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feat: added analyze_sponsors.py script
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__pycache__ | ||
*.png | ||
output |
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output/sponsors.html: output/sponsors.md | ||
markdown2 $< -x tables > $@ | ||
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output/sponsors.md: analyze_sponsors.py | ||
python3 analyze_sponsors.py > $@ |
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""" | ||
Analyze sponsor data to generate a sponsors table on the website | ||
""" | ||
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from dataclasses import dataclass, field | ||
from datetime import datetime, timedelta, timezone | ||
from typing import Optional | ||
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import pandas as pd | ||
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Amount = float | ||
Currency = str | ||
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@dataclass | ||
class Sponsor: | ||
name: str | ||
github_username: Optional[str] = None | ||
donated: list[tuple[Amount, Currency, datetime]] = field(default_factory=list) | ||
source: str = "unknown" | ||
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def __repr__(self): | ||
return f"<Sponsor {self.name} ({self.github_username}) on {self.source} total_donated={self.total_donated}>" | ||
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@property | ||
def total_donated(self): | ||
# group donated by currency, aggregate by sum | ||
currencies = set([currency for _, currency, _ in self.donated]) | ||
total_donated = {} | ||
for currency in currencies: | ||
total_donated[currency] = sum( | ||
[amount for amount, c, _ in self.donated if c == currency] | ||
) | ||
return total_donated | ||
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def load_github_sponsors_csv(filename: str) -> list[Sponsor]: | ||
"""The CSV looks like the following: | ||
Sponsor Handle,Sponsor Profile Name,Sponsor Public Email,Sponsorship Started On,Is Public?,Is Yearly?,Transaction ID,Tier Name,Tier Monthly Amount,Processed Amount,Is Prorated?,Status,Transaction Date,Metadata,Country,Region,VAT | ||
snehal-shekatkar,Snehal Shekatkar,,2023-05-07 21:45:50 +0200,true,false,ch_3N5DWnEQsq43iHhX1Svht2g7,$5 a month,$5.00,$4.52,true,settled,2023-05-07 21:46:01 +0200,"",AUT,undefined, | ||
justyn,Justyn Butler,,2023-02-15 12:14:28 +0100,true,false,ch_3NExsXEQsq43iHhX0Fmfcg6w,$3 a month,$3.00,$3.00,false,settled,2023-06-03 19:04:45 +0200,"",GBR,Kent, | ||
justyn,Justyn Butler,,2023-02-15 12:14:28 +0100,true,false,ch_3N3ikOEQsq43iHhX1eMXefVn,$3 a month,$3.00,$3.00,false,settled,2023-05-03 18:41:56 +0200,"",GBR,Kent, | ||
""" | ||
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df = pd.read_csv( | ||
filename, parse_dates=["Sponsorship Started On", "Transaction Date"] | ||
) | ||
df = df[df["Is Public?"] == True] # noqa: E712 | ||
df = df[df["Status"] == "settled"] | ||
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sponsors = [] | ||
handles = df["Sponsor Handle"].unique() | ||
for handle in handles: | ||
sponsor = Sponsor( | ||
name="placeholder", | ||
github_username=handle, | ||
donated=[], | ||
source="github", | ||
) | ||
for _, row in df.iterrows(): | ||
if row["Sponsor Handle"] != handle: | ||
continue | ||
sponsor.name = row["Sponsor Profile Name"] | ||
sponsor.donated.append( | ||
( | ||
float(row["Processed Amount"].replace("$", "")), | ||
"USD", | ||
row["Transaction Date"], | ||
) | ||
) | ||
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sponsors.append(sponsor) | ||
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return sponsors | ||
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def load_opencollective_csv(filename: str) -> list[Sponsor]: | ||
"""The CSV looks like this: | ||
"datetime","shortId","shortGroup","description","type","kind","isRefund","isRefunded","shortRefundId","displayAmount","amount","paymentProcessorFee","netAmount","balance","currency","accountSlug","accountName","oppositeAccountSlug","oppositeAccountName","paymentMethodService","paymentMethodType","expenseType","expenseTags","payoutMethodType","merchantId","orderMemo" | ||
"2023-06-06T05:47:17","d3f98b95","f2238225","Contribution from Martin","CREDIT","CONTRIBUTION","","","","$50.00 USD",50,-2.5,47.5,3059.14,"USD","activitywatch","ActivityWatch","guest-cf5e5bf5","Martin","STRIPE","CREDITCARD",,"",,, | ||
"2023-06-06T05:47:17","e3c0d1f9","f2238225","Host Fee to Open Source Collective","DEBIT","HOST_FEE","","","","-$5.00 USD",-5,0,-5,3011.64,"USD","activitywatch","ActivityWatch","opensource","Open Source Collective",,,,"",,, | ||
"2023-06-01T04:03:23","80120e4e","9a189bcd","Yearly contribution from Olli Nevalainen","CREDIT","CONTRIBUTION","","","","$24.00 USD",24,-1.24,22.76,3016.64,"USD","activitywatch","ActivityWatch","olli-nevalainen","Olli Nevalainen","STRIPE","CREDITCARD",,"",,, | ||
""" | ||
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df = pd.read_csv(filename, parse_dates=["datetime"]) | ||
df = df[df["type"] == "CREDIT"] | ||
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sponsors = [] | ||
handles = df["oppositeAccountSlug"].unique() | ||
for handle in handles: | ||
sponsor = Sponsor( | ||
name="placeholder", | ||
github_username=handle, | ||
donated=[], | ||
source="opencollective", | ||
) | ||
for _, row in df.iterrows(): | ||
if row["oppositeAccountSlug"] != handle: | ||
continue | ||
sponsor.name = row["oppositeAccountName"] | ||
sponsor.donated.append( | ||
( | ||
row["amount"], | ||
row["currency"], | ||
row["datetime"].replace(tzinfo=timezone.utc), | ||
) | ||
) | ||
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sponsors.append(sponsor) | ||
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# remove 'GitHub Sponsors' from sponsors | ||
sponsors = [sponsor for sponsor in sponsors if sponsor.name != "GitHub Sponsors"] | ||
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# subtract $3002 from Kerkko (actually FUUG.fi) | ||
for sponsor in sponsors: | ||
if sponsor.name == "Kerkko Pelttari": | ||
sponsor.donated.append((-3002, "USD", datetime.now(tz=timezone.utc))) | ||
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return sponsors | ||
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def load_patreon_csv(filename: str) -> list[Sponsor]: | ||
"""The CSV looks like: | ||
Name,Email,Twitter,Discord,Patron Status,Follows You,Lifetime Amount,Pledge Amount,Charge Frequency,Tier,Addressee,Street,City,State,Zip,Country,Phone,Patronage Since Date,Last Charge Date,Last Charge Status,Additional Details,User ID,Last Updated,Currency,Max Posts,Access Expiration,Next Charge Date | ||
Karan singh,[email protected],,kraft#9466,Declined patron,No,0.00,1.00,monthly,Time Tracker,,,,,,,,2023-04-08 17:45:28.731953,2023-05-31 07:46:37,Declined,,76783024,2023-05-31 08:01:37.517184,USD,,,2023-05-01 07:00:00 | ||
Dan Thompson,[email protected],,,Declined patron,No,0.00,1.00,monthly,Time Tracker,,,,,,,,2023-02-28 20:00:03.756241,2023-03-15 12:03:01,Declined,,46598895,2023-03-15 12:18:01.633900,USD,,,2023-03-01 08:00:00 | ||
""" | ||
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df = pd.read_csv(filename, parse_dates=["Patronage Since Date", "Last Charge Date"]) | ||
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sponsors = [] | ||
for _, row in df.iterrows(): | ||
sponsor = Sponsor( | ||
name=row["Name"], | ||
github_username=None, | ||
donated=[ | ||
( | ||
row["Lifetime Amount"], | ||
row["Currency"], | ||
row["Last Charge Date"].replace(tzinfo=timezone.utc), | ||
) | ||
], | ||
source="patreon", | ||
) | ||
sponsors.append(sponsor) | ||
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return sponsors | ||
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if __name__ == "__main__": | ||
now = datetime.now(tz=timezone.utc) | ||
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sponsors = load_github_sponsors_csv( | ||
"data/sponsors/ActivityWatch-sponsorships-all-time.csv" | ||
) | ||
sponsors += load_opencollective_csv( | ||
"data/sponsors/opencollective-activitywatch-transactions.csv" | ||
) | ||
sponsors += load_patreon_csv("data/sponsors/patreon-members-866337.csv") | ||
sponsors = sorted(sponsors, key=lambda s: s.total_donated["USD"], reverse=True) | ||
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# filter out sponsors who have donated less than $10 | ||
sponsors = [sponsor for sponsor in sponsors if sponsor.total_donated["USD"] >= 10] | ||
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# print as markdown table | ||
print("| Name | Active? | Total Donated |") | ||
print("| ---- |:-------:| -------------:|") | ||
for sponsor in sponsors: | ||
link = ( | ||
f"([@{sponsor.github_username}](https://github.com/{sponsor.github_username}))" | ||
if sponsor.github_username | ||
else "" | ||
) | ||
# active if last donation was less than 3 months ago | ||
last_donation: datetime = max(timestamp for _, _, timestamp in sponsor.donated) | ||
is_active = ( | ||
last_donation > now - timedelta(days=90) if sponsor.donated else False | ||
) | ||
print( | ||
f"| {sponsor.name} {link} | {'✔️' if is_active else ''} | {sponsor.total_donated['USD']:.2f} USD |" | ||
) |
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