def beli_lapangan(id_lapangan):
if islogin():
status = True
d_checkin = request.form['checkin']
d_checkout = request.form['checkout']
d_waktuin = request.form['waktuin']
d_waktuout = request.form['waktuout']
d_lapangan = lapangan.get(lapangan.id == id_lapangan)
d_nama = request.form['nama']
d_ktp = request.form['ktp']
d_checkin = datetime.datetime.strptime(d_checkin,'%Y-%m-%d')
d_checkout = datetime.datetime.strptime(d_checkout,'%Y-%m-%d')
d_waktuin = datetime.datetime.strptime(d_waktuin,'%H:%M')
d_waktuout = datetime.datetime.strptime(d_waktuout,'%H:%M')
d_checkin = datetime.datetime(d_checkin.year,d_checkin.month,d_checkin.day,d_waktuin.hour,d_waktuin.minute)
d_checkout = datetime.datetime(d_checkout.year,d_checkout.month,d_checkout.day,d_waktuout.hour,d_waktuout.minute)
# cek
d_transaksi = transaksi.select().where((transaksi.selesai == False)&(transaksi.id_lapangan == id_lapangan))
if d_transaksi.exists():
for data in d_transaksi:
d_checkin_d = datetime.datetime(data.checkin.year,data.checkin.month,data.checkin.day,data.checkin.hour,data.checkin.minute)
d_checkout_d = datetime.datetime(data.checkout.year,data.checkout.month,data.checkout.day,data.checkout.hour,data.checkout.minute)
checkin_now = d_checkin
checkout_now = d_checkout
time_range = DateTimeRange(checkin_now,checkout_now)
for date in time_range.range(datetime.timedelta(days=1)):
hour_range = DateTimeRange(date,checkout_now)
for hour in hour_range.range(datetime.timedelta(hours=1)):
minute_range = DateTimeRange(hour,checkout_now)
for minute in hour_range.range(datetime.timedelta(minutes=1)):
if d_checkin_d == minute or d_checkout_d == minute:
# print(True)
status = False
break
if status == True:
lama_menginap = d_checkout - d_checkin
# print(lama_menginap.seconds // 3600) #getHours
d_total_harga = int(lama_menginap.seconds // 3600) * int(d_lapangan.harga)
transaksi.create(
id_user=session['iduser'],
id_lapangan=id_lapangan,
nama_pemesan=d_nama,
no_ktp=d_ktp,
checkin = d_checkin,
checkout = d_checkout,
total_harga=d_total_harga,
waktu_transaksi=datetimenow())
return redirect(url_for('index'))
return redirect(url_for('index'))
return redirect(url_for('index'))
def generate_timestamp(start_datetime, sampling_rate, signal_length):
"""
Parameters
----------
start_datetime :
sampling_rate : float
signal_length : int
Returns
-------
list : list of timestamps with length equal to signal_length.
"""
number_of_seconds = (signal_length - 1)/sampling_rate
if start_datetime is None:
start_datetime = dt.datetime.now()
end_datetime = start_datetime + dt.timedelta(seconds=number_of_seconds)
time_range = DateTimeRange(start_datetime, end_datetime)
timestamps = []
for value in time_range.range(dt.timedelta(seconds=1/sampling_rate)):
timestamps.append(value)
if len(timestamps) != signal_length:
raise Exception("Timestamp series generated is not valid, please "
"check sampling rate.")
return timestamps
def update_training_for_staff_after_absence(sender, instance, **kwargs):
if instance.abs_type.abbr == "FOR":
absence_range = instance.datetime_range
old_absence_start_date = instance.tracker.previous("start_date")
old_absence_end_date = instance.tracker.previous("end_date")
old_absence_range = DateTimeRange(old_absence_start_date,
old_absence_end_date)
years = []
rt = RightTraining.objects.first()
if rt:
for value in absence_range.range(datetime.timedelta(days=1)):
if value.month in range(rt.start_month, 13):
year = value.year
else:
year = value.year - 1
if year not in years:
years.append(year)
if old_absence_start_date and old_absence_end_date:
for value in old_absence_range.range(
datetime.timedelta(days=1)):
if value.month in range(rt.start_month, 13):
year = value.year
else:
year = value.year - 1
if year not in years:
years.append(year)
call_command('update_training',
years=years,
staffs=[instance.staff.id])
def horarios_futuros(self, data, solicitante):
quando = self.solicitacao_futura(solicitante)
if quando is not None:
inicio = localtime(quando.inicio).strftime('%d/%m/%Y às %H:%M')
raise Exception(
f"Você já tem uma solicitação prevista para {inicio} na situação {quando.status}"
)
if not (max(self.inicio, date.today()) <= data.date() <= self.fim):
raise Exception(
f"A data deve ser entre {self.inicio} e {self.fim}, mas você informou a data {data}."
)
result = []
for vaga in self.vaga_set.filter(dia=data.weekday()):
time_range = DateTimeRange(datetime.combine(data, vaga.inicio),
datetime.combine(data, vaga.fim))
for dt in time_range.range(timedelta(minutes=self.janela)):
if make_aware(dt) > now():
quantidade = Solicitacao.objects.filter(
agenda=self,
inicio=dt,
status__in=[
Solicitacao.Status.DEFERIDO,
Solicitacao.Status.SOLICITADO
]).count()
if quantidade < vaga.atendimentos:
result.append(dt)
return result[:-1]
def merge_schedules(players: Dict[str, List[DateTimeRange]], required: int,
start: datetime) -> Dict[datetime, List[Set[str]]]:
"""Merge individual schedules to time slots where people are free.
Takes a mapping of people's availability and returns a mapping of
blocks of time (by the start time) to players free in that block.
E.g. if Jon is free at 12-2pm and Neel is free from 1-2pm and blocks
are 30 minutes, then return a dictionary of 4 times, with the first
2 time blocks mapping to (Jon) and the second two to (Jon, Neel).
"""
if not start:
start = datetime.now(timezone("Europe/London")).replace(minute=0,
second=0,
microsecond=0)
candidates = DateTimeRange(start, start + timedelta(days=14))
potentials = defaultdict(list)
for candidate_times in candidates.range(timedelta(minutes=MINUTES)):
candidate_players = []
for player, timeranges in players.items():
for timerange in timeranges:
if timerange.start_datetime <= candidate_times < timerange.end_datetime:
candidate_players.append(player)
for combination_length in range(required, len(candidate_players) + 1):
combos = combinations(candidate_players, combination_length)
potentials[candidate_times].extend(combos)
return potentials
def generate_timeslots_dict(work_hours_list, interval):
"""
Args:
work_hours_list:
interval:
Returns:
"""
timeslots_dict = dict()
if len(work_hours_list) == 1:
time_range = DateTimeRange(work_hours_list[0], work_hours_list[-1])
timeslots_dict = {
value: 1
for value in time_range.range(relativedelta(
minutes=+int(interval)))
}
elif len(work_hours_list) == 4:
first_time_range = DateTimeRange(work_hours_list[0],
work_hours_list[1])
first_timeslots_dict = {
value: 1
for value in first_time_range.range(
relativedelta(minutes=+int(interval)))
}
second_time_range = DateTimeRange(work_hours_list[1],
work_hours_list[2])
second_timeslots_dict = {
value: 0
for value in second_time_range.range(
relativedelta(minutes=+int(interval)))
}
third_time_range = DateTimeRange(work_hours_list[2],
work_hours_list[3])
third_timeslots_dict = {
value: 1
for value in third_time_range.range(
relativedelta(minutes=+int(interval)))
}
timeslots_dict.update(first_timeslots_dict)
timeslots_dict.update(second_timeslots_dict)
timeslots_dict.update(third_timeslots_dict)
return timeslots_dict
def beli_kamar(id_kamar):
if islogin():
status = True
d_checkin = request.form['checkin']
d_checkout = request.form['checkout']
d_kamar = kamar.get(kamar.id == id_kamar)
d_nama = request.form['nama']
d_ktp = request.form['ktp']
d_checkin = datetime.datetime.strptime(d_checkin, '%Y-%m-%d')
d_checkout = datetime.datetime.strptime(d_checkout, '%Y-%m-%d')
# cek
d_transaksi = transaksi.select().where(
(transaksi.selesai == False) & (transaksi.id_kamar == id_kamar))
if d_transaksi.exists():
for data in d_transaksi:
d_checkin_d = datetime.datetime(data.checkin.year,
data.checkin.month,
data.checkin.day, 0, 0)
d_checkout_d = datetime.datetime(data.checkout.year,
data.checkout.month,
data.checkout.day, 0, 0)
checkin_now = datetime.datetime(d_checkin.year,
d_checkin.month, d_checkin.day,
0, 0)
checkout_now = datetime.datetime(d_checkout.year,
d_checkout.month,
d_checkout.day, 0, 0)
time_range = DateTimeRange(checkin_now, checkout_now)
for date in time_range.range(datetime.timedelta(days=1)):
check = date
if d_checkin_d == check or d_checkout_d == check:
status = False
if status == True:
lama_menginap = datetime.datetime(
d_checkout.year, d_checkout.month,
d_checkout.day, 0, 0) - datetime.datetime(
d_checkin.year, d_checkin.month, d_checkin.day, 0, 0)
d_total_harga = int(lama_menginap.days) * int(d_kamar.harga)
transaksi.create(id_user=session['iduser'],
id_kamar=id_kamar,
nama_pemesan=d_nama,
no_ktp=d_ktp,
checkin=d_checkin,
checkout=d_checkout,
total_harga=d_total_harga,
waktu_transaksi=datetimenow())
return redirect(url_for('index'))
return redirect(url_for('index'))
return redirect(url_for('index'))
def saveDateRange(start, end):
givenRange = DateTimeRange(start, end)
tables = ['Jobs', 'ReviewJobs']
for table in tables:
data = []
query = 'SELECT * FROM ' + table
cur.execute(query)
results = [list(each) for each in cur.fetchall()]
for job in results:
dateRange = job[15]
d = [each.lstrip().rstrip() for each in dateRange.split("-")]
s = d[0].split("/")
startFormat = str(int(s[2]) + 2000) + "/" + s[1] + "/" + s[0]
inRange = False
if len(d) > 1:
e = d[1].split("/")
endFormat = str(int(e[2]) + 2000) + "/" + e[1] + "/" + e[0]
tableRange = DateTimeRange(startFormat, endFormat)
for day in tableRange.range(relativedelta(days=1)):
if day in givenRange:
inRange = True
else:
inRange = startFormat in givenRange
if inRange:
data.append(job)
columnNames = names.get(table)
file = "Date Range for " + table + " from " + start.replace("/", "-") + " to " + end.replace("/", "-") + ".csv"
if len(data) > 0:
data.insert(0, columnNames)
data.insert(1, [])
for i in range(len(data)):
line = data[i]
if (i == 0):
open(file, 'w+').close()
with open(file, 'a', newline='') as fp:
a = csv.writer(fp, delimiter=',')
line = [line]
a.writerows(line)
def add_cron_job(cron_day, stop_date):
days_ = ["mon", "tue", "wed", "thu", "fri", "sat", "sun"]
cron_day = days_.index(cron_day)
today_ = datetime.date.today()
date1 = datetime.datetime.strptime(str(today_), '%Y-%m-%d')
date2 = datetime.datetime.strptime(stop_date,
'%Y-%m-%d') - datetime.timedelta(days=1)
time_range = DateTimeRange(date1, date2)
for value in time_range.range(datetime.timedelta(days=1)):
if cron_day == value.weekday():
return True
return False
def apithree(request, start_date, end_date):
response = requests.get(
'https://gitlab.com/-/snippets/2094509/raw/master/sample_json_2.json')
all_data = response.json()
time_range_2 = DateTimeRange(start_date, end_date)
all_date = []
for value in time_range_2.range(datetime.timedelta(minutes=1)):
(all_date.append(str(value.date()) + ' ' + str(value.time())))
time_sets = set()
for i in all_date:
time_sets.add(i)
runtime = 0
downtime = 0
for data in all_data:
if data['time'] in time_sets:
if data['runtime'] <= 1021:
runtime += data['runtime']
if data['runtime'] > 1021:
evaluated_downtime = data['runtime'] - 1021
downtime += evaluated_downtime
runtime += 1021
# print(runtime,downtime)
total_runtime = round(((runtime) / (runtime + downtime)) * 100, 2)
# conversion on runtime and downtime seconds to hh:mm:ss
minute, sec = divmod(runtime, 60)
hour, minute = divmod(minute, 60)
runtime = ("%dh:%02dm:%02ds" % (hour, minute, sec))
minute, sec = divmod(downtime, 60)
hour, minute = divmod(minute, 60)
downtime = ("%dh:%02dm:%02ds" % (hour, minute, sec))
# =====================================================
result = {
'runtime': runtime,
'downtime': downtime,
'utilization': total_runtime
}
print(result)
return JsonResponse(result, safe=False)
def get_vacancies_by_search_phrase_async2(search_dict):
search_str = '&'.join(f'{k}={v}' for k, v in search_dict.items())
url = f'{VACANCY_URL}?{search_str}'
print(url)
start_time = datetime.utcnow().replace(tzinfo=timezone.utc)
end_time = start_time - timedelta(**TIME_PERIOD)
step_time_delta = timedelta(**TIME_STEP)
time_range = DateTimeRange(end_time, start_time)
time_interval_list = [(start + step_time_delta, start)
for start in time_range.range(step_time_delta)][::-1]
vacancy_id_list = asyncio.run(get_search_res_list(url, time_interval_list))
vacancy_list = asyncio.run(get_vacancies_coro(list(set(vacancy_id_list))))
with open(f'{OUTPUT_DIR}/{search_str}{start_time}{end_time}.json',
mode='w',
encoding='utf8') as out:
json.dump(vacancy_list, out, ensure_ascii=False)
return len(vacancy_list)
def check_hours(request, query=None):
picked_date = request.GET["datechoosen"]
doctor_id = request.GET["id_doctor"]
all_appointments = appoint_models.Appointment.objects.filter(
date=picked_date, doctor_id=doctor_id)
current_appointments = []
time_list = []
time_to_display = []
for appointment in all_appointments:
if appointment.start_time.hour < 10:
hours = '0' + str(appointment.start_time.hour)
else:
hours = appointment.start_time.hour
if appointment.start_time.minute == 0:
minutes = '00'
else:
minutes = appointment.start_time.minute
current_appointments.append(f'{hours}:{minutes}')
time_range = DateTimeRange("2015-01-01T09:00:00", "2015-01-01T17:00:00")
for value in time_range.range(relativedelta(minutes=30)):
time_list.append(str(value.time())[0:5])
for current_time in time_list:
if current_time not in current_appointments:
time_to_display.append(current_time)
result = {
i: {
"time": time_to_display[i]
}
for i in range(0, len(time_to_display))
}
return JsonResponse(result)
def jobsInDateRange(start, end):
givenRange = DateTimeRange(start, end)
tables = ['Jobs', 'ReviewJobs']
data = []
for table in tables:
query = 'SELECT DateRange, JobID, CountryOfWinner FROM ' + table
cur.execute(query)
results = [list(each) for each in cur.fetchall()]
for job in results:
dateRange = job[0]
d = [each.lstrip().rstrip() for each in dateRange.split("-")]
s = d[0].split("/")
startFormat = str(int(s[2]) + 2000) + "/" + s[1] + "/" + s[0]
inRange = False
endFormat = ''
if len(d) > 1:
e = d[1].split("/")
endFormat = str(int(e[2]) + 2000) + "/" + e[1] + "/" + e[0]
tableRange = DateTimeRange(startFormat, endFormat)
for day in tableRange.range(relativedelta(days=1)):
if day in givenRange:
inRange = True
else:
inRange = startFormat in givenRange
if inRange:
data.append([job[1], job[2]])
return data
def index(request, start_date, end_date):
response = requests.get(
'https://gitlab.com/-/snippets/2094509/raw/master/sample_json_1.json')
data = response.json()
data_ = json.dumps(data)
time_range_2 = DateTimeRange(start_date, end_date)
all_date = []
for value in time_range_2.range(datetime.timedelta(minutes=1)):
(all_date.append(str(value.date()) + ' ' + str(value.time())))
# print(all_date)
shiftA = []
shiftB = []
shiftC = []
shift1 = DateTimeRange(start_date[:start_date.index('T')] + ' ' + '06:00',
start_date[:start_date.index('T')] + ' ' + '14:00')
for i in shift1.range(datetime.timedelta(minutes=1)):
shiftA.append(str(i.date()) + ' ' + str(i.time()))
shift2 = DateTimeRange(start_date[:start_date.index('T')] + ' ' + '14:00',
start_date[:start_date.index('T')] + ' ' + '20:00')
for i in shift2.range(datetime.timedelta(minutes=1)):
shiftB.append(str(i.date()) + ' ' + str(i.time()))
shift3 = DateTimeRange(start_date[:start_date.index('T')] + ' ' + '20:00',
start_date[:start_date.index('T')] + ' ' + '23:59')
# print(shift3)
for i in shift3.range(datetime.timedelta(minutes=1)):
shiftC.append(str(i.date()) + ' ' + str(i.time()))
shift3 = DateTimeRange(end_date[:end_date.index('T')] + ' ' + '00:00',
end_date[:end_date.index('T')] + ' ' + '06:00')
# print(shift3)
for i in shift3.range(datetime.timedelta(minutes=1)):
shiftC.append(str(i.date()) + ' ' + str(i.time()))
# print(shiftC)
res = {}
count_prodA = 0
count_prodB = 0
for i in data:
if i['time'] in all_date:
if i['time'] in shiftA:
if i['production_A'] == True:
# print(i)
count_prodA += 1
for i in data:
if i['time'] in all_date:
if i['time'] in shiftA:
if i['production_B'] == True:
# print(i)
count_prodB += 1
res['shiftA'] = {
'production_A_count': count_prodA,
'production_B_count': count_prodB,
}
# print(res)
count_prodA = 0
count_prodB = 0
for i in data:
if i['time'] in all_date:
if i['time'] in shiftB:
if i['production_A'] == True:
# print(i)
count_prodA += 1
# print(count)
for i in data:
if i['time'] in all_date:
if i['time'] in shiftB:
if i['production_B'] == True:
# print(i)
count_prodB += 1
# print(count)
res['shiftB'] = {
'production_A_count': count_prodA,
'production_B_count': count_prodB,
}
# print(shiftC)
count_prodA = 0
count_prodB = 0
for i in data:
if i['time'] in all_date:
if i['time'] in shiftC:
if i['production_A'] == True:
# print(i)
count_prodA += 1
# print(count)
# print(shiftC)
print('==============')
for i in data:
if i['time'] in all_date:
if i['time'] in shiftC:
if i['production_B'] == True:
# print(i)
count_prodB += 1
# print(count)
res['shiftC'] = {
'production_A_count': count_prodA,
'production_B_count': count_prodB,
}
# print(res)
return JsonResponse(res, safe=False)
def get_grid_geojson(bus_ids,
time_range,
flip_coordinates=True,
stations_source='overpass'):
"""
Generate the grid GeoJson based on the values saved in 'grid_cells' table.
This can be used to overlay it on top of the routes in the jupyter notebooks.
For each hour in the time interval it will generate a grid.
It also maps the bus stations to each cell in order to provide 'buses_count_subset' and
'buses_count_total' in the returned GeoJson, that are the frequency of buses (counted at a single station)
for the given bus_ids in each cell and the frequency of all buses in each cell. This can be used as a ratio
to show the percentage of the subset in terms of max frequencies.
Args:
bus_ids (list): List of the bus ids.
time_range (tuple): Time range in format ('saturday', '10:03', '11:03').
flip_coordinates (bool, optional): Flip the coordinates. Defaults to True.
stations_source (str, optional): The source of the stations' coordinates.
Valid values: 'overpass', 'here'. Defaults to 'overpass'.
Returns:
dict: The dict that represents the GeoJson.
"""
conn = sqlite3.connect(db)
cursor = conn.cursor()
if stations_source == 'overpass':
stmt_buses_subset = f"""SELECT cell_id, substr(time, 0, 3) AS interval, count(*) FROM departures d, stations_cells_overpass sc
WHERE d.station_id = sc.station_id AND bus_id IN ({','.join(['?'] * len(bus_ids))}) AND day = ? AND time BETWEEN ? AND ?
GROUP BY cell_id, interval;"""
stmt_buses_all = f"""SELECT cell_id, substr(time, 0, 3) as interval, count(*) FROM departures d, stations_cells_overpass sc
WHERE d.station_id = sc.station_id AND day = ? AND time BETWEEN ? AND ? GROUP BY cell_id, interval;"""
elif stations_source == 'here':
stmt_buses_subset = f"""SELECT cell_id, substr(time, 0, 3) as interval, count(*) FROM departures d, stations_cells_here sc
WHERE d.station_id = sc.station_id AND bus_id IN ({','.join(['?'] * len(bus_ids))}) AND day = ? AND time BETWEEN ? AND ?
GROUP BY cell_id, interval;"""
stmt_buses_all = f"""SELECT cell_id, substr(time, 0, 3) as interval, count(*) FROM departures d, stations_cells_here sc
WHERE d.station_id = sc.station_id AND day = ? AND time BETWEEN ? AND ? GROUP BY cell_id, interval;"""
else:
cursor.close()
conn.close()
raise Exception('Invalid stations_source!')
buses_count_subset = {}
for cell, interval, count in cursor.execute(
stmt_buses_subset, (*bus_ids, *time_range)).fetchall():
d = {}
d[interval] = count
buses_count_subset.setdefault(cell, {}).update(d)
buses_count_total = {}
for cell, interval, count in cursor.execute(stmt_buses_all,
[*time_range]).fetchall():
d = {}
d[interval] = count
buses_count_total.setdefault(cell, {}).update(d)
geo_json = {
"type": "FeatureCollection",
"properties": {
"time_range":
f"{time_range[0]}: {time_range[1]} - {time_range[2]}",
"bus_ids": bus_ids
},
"features": []
}
tr = DateTimeRange(*time_range[-2:])
stmt = 'SELECT id, x_axis, y_axis, upper_left, upper_right, lower_right, lower_left FROM grid_cells;'
for cell_id, x_axis, y_axis, u_left, u_right, l_right, l_left in cursor.execute(
stmt).fetchall():
coordinates_list = [
list(
map(
float,
u_left.split(',')[::-1]
if flip_coordinates else u_left.split(','))),
list(
map(
float,
u_right.split(',')[::-1]
if flip_coordinates else u_right.split(','))),
list(
map(
float,
l_right.split(',')[::-1]
if flip_coordinates else l_right.split(','))),
list(
map(
float,
l_left.split(',')[::-1]
if flip_coordinates else l_left.split(',')))
]
for time in tr.range(datetime.timedelta(hours=1)):
time_hours = time.strftime('%H')
if cell_id in buses_count_subset and time_hours in buses_count_subset[
cell_id]:
subset = buses_count_subset[cell_id][time_hours]
else:
subset = 0
if cell_id in buses_count_total and time_hours in buses_count_total[
cell_id]:
total = buses_count_total[cell_id][time_hours]
else:
total = 0
perc = subset / total if total else 0
cell_color = plt.cm.get_cmap('Reds')(
perc * 1.5) # 5 - to increase the shade
cell_color = mpl.colors.to_hex(cell_color)
perc = round(perc * 100, 2)
cell = {
"type": "Feature",
"properties": {
"matrix_coordinates": f"({x_axis},{y_axis})",
"buses_count_subset": subset,
"buses_count_total": total,
"popup":
f'({x_axis}, {y_axis}) {subset}/{total} ({perc}%)',
# "fillColor": cell_color,
"style": {
'fillColor': cell_color,
'color': 'black',
'weight': 0.5,
'dashArray': '5',
'fillOpacity': 0.5
},
"time": "2020-10-10T" + time.strftime('%H:%M') + ":00"
},
"geometry": {
"type": "Polygon",
"coordinates": [coordinates_list]
}
}
geo_json['features'].append(cell)
cursor.close()
conn.close()
return geo_json
def get_available_youbike_numbers_dfs_per_weekday(df, weekdays='all'):
'''
df: dataframe
weekdays: all or a list of weekdays, ex: ['Mon', 'Tue']
'''
key_column = '可借車數'
time_range = DateTimeRange("00:00:00", "23:55:00")
index_selectors = []
dfs_dict = {}
start_date = '2018-01-01'
end_date = '2018-06-15'
start_date_dict = {
'Mon': '2018-01-01',
'Tue': '2018-01-02',
'Wed': '2018-01-03',
'Thu': '2018-01-04',
'Fri': '2018-01-05',
'Sat': '2018-01-06',
'Sun': '2018-01-07'
}
if weekdays == 'all':
weekdays = start_date_dict.keys()
for value in time_range.range(relativedelta(minutes=+5)):
time_str_list = str(value).split(' ')[-1].split(':') # XX:XX:XX
time_hour = int(time_str_list[0])
time_min = int(time_str_list[1])
time_sec = int(time_str_list[2])
index_selectors.append(
time(hour=time_hour, minute=time_min, second=time_sec))
thresh = len(index_selectors) * 0.9
for weekday in weekdays:
df_weekday = df[df['星期幾'] == weekday]
df_weekday = df_weekday[[key_column]]
date_range = pd.date_range(start=start_date_dict[weekday],
end=end_date,
freq="7D")
df_new = pd.DataFrame()
for date in date_range:
start_date_ = date
end_date_ = date + DateOffset(days=1)
mask = (df_weekday.index > start_date_) & (df_weekday.index <=
end_date_)
df_ = df_weekday.loc[mask]
df_ = df_.rename(columns={key_column: str(start_date_.date())})
df_.index = df_.index.time
if df_new.empty:
df_new = df_
else:
df_new = pd.concat([df_new, df_], axis=1)
df_new = (df_new.loc[index_selectors].dropna(
axis=1,
thresh=thresh).fillna(method='ffill').fillna(method='bfill'))
dfs_dict[weekday] = df_new
return dfs_dict
def main():
db_conn1 = sqlite3.connect(
r'D:\PythonCodes\vnpy\.vntrader\symb_list.db'
) # Connect to a database that hosts all stock symbols (i.e. corporate database)
db_conn2 = sqlite3.connect(
r'D:\PythonCodes\vnpy\.vntrader\database.db'
) # Connect to the main database that host all stock data (i.e. bar database)
# dict_example = {'name':['Microsoft Corp.'],
# 'cname': ['微软公司'],
# 'symbol':['MSFT']}
# dict_example = {'name':['Microsoft Corp.','Apple Company'],
# 'cname': ['微软公司', '苹果公司'],
# 'symbol':['MSFT', 'AAPL']}
# dict_example = {'name':['Microsoft Corp.','Apple Company', 'Facebook'],
# 'cname': ['微软公司', '苹果公司', '脸书'],
# 'symbol':['MSFT', 'AAPL', 'FB']}
# dict_example = {'name':['Microsoft Corp.','Apple Company', 'Facebook', 'Amazon'],
# 'cname': ['微软公司', '苹果公司', '脸书','亚马逊'],
# 'symbol':['MSFT', 'AAPL', 'FB', 'AMZN']}
# df_example = pd.DataFrame.from_dict(dict_example)
# df_example.to_csv(Path.cwd().joinpath('temp.csv'), encoding='utf_8_sig', index=False)
# df_example = pd.read_csv(Path.cwd().joinpath('temp.csv'), encoding='utf_8_sig')
# df_allstocks = ak.get_us_stock_name() # Download all stock symbols using AkShare service. Expect to run this line and update stock symbols periodically.
# df_allstocks.to_csv(Path.cwd().joinpath('temp.csv'), encoding='utf_8_sig', index=False) # Save all stock symbols to a csv file. This is for testing purpose.
df_example = pd.read_csv(
Path.cwd().joinpath('temp.csv'), encoding='utf_8_sig'
) # Load all stock symbols from the csv file. This is for testing purpose.
# df_example = df_example.iloc[0:2, :] # Only take a few lines for testing. This is for testing purpose.
df_example.to_sql(
"dbcorpdata", db_conn1,
if_exists='replace') # Save all stock symbols to corporate database
df_corpsdata_dl = pd.read_sql_query(
"SELECT * from dbcorpdata",
db_conn1) # Load all stock symbols from corporate database
df_bardata_ex = pd.read_sql_query(
"SELECT * from dbbardata",
db_conn2) # Load all existing stock data from bardata database
totalSymbol = len(df_corpsdata_dl.symbol)
procSymbol = 0
forcedFullLoad = False
for s in df_corpsdata_dl.symbol: # For each symbol read from the corporate database
try:
procSymbol += 1
progress(procSymbol, totalSymbol)
bars = []
bar_latestBarOneStock_ex = database_manager.get_newest_bar_data(
s, Exchange.LOCAL, Interval.DAILY
) # Find the latest bar record for that symbol from the bar database
df_allBarOneStock_dl = ak.stock_us_daily(
symbol=s, adjust="qfq"
).fillna(method='ffill').fillna(
0
) # Download the history data for that symbol using AkShare service.
# Fill NaN or Null fields with previous value, and then zero.
if (
(bar_latestBarOneStock_ex is not None) and (~forcedFullLoad)
): # If the bar database contains this symbol, and not full load we will decide if incremental data will be needed or full history data will be saved to bar database
lastDayDate_ex = bar_latestBarOneStock_ex.datetime.replace(
tzinfo=None
) # VNPY datetime is aware type, but the AkShare datetime is unaware type
latestDayDate_dl = df_allBarOneStock_dl.index[
-1] # Be careful of the difference between last day and latest date.
dailyDataMatched = comp_bar(
bar_latestBarOneStock_ex, df_allBarOneStock_dl
) # This is a simplified logic check to compare the OHLC prices and see if they are all equal.
if dailyDataMatched: # If the close prices from existing and new sources match, we assume data remain correct and will only incrementally update
time_range = DateTimeRange(
lastDayDate_ex, latestDayDate_dl
) # Find the date range for incremental update
for dt in time_range.range(timedelta(days=1)):
# print(dt)
if dt == latestDayDate_dl: # When last date equals latest date, there is still a day in the date range, and we need to break the loop
# print('I am going to break...')
break
bar = BarData(
symbol=s,
exchange=Exchange.LOCAL,
datetime=dt, # Here dt is a native datetime object
interval=Interval.DAILY,
volume=df_allBarOneStock_dl.loc[dt].volume,
open_price=df_allBarOneStock_dl.loc[dt].open,
high_price=df_allBarOneStock_dl.loc[dt].high,
low_price=df_allBarOneStock_dl.loc[dt].low,
close_price=df_allBarOneStock_dl.loc[dt].close,
open_interest=0,
gateway_name='Sim')
bars.append(bar)
# print('only add incremental updates for '+s)
else: # If the close prices from existing and new sources do not match, we assume data are corrupted and will fully update
for i, dt in enumerate(df_allBarOneStock_dl.index):
bar = BarData(
symbol=s,
exchange=Exchange.LOCAL,
datetime=dt.to_pydatetime(
), # Convert to a datetime object
interval=Interval.DAILY,
volume=df_allBarOneStock_dl.loc[dt].volume,
open_price=df_allBarOneStock_dl.loc[dt].open,
high_price=df_allBarOneStock_dl.loc[dt].high,
low_price=df_allBarOneStock_dl.loc[dt].low,
close_price=df_allBarOneStock_dl.loc[dt].close,
open_interest=0,
gateway_name='Sim')
bars.append(bar)
# print('correct database data for '+s)
else: # If bar database does not have this symbol, or just want to force full load, we will fully update
for i, dt in enumerate(df_allBarOneStock_dl.index):
bar = BarData(
symbol=s,
exchange=Exchange.LOCAL,
datetime=dt.to_pydatetime(
), # Convert to a datetime object
interval=Interval.DAILY,
volume=df_allBarOneStock_dl.loc[dt].volume,
open_price=df_allBarOneStock_dl.loc[dt].open,
high_price=df_allBarOneStock_dl.loc[dt].high,
low_price=df_allBarOneStock_dl.loc[dt].low,
close_price=df_allBarOneStock_dl.loc[dt].close,
open_interest=0,
gateway_name='Sim')
bars.append(bar)
# print('reload data for '+s)
database_manager.save_bar_data(
bars) # Push the updates to the bar database
print("Saved stock data of " + s + " into database.")
except: # When exceptoin occurs, assume it is because database buffer full, reconnect databases.
time.sleep(5)
print('Exception detected. Now reconnect to the databases.')
db_conn1.close()
db_conn2.close()
db_conn1 = sqlite3.connect(
r'D:\PythonCodes\vnpy\.vntrader\symb_list.db')
db_conn2 = sqlite3.connect(
r'D:\PythonCodes\vnpy\.vntrader\database.db')
time.sleep(5)
db_conn1.close() # When done with the database, close the connection
db_conn2.close() # When done with the database, close the connection
def apithree(request, start_date, end_date):
response = requests.get(
'https://gitlab.com/-/snippets/2094509/raw/master/sample_json_3.json')
data = response.json()
data_ = json.dumps(data)
time_range_2 = DateTimeRange(start_date, end_date)
all_date = []
for value in time_range_2.range(datetime.timedelta(minutes=1)):
(all_date.append(str(value.date()) + ' ' + str(value.time())))
new_data = []
for d in data:
if d['time'] in all_date:
if d['state'] == False:
d['id'] = int(d['id'][d['id'].index('0') + 1:])
d['belt2'] = 0
new_data.append(d)
if d['state'] == True:
d['belt1'] = 0
d['id'] = int(d['id'][d['id'].index('0') + 1:])
new_data.append(d)
v = {}
for i in new_data:
v[i['id']] = 0
for i in new_data:
if i['id'] in v.keys():
v[i['id']] += i['belt1']
v[i['id']] += i['belt2']
print(v)
s = {}
for i in new_data:
s[i['id']] = 0
for i in new_data:
if i['id'] in s.keys():
s[i['id']] += 1
# v[i['id']]+=1
print(s)
for i in v:
if i in s:
v[i] = (v[i] // s[i])
print(v)
for i in new_data:
if i['id'] in v:
if i['belt1'] != 0:
i['belt1'] = v[i['id']]
# print(new_data)
if i['belt2'] != 0:
i['belt2'] = v[i['id']]
for i in new_data:
print(i)
result_output = []
seen = set()
for i in new_data:
if i['id'] not in seen:
seen.add(i['id'])
result_output.append(i)
for i in result_output:
i.pop('time')
i.pop('state')
i['avg_belt1'] = i.pop('belt1')
i['avg_belt2'] = i.pop('belt2')
result_output.sort(key=lambda k: k['id'])
# print(result_output)
return JsonResponse(result_output, safe=False)
def dateRange(start, end):
rangeList = []
time_range = DateTimeRange(start, end)
for value in time_range.range(datetime.timedelta(days=1)):
rangeList.append(value.strftime('%Y-%m-%d'))
return rangeList
#1. Принимаю от пользователя дату
#2. Составляю расписание раз в 2 дня (через день)
#3. На 30 дней ДД ММ ГГ и день недели
#4. Если это воскресенье, то перенести на понеделтник и опять через день
import datetime
#прошу у пользователся дату
date_entry = input("Введите дату в формате ДД, ММ, ГГГГ ")
#перевожу в формат даты ДД ММ ГГГГ - если ввести формат по-другому, то программа не запустится
dt = datetime.datetime.strptime(date_entry, "%d, %m, %Y")
#вывод списка по дням
#скачать pip DateTimeRange (https://pypi.org/project/DateTimeRange/#get-iterator)
from datetimerange import DateTimeRange
# date_End - финальная дата через 30 дней
date_End = datetime.timedelta(days=30)
time_range = DateTimeRange(dt, dt + date_End)
print("Расписание на месяц: ")
#список выводится через день (days=2)
for value in time_range.range(datetime.timedelta(days=2)):
#проверка на то, что будут выводиться дни с пн до сб
if value.weekday() in range(0, 6):
print(value.strftime("%A, %d %B, %Y"))
def post(self, request):
print("I'm in POST")
print("Request body: ", request.body)
print("Request data: ", request.data)
serializer = ScheduleSerializer(data=request.data, many=True)
list_exceptions = []
list_every = []
if serializer.is_valid():
print("Data is valid")
# serializer.save()
start_day_list = []
end_day_list = []
start_time_list = []
end_time_list = []
for i in range(0, len(serializer.validated_data)):
start_day_list.append(serializer.validated_data[i]['startday'])
end_day_list.append(serializer.validated_data[i]['endday'])
start_time_list.append(serializer.validated_data[i]['starttime'])
end_time_list.append(serializer.validated_data[i]['endtime'])
scheduler.pause()
""" For all days which are given, check if it is ...
... one exception day (e.g. 2019-08-12) or an interval (e.g. 2019-08-12 - 2019-08-14)
... an every day job (e.g. Every Monday
Make a continuous list for all exception days
-> e.g. '2019-11-19 10:10:00 - 2019-11-22 17:15:00', '2019-11-20 05:20:00 - 2019-11-24 21:45:00'
becomes '2019-11-19 10:10:00 - 2019-11-24 21:45:00'
Make a continuous list for all every day jobs
-> e.g Every Monday 8:00 - 24:00 and Every Tuesday 00:00 - 17:00 becomes Mon-Tues 8:00 - 17:00)
In the end:
- Find out if evey day jobs intersect exception jobs
- Make a list of all start and stop times for the every day jobs, so the exception days can run
- Add the jobs to the scheduler
"""
for d in range(0, len(start_day_list)):
if not start_day_list[d].startswith('Every'):
if not end_day_list[d]:
start_date = str(start_day_list[d]) + str(' ') + str(start_time_list[d]) + str(':00')
start_date = datetime.datetime.strptime(start_date, '%Y-%m-%d %H:%M:%S')
# if day ends with 24:00, the end day will be the next day at 00:00
stop_date = str(start_day_list[d]) + str(' ') + str(end_time_list[d]) + str(':00')
stop_date = change_24_to_00(stop_date)
test_range = DateTimeRange(start_date, stop_date)
# check for intersections of time ranges in list
list_exceptions = check_intersect_with_dates_list(list_exceptions, test_range)
else:
start_date = str(start_day_list[d]) + str(' ') + str(start_time_list[d]) + str(':00')
start_date = datetime.datetime.strptime(start_date, '%Y-%m-%d %H:%M:%S')
start_date_interval = str(end_day_list[d]) + str(' ') + str(start_time_list[d]) + str(':00')
# if day ends with 24:00, the end day will be the next day at 00:00
stop_date = str(end_day_list[d]) + str(' ') + str(end_time_list[d]) + str(':00')
stop_date = change_24_to_00(stop_date)
stop_date_interval = str(start_day_list[d]) + str(' ') + str(end_time_list[d]) + str(':00')
stop_date_interval = change_24_to_00(stop_date_interval)
time_range1 = DateTimeRange(start_date, start_date_interval)
time_range2 = DateTimeRange(stop_date_interval, stop_date)
# Go in 1 day steps from start date to end date because
# the start time and end time is valid for every date between the interval days
# check for intersections of time ranges
for i1, j1 in zip(time_range1.range(datetime.timedelta(days=1)),
time_range2.range(datetime.timedelta(days=1))):
test_range = DateTimeRange(i1, j1)
list_exceptions = check_intersect_with_dates_list(list_exceptions, test_range)
if start_day_list[d].startswith('Every'):
list_every = check_intersect_with_every_list(get_day_of_every(start_day_list[d]),
start_time_list[d], end_time_list[d], list_every)
# process List_days for 24:00 entries and change it to "12 am the next day"
if list_every:
for i in range(0, len(list_every)):
if list_every[i][2] == "24:00":
list_every[i] = every_change_24_to_00_end(list_every[i][0], list_every[i][1], list_every[i][2])
list_exceptions = [str(i) for i in list_exceptions]
sorted_exception_list = sorted(list_exceptions)
cron_start_stop, new_list_exceptions = split_time_ranges_and_make_job_list(sorted_exception_list,
list_every)
new_list_exceptions = sorted(list(set(new_list_exceptions)))
add_all_jobs(cron_start_stop, list_every, new_list_exceptions, scheduler)
scheduler.print_jobs()
register_events(scheduler)
scheduler.resume()
return Response(serializer.data, status=status.HTTP_201_CREATED)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
dateRange = job[0]
d = [each.lstrip().rstrip() for each in dateRange.split("-")]
s = d[0].split("/")
startFormat = str(int(s[2]) + 2000) + "/" + s[1] + "/" + s[0]
inRange = False
if len(d) > 1:
e = d[1].split("/")
endFormat = str(int(e[2]) + 2000) + "/" + e[1] + "/" + e[0]
tableRange = DateTimeRange(startFormat, endFormat)
for day in tableRange.range(relativedelta(days=1)):
if day in givenRange:
inRange = True
else:
inRange = startFormat in givenRange
if inRange:
seen += 1
data.append(float(job[1]))
query = "SELECT DateRange, ConvertedFinalCost FROM Jobs WHERE ConvertedFinalCost != 'None' AND Year = 2018"
cur.execute(query)
results = [list(each) for each in cur.fetchall()]
for j in range(len(results)):
job = results[j]
