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Python

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#!/usr/bin/env python3
import pickle
from matplotlib import pyplot as plt
import requests
import json
from datetime import datetime
from dataclasses import dataclass
from collections import defaultdict
from time import sleep
from pathlib import Path
api_url = r'https://review.video.fosdem.org/api/v1/event/1/overview'
poll_rate = 10*60 # seconds
pickle_file = Path(r'./talk_data.pickle')
@dataclass
class TimeSeries:
"The object to pickle and unpickle"
states: set[str]
jobstates: set[str]
data: dict[datetime, tuple[dict[str, int], dict[str, int]]] # time → (states(name → count), jobstates(ditto))
def get_data() -> tuple[datetime, dict[str, int], dict[str, int]]:
resp = requests.get(api_url)
# TODO: error handling?
time = datetime.now().astimezone()
data = json.loads(resp.content.decode())
states = defaultdict(lambda: 0)
jobstates = defaultdict(lambda: 0)
# should be an array/list
for talk in data:
states[talk['state']] += 1
jobstates[talk['progress']] += 1
return time, states, jobstates
def main():
if pickle_file.exists():
with open(pickle_file, 'rb') as f:
ts = pickle.load(f)
else:
print("New time series.")
ts = TimeSeries(states=set(), jobstates=set(), data=dict())
while True:
time, states, jobstates = get_data()
assert time not in ts.data
ts.data[time] = (states, jobstates)
ts.states |= states.keys()
ts.jobstates |= jobstates.keys()
# Save the pickle
# Should probably save elsewhere and do atomic rename, but whatever.
with open(pickle_file, 'wb') as f:
pickle.dump(ts, f)
# Show the plot
x = sorted(ts.data.keys()) # times
# vvv should be a defaultdict anyway, but let's be defensive :-)
ys = [tuple(ts.data[time][0].get(state, 0) for state in ts.states) for time in x] # numbers per state
# We do not show jobstates atm. Too lazy.
# ys are transposed we need vectors by times, not by states.
ys = list(zip(*ys))
plt.stackplot(x, *ys)
plt.show(block=False)
sleep(poll_rate)
plt.close()
plt.clf()
main()