You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

75 lines
2.0 KiB
Python

This file contains ambiguous Unicode characters!

This file contains ambiguous Unicode characters that may be confused with others in your current locale. If your use case is intentional and legitimate, you can safely ignore this warning. Use the Escape button to highlight these characters.

#!/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 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, dict(states), dict(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()
print(f'data got at {time}')
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)
print('pickle saved')
# Show the plot
plt.close()
plt.clf()
x = sorted(ts.data.keys()) # times
states = sorted(ts.states)
ys = [tuple(ts.data[time][0].get(state, 0) for state in 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, labels=states)
plt.legend(loc='upper left')
print('showing plot')
plt.show(block=False)
plt.pause(poll_rate)
main()