_ages = dash_ages.get()
267 dash_by_province = dash_by_province.get()
~/.pyenv/versions/3.8.6/lib/python3.8/multiprocessing/pool.py in get(self, timeout)
769 return self._value
770 else:
--> 771 raise self._value
772
773 def _set(self, i, obj):
AssertionError:
I guess it's better to read from a static dump. Although the "release" link on the readme seems to be broken 🤔
@kahnwong I think a notebook is more useful for helping with plotting rather than scraping so downloading the csv release makes sense as thats the fastest way. Scraping I think is best done using an IDE and via pytest? Otherwise you need to get the 1.5G docs download...
I tested the link on https://github.com/djay/covidthailand#running-just-plots-or-latest-files and it seems to work fine for me.
Would it be something people open in colab or they have to check out and run locally?
I could do both: make a local nb but also make it available on colab too. Code drift should be minimal since it's mostly a wrapper function