gen_dategraph.py

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as ticker
import time
from datetime import datetime as dt
from datetime import timedelta

import sqlite3

db = sqlite3.connect('./db.sqlite3')
cur = db.cursor()


def dump():
    figpath = '%s.png' % pdate.strftime('%Y-%m-%d')
    fig, ax = plt.subplots()

    start = dt.combine(pdate, dt.min.time())
    end = dt.combine(pdate, dt.max.time())

    ax.set_xlim(start, end)
    ax.set_ylim(0, 20 * 10**9)
    ax.plot(log_x, log_y)
    ax.plot([ start, end ], [ 10 * 10**9, ] * 2)
    ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))
    ax.yaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '%.1f GB' % (x / (10**9), )))
    fig.suptitle(pdate.isoformat())
    fig.savefig(figpath)

pdate = None
log_x, log_y = [], []
results = [ row for row in cur.execute('SELECT * FROM stat ORDER BY time') ]
for idx in range(len(results)):
    id, download, upload, time = results[idx]
    time_dt = dt.fromtimestamp(time)
    time_d = time_dt.date()

    if pdate is not None:
        if pdate != time_d:
            print(pdate)
            dump()

    log_x.append(time_dt)
    log_y.append(download)
    pdate = time_d

print(pdate)
dump()

db.close()