Comments (6)
Greetings,
Just wanted to congratulate you on this amazing python PINOY PSE lbrary.
Now for my question;
I imported the following:
from fastquant import get_company_disclosures
but got this error on google colab:
`ImportError Traceback (most recent call last)
in ()
----> 1 from fastquant import get_company_disclosures
ImportError: cannot import name 'get_company_disclosures'
`
I thought it could be a problem with the Kernel so I restarted, re-installed fastquant and re-ran all the python scripts but still couldn't import get_company_discolsures.....
Any suggestions would be highly appreciated. Thanks.
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Hi @RadEdje, thanks for checking fastquant. You have to first initialize the DisclosuresPSE
class before being able to use the get_company_disclosures
method. Please see the example in this notebook:
https://github.com/enzoampil/fastquant/blob/master/examples/disclosures.ipynb
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@jpdeleon
You basically read my mind on the next steps for that function. Figuring out the pattern w/ that URL is still a huge todo that could allow us to integrate a lot of NLP into psequant.
On how to scrape the company disclosures, my current impression (haven't stress tested this but have seen the patterns based on a few instances) is that each Template Name (w/ its own form number) will have a fairly similar html structure, so the current approach to adding functionality to scrape contents is if we go through each template one by one and create the scraping logic for each separately. Of course we can prioritize certain templates over others and start with those.
I'll prioritize this as the next feature to work on (probably w/ disclosures first), but also feel free to help out with a PR if you find a solution before I post an update :)
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@jpdeleon URL issue should be resolved now. get_company_disclosures()
now returns a df with a url
column that points to the url of the required doc :) Now the only thing left is to integrate scraping logic per disclosure type! (as indicated above).
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I pulled the changes and it worked! Inddeed, simply adding an url
column in the df
is the way to go.
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@RadEdje Did it work for you? Please give us some feedback for improvements or feature requests if there are any. Thanks!
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