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