Comments (3)
Any ideas before I do a big run? Cheers
from py-xbrl.
Hello @mrx23dot ,
i have looked into the filing you provided and was able to successfully extract the two facts tagged with "dei:EntityCommonStockSharesOutstanding". One concept has the member "CommonClassAMember" the other "CommonClassBMember".
This was the code i used:
cache: HttpCache = HttpCache('./cache')
xbrlParser = XbrlParser(cache)
inst: XbrlInstance = xbrlParser.parse_instance(
'https://www.sec.gov/Archives/edgar/data/0001751143/000121390021027034/f10q0321_atlastechnical.htm')
print(inst)
facts: list = []
for fact in inst.facts:
if fact.concept.name == 'EntityCommonStockSharesOutstanding':
facts.append(fact)
print(facts)
In this screenshot you can see how the parsed facts correspond with the iXBRL Viewer of the SEC.
You can use this code to print out the facts with their corresponding dimensions/members
for fact in facts:
print(f"{fact.concept.name}: {fact.value} ({fact.context.segments[0].member if len(fact.context.segments) > 0 else ''})")
Please let me know if that works for you :)
Greetings,
Manu
from py-xbrl.
Works great it was hidden away :D Thanks!
The structural filtering (like cover/balance/cashflow section) would be a great addition.
Currently I query for number of shares and it gives me back 4+ different results all over the doc and no way telling which one is front cover and which one is from textblob or subsidiary.
from py-xbrl.
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