def get_jobs_plot(day: date) -> Figure:
"""Return matplotlib plot showing the number i-page-job to the day."""
day_of_week: int = pyday_to_sqlday(day.weekday())
day_quota: int = quota.daily_quota(
datetime.combine(day, datetime.min.time()))
sql_today_freq = '''
SELECT `pages`, SUM(`count`) AS `count`
FROM `public_jobs`
WHERE
(`pages` <= %s) AND
(DAYOFWEEK(`day`) = %s) AND
(`day` = %s )
GROUP BY `pages`
ORDER BY `pages` ASC
'''
# executing the sql query to get the data
with quota.get_connection() as cursor:
cursor.execute(sql_today_freq, (day_quota, day_of_week, day))
today_freq_data = cursor.fetchall()
# converting the data into a list
today_jobs_dict = {row['pages']: row['count'] for row in today_freq_data}
today_jobs_count = [
today_jobs_dict.get(i, 0) for i in range(1, day_quota + 1)
]
# Generating the plot
fig = Figure(figsize=(10, 4))
ax = fig.add_subplot(1, 1, 1)
tickLocations = np.arange(1, day_quota + 1)
width = 0.8
ax.bar(tickLocations, today_jobs_count, width)
ax.set_xticks(ticks=tickLocations)
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
ax.yaxis.grid(True)
ax.set_ylim(bottom=0)
ax.set_ylabel('Number of Jobs Printed')
ax.set_title(f'Print Job Distribution {day:%a %b %d}')
return fig
def get_jobs_plot(day):
"""Return matplotlib plot showing the number i-page-job to the day."""
day_of_week = pyday_to_sqlday(day.weekday())
day_quota = quota.daily_quota(datetime.combine(day, datetime.min.time()))
sql_today_freq = '''
SELECT `pages`, SUM(`count`) AS `count`
FROM `public_jobs`
WHERE
(`pages` <= %s) AND
(DAYOFWEEK(`day`) = %s) AND
(`day` = %s )
GROUP BY `pages`
ORDER BY `pages` ASC
'''
# executing the sql query to get the data
with quota.get_connection() as cursor:
cursor.execute(sql_today_freq, (day_quota, day_of_week, day))
today_freq_data = cursor.fetchall()
# converting the data into a list
today_jobs_dict = {row['pages']: row['count'] for row in today_freq_data}
today_jobs_count = [today_jobs_dict.get(i, 0) for i in range(1, day_quota + 1)]
# Generating the plot
fig = Figure(figsize=(10, 4))
ax = fig.add_subplot(1, 1, 1)
tickLocations = np.arange(1, day_quota + 1)
width = 0.8
ax.bar(tickLocations, today_jobs_count, width)
ax.set_xticks(ticks=tickLocations)
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
ax.yaxis.grid(True)
ax.set_ylim(ymin=0)
ax.set_ylabel('Number of Jobs Printed')
ax.set_title('Print Job Distribution {:%a %b %d}'.format(day))
return fig
def test_daily_quota(time, expected):
"""Test that the daily quota returns reasonable things."""
time = datetime.strptime(time, '%Y-%m-%d')
with freeze_time(time):
assert daily_quota() == expected
assert daily_quota(time) == expected
def test_daily_quota(time, expected):
"""Test that the daily quota returns reasonable things."""
time = datetime.strptime(time, '%Y-%m-%d')
with freeze_time(time):
assert daily_quota() == expected
assert daily_quota(time) == expected
