From f312547044fe1a68aa8f85cb8f821726512911a5 Mon Sep 17 00:00:00 2001 From: SPCH-GL Date: Wed, 26 Jun 2024 12:12:02 +0200 Subject: [PATCH 1/2] 4 fichiers avec mes corrections --- comptages/core/report.py | 159 +++++++++++++++++++------ comptages/core/statistics.py | 72 +++++++++-- comptages/report/template_yearly.xlsx | Bin 186547 -> 187466 bytes comptages/report/yearly_report_bike.py | 105 ++++++++++++++-- 4 files changed, 279 insertions(+), 57 deletions(-) diff --git a/comptages/core/report.py b/comptages/core/report.py index e1b7940..26e601d 100644 --- a/comptages/core/report.py +++ b/comptages/core/report.py @@ -1,11 +1,9 @@ import os from datetime import date, datetime, timedelta -from typing import Generator +from typing import Generator, Optional +from qgis.core import Qgis, QgsMessageLog -from datetime import timedelta, datetime -from typing import Optional from openpyxl import load_workbook, Workbook -from qgis.core import Qgis, QgsMessageLog from comptages.core import statistics from comptages.datamodel import models @@ -24,6 +22,9 @@ def prepare_reports( callback_progress=simple_print_callback, sections_days: Optional[dict[str, list[date]]] = None, ): + print( + f"{datetime.now()}: _prepare_reports: begin, folder: {file_path}" + ) current_dir = os.path.dirname(os.path.abspath(__file__)) if template == "default": @@ -48,6 +49,9 @@ def prepare_reports( ) elif template == "yearly_bike": pass + print( + f"{datetime.now()}: _prepare_reports: ended, folder: {file_path}" + ) def _prepare_default_reports( @@ -58,6 +62,9 @@ def _prepare_default_reports( sections_days: Optional[dict[str, list[date]]] = None, ): """Write default reports to disk (1 per section in count, per week)""" + print( + f"{datetime.now()}: _prepare_default_reports: begin, count: {count}" + ) # We do by section and not by count because of special cases. sections = models.Section.objects.filter( lane__id_installation__count=count @@ -95,6 +102,10 @@ def _prepare_default_reports( workbook.save(filename=output) + print( + f"{datetime.now()}: _prepare_default_reports: ended, count: {count}" + ) + def _prepare_yearly_report( file_path: str, @@ -105,6 +116,9 @@ def _prepare_yearly_report( sections_days: Optional[dict[str, list[date]]] = None, ): """Write default reports to disk (1 per section included in the count)""" + print( + f"{datetime.now()}: _prepare_yearly_report: begin, sections_ids: {sections_ids}" + ) # Get first count to be used as example count_qs = models.Count.objects.filter( id_installation__lane__id_section=sections_ids[0], @@ -113,6 +127,7 @@ def _prepare_yearly_report( ) if not count_qs.exists(): info_str = f"{datetime.now()}: Aucun comptage trouvé pour cette section {sections_ids[0]} et cette année {year}" + print(info_str) QgsMessageLog.logMessage(info_str, "Comptages", Qgis.Warning) return @@ -137,6 +152,10 @@ def _prepare_yearly_report( output = os.path.join(file_path, f"{section.id}_{year}_r.xlsx") workbook.save(filename=output) + print( + f"{datetime.now()}: _prepare_yearly_report: ended, sections_ids: {sections_ids}" + ) + def _mondays_of_count(count: models.Count) -> Generator[date, None, None]: """Generator that return the Mondays of the count""" @@ -247,7 +266,12 @@ def _data_count_yearly( ws["B14"] = lanes[1].direction_desc -def _data_day(count: models.Count, section: models.Section, monday, workbook: Workbook): +def _data_day( + count: models.Count, + section: models.Section, + monday, + workbook: Workbook, +): ws = workbook["Data_day"] # Monthly coefficients @@ -285,6 +309,7 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo section, start=monday + timedelta(days=i), end=monday + timedelta(days=i + 1), + exclude_trash=True, ) for row in df.itertuples(): @@ -300,6 +325,7 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo start=monday + timedelta(days=i), end=monday + timedelta(days=i + 1), direction=1, + exclude_trash=True, ) for row in df.itertuples(): @@ -315,6 +341,7 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo start=monday + timedelta(days=i), end=monday + timedelta(days=i + 1), direction=1, + exclude_trash=True, ) ws.cell(row=row_offset, column=col_offset + i, value=light.get(True, 0)) ws.cell(row=row_offset + 1, column=col_offset + i, value=light.get(False, 0)) @@ -330,6 +357,7 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo start=monday + timedelta(days=i), end=monday + timedelta(days=i + 1), direction=2, + exclude_trash=True, ) for row in df.itertuples(): @@ -345,6 +373,7 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo start=monday + timedelta(days=i), end=monday + timedelta(days=i + 1), direction=2, + exclude_trash=True, ) ws.cell(row=row_offset, column=col_offset + i, value=light.get(True, 0)) ws.cell( @@ -353,15 +382,21 @@ def _data_day(count: models.Count, section: models.Section, monday, workbook: Wo def _data_day_yearly( - count: models.Count, section: models.Section, year: int, workbook: Workbook + count: models.Count, + section: models.Section, + year: int, + workbook: Workbook, ): ws = workbook["Data_day"] # Total (section) row_offset = 69 col_offset = 2 - - df = statistics.get_time_data_yearly(year, section) + df = statistics.get_time_data_yearly( + year, + section, + exclude_trash=True, + ) if df is None: print( @@ -378,7 +413,10 @@ def _data_day_yearly( row_offset = 95 col_offset = 2 df = statistics.get_light_numbers_yearly( - section, start=datetime(year, 1, 1), end=datetime(year + 1, 1, 1) + section, + start=datetime(year, 1, 1), + end=datetime(year + 1, 1, 1), + exclude_trash=True, ) for i in range(7): @@ -396,10 +434,17 @@ def _data_day_yearly( # Direction 1 row_offset = 5 col_offset = 2 - - df = statistics.get_time_data_yearly(year, section, direction=1) + df = statistics.get_time_data_yearly( + year, + section, + direction=1, + exclude_trash=True, + ) if df is None: + print( + f"{datetime.now()}:_data_day_yearly - Pas de données pour cette section:{section}, cette direction:1 et cette année:{year} /!\\/!\\/!\\" + ) return for i in range(7): @@ -411,7 +456,11 @@ def _data_day_yearly( row_offset = 31 col_offset = 2 df = statistics.get_light_numbers_yearly( - section, start=datetime(year, 1, 1), end=datetime(year + 1, 1, 1), direction=1 + section, + start=datetime(year, 1, 1), + end=datetime(year + 1, 1, 1), + direction=1, + exclude_trash=True, ) for i in range(7): @@ -430,8 +479,12 @@ def _data_day_yearly( if len(section.lane_set.all()) == 2: row_offset = 37 col_offset = 2 - - df = statistics.get_time_data_yearly(year, section, direction=2) + df = statistics.get_time_data_yearly( + year, + section, + direction=2, + exclude_trash=True, + ) for i in range(7): day_df = df[df["date"] == i] @@ -446,6 +499,7 @@ def _data_day_yearly( start=datetime(year, 1, 1), end=datetime(year + 1, 1, 1), direction=2, + exclude_trash=True, ) for i in range(7): @@ -469,28 +523,42 @@ def _data_month_yearly( end = datetime(year + 1, 1, 1) # Section - df = statistics.get_month_data(section, start, end) - row_offset = 14 col_offset = 2 + df = statistics.get_month_data( + section, + start, + end, + exclude_trash=True, + ) for col in df.itertuples(): ws.cell(row=row_offset, column=col_offset + col.Index, value=col.tm) # Direction 1 - df = statistics.get_month_data(section, start, end, direction=1) - row_offset = 4 col_offset = 2 + df = statistics.get_month_data( + section, + start, + end, + direction=1, + exclude_trash=True, + ) for col in df.itertuples(): ws.cell(row=row_offset, column=col_offset + col.Index, value=col.tm) # Direction 2 - df = statistics.get_month_data(section, start, end, direction=2) - row_offset = 9 col_offset = 2 + df = statistics.get_month_data( + section, + start, + end, + direction=2, + exclude_trash=True, + ) for col in df.itertuples(): ws.cell(row=row_offset, column=col_offset + col.Index, value=col.tm) @@ -573,8 +641,8 @@ def _data_speed( end=monday + timedelta(days=7), speed_low=range_[0], speed_high=range_[1], + exclude_trash=True, ) - for row in res: ws.cell(row=row_offset + row[0], column=col_offset + i, value=row[1]) @@ -590,6 +658,7 @@ def _data_speed( start=monday, end=monday + timedelta(days=7), v=v, + exclude_trash=True, ) for row in df.itertuples(): ws.cell( @@ -599,9 +668,13 @@ def _data_speed( # Average speed direction 1 row_offset = 5 col_offset = 19 - df = statistics.get_average_speed_by_hour( - count, section, direction=1, start=monday, end=monday + timedelta(days=7) + count, + section, + direction=1, + start=monday, + end=monday + timedelta(days=7), + exclude_trash=True, ) for row in df.itertuples(): ws.cell(row=row_offset + row.Index, column=col_offset, value=row.speed) @@ -619,8 +692,8 @@ def _data_speed( end=monday + timedelta(days=7), speed_low=range_[0], speed_high=range_[1], + exclude_trash=True, ) - for row in res: ws.cell(row=row_offset + row[0], column=col_offset + i, value=row[1]) @@ -636,6 +709,7 @@ def _data_speed( start=monday, end=monday + timedelta(days=7), v=v, + exclude_trash=True, ) for row in df.itertuples(): ws.cell( @@ -647,9 +721,13 @@ def _data_speed( # Average speed direction 2 row_offset = 33 col_offset = 19 - df = statistics.get_average_speed_by_hour( - count, section, direction=2, start=monday, end=monday + timedelta(days=7) + count, + section, + direction=2, + start=monday, + end=monday + timedelta(days=7), + exclude_trash=True, ) for row in df.itertuples(): ws.cell(row=row_offset + row.Index, column=col_offset, value=row.speed) @@ -708,8 +786,8 @@ def _data_speed_yearly( end=end, speed_low=range_[0], speed_high=range_[1], + exclude_trash=True, ) - for row in res: ws.cell(row=row_offset + row[0], column=col_offset + i, value=row[1]) @@ -719,7 +797,13 @@ def _data_speed_yearly( col_offset = 16 for i, v in enumerate(characteristic_speeds): df = statistics.get_characteristic_speed_by_hour( - None, section, direction=1, start=start, end=end, v=v + None, + section, + direction=1, + start=start, + end=end, + v=v, + exclude_trash=True, ) for row in df.itertuples(): ws.cell( @@ -729,13 +813,13 @@ def _data_speed_yearly( # Average speed direction 1 row_offset = 5 col_offset = 19 - df = statistics.get_average_speed_by_hour( - count, + None, section, direction=1, start=start, end=end, + exclude_trash=True, ) for row in df.itertuples(): ws.cell(row=row_offset + row.Index, column=col_offset, value=row.speed) @@ -746,13 +830,14 @@ def _data_speed_yearly( col_offset = 2 for i, range_ in enumerate(speed_ranges): res = statistics.get_speed_data_by_hour( - count, + None, section, direction=2, start=start, end=end, speed_low=range_[0], speed_high=range_[1], + exclude_trash=True, ) for row in res: @@ -764,7 +849,13 @@ def _data_speed_yearly( col_offset = 16 for i, v in enumerate(characteristic_speeds): df = statistics.get_characteristic_speed_by_hour( - count, section, direction=2, start=start, end=end, v=v + None, + section, + direction=2, + start=start, + end=end, + v=v, + exclude_trash=True, ) for row in df.itertuples(): ws.cell( @@ -776,13 +867,13 @@ def _data_speed_yearly( # Average speed direction 2 row_offset = 33 col_offset = 19 - df = statistics.get_average_speed_by_hour( - count, + None, section, direction=2, start=start, end=end, + exclude_trash=True, ) for row in df.itertuples(): ws.cell(row=row_offset + row.Index, column=col_offset, value=row.speed) diff --git a/comptages/core/statistics.py b/comptages/core/statistics.py index 2c19377..b04384a 100644 --- a/comptages/core/statistics.py +++ b/comptages/core/statistics.py @@ -1,9 +1,9 @@ from typing import Any -from pandas import DataFrame, cut from functools import reduce from datetime import timedelta, datetime -from pytz import timezone +from pandas import DataFrame, cut +from pytz import timezone from django.db.models import F, CharField, Value, Q, Sum, QuerySet from django.db.models.functions import ExtractHour, Trunc, Concat @@ -11,8 +11,6 @@ from comptages.core import utils from comptages.datamodel import models -TZ = timezone("Europe/Zurich") - def get_time_data( count, @@ -57,16 +55,24 @@ def get_time_data( .annotate(thm=Sum("times")) .values("import_status", "date", "hour", "thm") ) + print( + f"statistics.py : get_time_data - qs.query={str(qs.query)}" + ) df = DataFrame.from_records(qs) if not df.empty: df["date"] = df["date"].dt.strftime("%a %d.%m.%Y") df["import_status"].replace({0: "Existant", 1: "Nouveau"}, inplace=True) + return df def get_time_data_yearly( - year, section: models.Section, lane=None, direction=None + year, + section: models.Section, + lane=None, + direction=None, + exclude_trash=False, ) -> DataFrame: """Vehicles by hour and day of the week""" start = datetime(year, 1, 1) @@ -82,6 +88,9 @@ def get_time_data_yearly( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if lane is not None: qs = qs.filter(id_lane=lane) @@ -107,6 +116,9 @@ def get_time_data_yearly( print( f"statistics.py : get_time_data_yearly - Nothing found !!! for Year: {year}. Section: {section}. Lane: {lane}. Direction: {direction}. !!!)" ) + print( + f"statistics.py : get_time_data_yearly - qsa.query={str(qs.query)}" + ) df = DataFrame.from_records(qs) if not df.empty: @@ -162,7 +174,7 @@ def get_day_data( .annotate(tj=Sum("times")) .values("date", "tj", "import_status") ) - print(f"statistics.py : get_day_data - qs.query=", str(qs.query)) + print(f"statistics.py : get_day_data - qs.query={str(qs.query)}") df = DataFrame.from_records(qs) mean = 0 @@ -212,7 +224,9 @@ def get_category_data( .order_by("cat_code") .values("cat_name", "cat_code", "cat_name_code", "value") ) - print(f"statistics.py : get_category_data - qs.query={str(qs.query)}") + print( + f"statistics.py : get_category_data - qs.query={str(qs.query)}" + ) df = DataFrame.from_records(qs) return df @@ -290,6 +304,7 @@ def get_light_numbers( direction=None, start=None, end=None, + exclude_trash=False, ) -> dict: if not start: start = count.start_process_date @@ -305,6 +320,9 @@ def get_light_numbers( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if lane is not None: qs = qs.filter(id_lane=lane) @@ -325,7 +343,12 @@ def get_light_numbers( def get_light_numbers_yearly( - section: models.Section, lane=None, direction=None, start=None, end=None + section: models.Section, + lane=None, + direction=None, + start=None, + end=None, + exclude_trash=False, ) -> DataFrame: qs = models.CountDetail.objects.filter( id_lane__id_section=section, @@ -334,6 +357,9 @@ def get_light_numbers_yearly( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if lane is not None: qs = qs.filter(id_lane=lane) @@ -359,6 +385,7 @@ def get_speed_data_by_hour( end=None, speed_low=0, speed_high=15, + exclude_trash=False, ) -> "ValuesQuerySet[models.CountDetail, Any]": if not start: start = count.start_process_date @@ -374,6 +401,9 @@ def get_speed_data_by_hour( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if count is not None: qs = qs.filter(id_count=count) @@ -403,6 +433,7 @@ def get_characteristic_speed_by_hour( start=None, end=None, v=0.15, + exclude_trash=False, ) -> DataFrame: if not start: start = count.start_process_date @@ -417,6 +448,9 @@ def get_characteristic_speed_by_hour( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if count is not None: qs = qs.filter(id_count=count) @@ -450,6 +484,7 @@ def get_average_speed_by_hour( start=None, end=None, v=0.15, + exclude_trash=False, ) -> DataFrame: if not start: start = count.start_process_date @@ -464,6 +499,9 @@ def get_average_speed_by_hour( timestamp__lt=end, ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if count is not None: qs = qs.filter(id_count=count) @@ -541,7 +579,12 @@ def get_special_periods(first_day, last_day) -> QuerySet[models.SpecialPeriod]: return qs -def get_month_data(section: models.Section, start, end, direction=None) -> DataFrame: +def get_month_data( + section: models.Section, + start, end, + direction=None, + exclude_trash=False, +) -> DataFrame: qs = models.CountDetail.objects.filter( id_lane__id_section=section, timestamp__gte=start, timestamp__lt=end ) @@ -554,6 +597,9 @@ def get_month_data(section: models.Section, start, end, direction=None) -> DataF .values("month", "tm", "import_status") ) + if exclude_trash: + qs = qs.exclude(id_category__trash=True) + if direction is not None: qs = qs.filter(id_lane__direction=direction) @@ -569,8 +615,9 @@ def get_valid_days(year: int, section: models.Section) -> int: where a day is deemed valid just in case there are at least 14 1-hour blocks between 6pm and 4pm with at least 1 vehicle. """ - start = TZ.localize(datetime(year, 1, 1)) - end = TZ.localize(datetime(year + 1, 1, 1)) + tz = timezone("Europe/Zurich") + start = tz.localize(datetime(year, 1, 1)) + end = tz.localize(datetime(year + 1, 1, 1)) iterator = ( models.CountDetail.objects.filter( id_lane__id_section=section, @@ -584,6 +631,9 @@ def get_valid_days(year: int, section: models.Section) -> int: .order_by("date") .values("date", "hour", "tj") ) + print( + f"statistics.py : get_valid_days - iterator.query={str(iterator.query)}" + ) def count_valid_blocks(acc: dict, item: dict) -> dict[str, int]: date = item["date"] diff --git a/comptages/report/template_yearly.xlsx b/comptages/report/template_yearly.xlsx index 3aea05e5b8d87fca15b87b02cc97de0a906a8e92..8de2ff9dee84ff033015063a5b9ae8f21a641523 100644 GIT binary patch delta 99560 zcmb5VbwE|y*EI}C3P^W~fOHB-cXuDU8$n6QEuB(_M!G|~TaoTA3F+>Teh>N!?|ts` ze((2(xY>KHvBnx>&bjA4XH!*y+*glWp8o7AZ|n!nYv~qCyze-Jy!|r_Gr_@+TlJ%L#9-Gnb&XJ?+}`lb3elPH?=bpz4- 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2tSs>(BIb5ZiPn7j*|a62j@0Jj13?aK2Vb{ z$w>eYxIlCbwN_9obwidLbke9{xS5m>Ssd`2f0RsT(4nLQK>Q$hiHk z_rYz$QsC4MNQJBOYrOX_Ix4DoVek!Ts^4EhJg{FTH9I`r39)nClIIXJ5TK%>6QuqF zRw_h+K?Fz&k~s^j4MLpo9Rh@g-2j2)v?-j=ps`C~=eibb+X*2cg>w|PS|?z83waq) z*oHb}b_x?_4}7~5Vo5os#{$0L@b}AG7iR8))Swzu*q{qK40m>e8NQx}KTARE@J2Tv zm%0GwyIsnlEdnm>f1j{Y%Y(J`?j9~mDH)Js1E(D8u|UwRWdBaCw>pS zMF8rbN%&p;h(@It9$z54@cS2o!gNqCoh~J#bh*#InmXBBKbtL9#6ICdGuO0Jlq? zPVpYavYSa1Hv0guEY{#;=6_pOkxYTPl3)*ZSLnP11{43E18PzzutoseB6ko8>;MMY(jM@0qRetR`^QKW^DVEa$F>?vfXqN>#W6Q(jtfwhxhCXbTh zvUsSd(use<(4Q$Vh9LkmNMg#45~ZRNVyFIN(htmV6cIwe`a{5;drENB5F~gwCS2K? zfS{sE_M)a@`b|SBssL4Ls!N_y0f8Z&&H*rA7sLk74nb%dM>A^J&K#^r!7i|QaN1M< zo?8-j@JS*h#HEf2xLXaDw~pDL%Eq~pv=E~$czNpd1YAvo*dgy=iej%ogUhmhZ|fW2 z4LAKiM@D8)V1myfcFM!D;gjGJf{RFecGv?nxX6#**iS`e;q+%Au_aJo)g;)z?ppXS zvrWb+unp2IcLETp zAy{S)P`ZzV`{%zO{=^+(Amh+5#|Wq*yn^tl5l}GpO2Dk6VDPOGK)`;V*{*QkBy=1qc}QW# xkQ64*pVtK69fy=DW3wJpq-9O~-JQ}x8Q?n((Xr9)Ci%k%{IG)f;-5gE^?y+m-TMFl diff --git a/comptages/report/yearly_report_bike.py b/comptages/report/yearly_report_bike.py index 9eea11b..a295b6d 100644 --- a/comptages/report/yearly_report_bike.py +++ b/comptages/report/yearly_report_bike.py @@ -5,24 +5,24 @@ from decimal import Decimal from qgis.core import Qgis, QgsMessageLog -from django.db.models import Sum, F, Avg # , Count, ExpressionWrapper +from openpyxl import load_workbook +from django.db.models import Sum, F, Avg from django.db.models.functions import ( ExtractHour, ExtractIsoWeekDay, ExtractMonth, TruncDate, ) -from openpyxl import load_workbook -from comptages.core import definitions, utils # , statistics +from comptages.core import definitions, utils from comptages.datamodel.models import ( CountDetail, Section, Lane, ClassCategory, Category, + Count as modelCount, ) -from comptages.datamodel.models import Count as modelCount class YearlyReportBike: @@ -33,7 +33,6 @@ def __init__(self, path_to_output_dir, year, section_id, classtxt): self.year = year self.section_id = section_id self.classtxt = classtxt - # Assuming seasons to run from 21 to 20 -> month20 = (date - timedelta(days=20)).month self.seasons = { "printemps": [3, 4, 5], "été": [6, 7, 8], @@ -78,6 +77,9 @@ def tjms_by_weekday_category( .annotate(tjm=Sum("times")) .values("weekday", "id_category__code", "tjm") ) + print( + f"yearly_report_bike.py: tjms_by_weekday_category - results.query:{str(results.query)}" + ) return results def tjms_by_weekday_hour(self) -> "ValuesQuerySet[CountDetail, dict[str, Any]]": @@ -98,11 +100,17 @@ def tjms_by_weekday_hour(self) -> "ValuesQuerySet[CountDetail, dict[str, Any]]": .values("date") .annotate(tj=Sum("times")) .values("date", "tj") - .annotate(weekday=ExtractIsoWeekDay("date"), hour=ExtractHour("timestamp")) + .annotate( + weekday=ExtractIsoWeekDay("date"), + hour=ExtractHour("timestamp"), + ) .values("weekday", "hour") .annotate(tjm=Avg("tj")) .values("weekday", "hour", "tjm") ) + print( + f"yearly_report_bike.py : tjms_by_weekday_hour - results.query:{str(results.query)}" + ) return results def total_runs_by_hour_and_direction( @@ -127,6 +135,9 @@ def total_runs_by_hour_and_direction( ) .values("runs", "hour", "direction", "section") ) + print( + f"yearly_report_bike.py : total_runs_by_hour_and_direction - results.query:{str(results.query)}" + ) def partition(acc: dict, val: dict) -> dict: hour = val["hour"] @@ -159,6 +170,9 @@ def total_runs_by_hour_one_direction(self, direction: int) -> dict[int, Any]: .annotate(day=ExtractIsoWeekDay("timestamp")) .order_by("day") ) + print( + f"yearly_report_bike.py : total_runs_by_hour_one_direction - results.query:{str(results.query)}" + ) def reducer(acc: dict, val: dict) -> dict: day = val["day"] @@ -192,6 +206,9 @@ def total_runs_by_hour_weekday_one_direction( .annotate(day=ExtractIsoWeekDay("timestamp")) .order_by("day") ) + print( + f"yearly_report_bike.py : total_runs_by_hour_weekday_one_direction - results.query:{str(results.query)}" + ) return results def tjms_by_weekday_and_month( @@ -218,6 +235,9 @@ def tjms_by_weekday_and_month( .annotate(month=ExtractMonth("timestamp")) .values("week_day", "month", "daily_runs") ) + print( + f"yearly_report_bike.py : tjms_by_weekday_and_month - results.query:{str(results.query)}" + ) # FIXME # Aggregation via `values()` into `annotate()` all the way to the end result would be more performant. @@ -291,6 +311,7 @@ def nb_weekday_by_month(self) -> "ValuesQuerySet[CountDetail, dict[str, Any]]": month=ExtractMonth("timestamp"), week_day=ExtractIsoWeekDay("timestamp") ) .values("date", "month", "week_day") + # .order_by("date") ) print( f"yearly_report_bike.py : nb_weekday_by_month - results.query:{str(results.query)}" @@ -325,6 +346,10 @@ def total_runs_by_day(self) -> "ValuesQuerySet[CountDetail, dict[str, Any]]": .values("date") .annotate(daily_runs=Sum("times")) .values("date", "daily_runs") + # .order_by("date") + ) + print( + f"yearly_report_bike.py : total_runs_by_day - results.query:{str(results.query)}" ) return results @@ -364,6 +389,7 @@ def tjms_total_runs_by_day_of_week(self) -> dict[str, Any]: builder[item["week_day"]]["runs"] / builder[item["week_day"]]["days"] ) + return builder def total_runs_by_class(self) -> dict[str, Any]: @@ -380,6 +406,9 @@ def total_runs_by_class(self) -> dict[str, Any]: .annotate(runs=Sum("times"), code=F("id_category__code")) .values("day", "runs", "code") ) + print( + f"yearly_report_bike.py : total_runs_by_class - results.query:{str(results.query)}" + ) def reducer(acc: dict, i: dict): code = i["code"] @@ -407,6 +436,9 @@ def tjms_by_direction_bike( ) assert qs.exists() results = qs.aggregate(res=Sum("times"))["res"] + print( + f"yearly_report_bike.py : tjms_by_direction_bike - results.query:{str(results.query)}" + ) # TODO: avoid the division? return results / 365 @@ -417,6 +449,10 @@ def total(self, categories=[1]) -> float: import_status=definitions.IMPORT_STATUS_DEFINITIVE, ) results = qs.aggregate(res=Sum("times"))["res"] + print( + f"yearly_report_bike.py : total - results.query:{str(results.query)}" + ) + return results def max_day(self, categories=[1]) -> tuple[str, Any]: @@ -431,6 +467,9 @@ def max_day(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("-total") ) + print( + f"yearly_report_bike.py : max_day - qs.query:{str(qs.query)}" + ) return qs[0]["total"], qs[0]["date"] @@ -446,6 +485,9 @@ def max_month(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("-total") ) + print( + f"yearly_report_bike.py : max_month - qs.query:{str(qs.query)}" + ) return qs[0]["total"], qs[0]["month"] @@ -461,6 +503,9 @@ def min_month(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("total") ) + print( + f"yearly_report_bike.py : min_month - qs.query:{str(qs.query)}" + ) return qs[0]["total"], qs[0]["month"] @@ -477,12 +522,19 @@ def count_details_by_various_criteria( .exclude(id_category__name__in=categories_name_to_exclude) .values_list("id_category", flat=True) ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - categories_ids.query:{str(categories_ids.query)}" + ) + # Base QuerySet base_qs = CountDetail.objects.filter( id_count=count.id, id_category__in=categories_ids, timestamp__year=self.year, ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - base_qs.query:{str(base_qs.query)}" + ) # Specialized QuerySets total_runs_in_year = ( @@ -490,15 +542,21 @@ def count_details_by_various_criteria( .values("category_name") .annotate(value=Sum("times")) ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - total_runs_in_year.query:{str(total_runs_in_year.query)}" + ) busy_date = ( base_qs.annotate( - date=TruncDate("timestamp"), category_name=F("id_category__name") + date=TruncDate("timestamp"), ) - .values("date", "category_name") + .values("date") .annotate(value=Sum("times")) .order_by("-value") ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - busy_date.query:{str(busy_date.query)}" + ) busiest_date = busy_date.first() least_busy_date = busy_date.last() @@ -513,6 +571,9 @@ def count_details_by_various_criteria( .values("date", "category_name") .annotate(value=Sum("times")) ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - busiest_date_row.query:{str(busiest_date_row.query)}" + ) least_busy_date_row = ( base_qs.annotate( @@ -522,6 +583,9 @@ def count_details_by_various_criteria( .values("date", "category_name") .annotate(value=Sum("times")) ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - least_busy_date_row.query:{str(least_busy_date_row.query)}" + ) busy_month = ( base_qs.annotate(month=ExtractMonth("timestamp")) @@ -529,6 +593,9 @@ def count_details_by_various_criteria( .annotate(value=Sum("times")) .order_by("-value") ) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - busy_month.query:{str(busy_month.query)}" + ) busiest_month = busy_month.first() least_busy_month = busy_month.last() @@ -563,8 +630,12 @@ def count_details_by_various_criteria( .annotate(value=Sum("times")) .order_by("-value") ) + total_runs_busiest_hour_weekday = busiest_hour.exclude(week_day__gt=5) total_runs_busiest_hour_weekend = busiest_hour.exclude(week_day__lt=6) + print( + f"yearly_report_bike.py : count_details_by_various_criteria - busiest_weekend_hour.query:{str(total_runs_busiest_hour_weekend.query)}" + ) busiest_weekday = total_runs_busiest_hour_weekday.first() busiest_weekend = total_runs_busiest_hour_weekend.first() @@ -592,6 +663,7 @@ def count_details_by_various_criteria( def count_details_by_season(self, count_id) -> dict[int, Any]: """Break down count details by season x section x class""" + # Assuming seasons to run from 21 to 20 -> month20 = (date - timedelta(days=20)).month # Preparing to filter out categories that don't reference the class picked out by `class_name` class_name = self.classtxt # Excluding irrelevant @@ -616,6 +688,9 @@ def count_details_by_season(self, count_id) -> dict[int, Any]: .annotate(value=Sum("times")) .values("date", "category_name", "value") ) + print( + f"yearly_report_bike.py : count_details_by_season - count_details.query:{str(count_details.query)}" + ) # Preparing to collect data def reducer(acc: dict, detail) -> dict: @@ -703,9 +778,16 @@ def get_category_data_by_dow( .values("week_day", "value") .values_list("week_day", "value") ) + print( + f"yearly_report_bike.py : get_category_data_by_dow - qs.query={str(qs.query)}" + ) + return qs def run(self): + print( + f"{datetime.now()}: YRB_run - begin... ({self.path_to_output_dir})" + ) current_dir = path.dirname(path.abspath(__file__)) template = path.join(current_dir, "template_yearly_bike.xlsx") workbook = load_workbook(filename=template) @@ -728,10 +810,8 @@ def render_section_dist(value: Union[str, Decimal, None]) -> str: section_start_dist = render_section_dist(section.start_dist) section_end_dist = render_section_dist(section.end_dist) - ws[ - "B3" - ] = f""" - Poste de comptage : {section.id} + ws["B3"] = f""" + Poste de comptage : {section.id} Axe : {section.owner}:{section.road}{section.way} PR {section.start_pr} + {section_start_dist} m à PR {section.end_pr} + {section_end_dist} m """ @@ -1000,5 +1080,6 @@ def render_section_dist(value: Union[str, Decimal, None]) -> str: output = path.join( self.path_to_output_dir, "{}_{}_r.xlsx".format(self.section_id, self.year) ) + workbook.save(filename=output) print(f"{datetime.now()}: YRB_run - end: Saved report to {output}") From d40fbdb7427f684706fb687f2255274dbf84678a Mon Sep 17 00:00:00 2001 From: maltaesousa Date: Wed, 26 Jun 2024 15:53:26 +0200 Subject: [PATCH 2/2] run black --- comptages/core/report.py | 16 ++++------------ comptages/core/statistics.py | 19 ++++++------------- comptages/report/yearly_report_bike.py | 24 ++++++++---------------- 3 files changed, 18 insertions(+), 41 deletions(-) diff --git a/comptages/core/report.py b/comptages/core/report.py index 26e601d..8091bb5 100644 --- a/comptages/core/report.py +++ b/comptages/core/report.py @@ -22,9 +22,7 @@ def prepare_reports( callback_progress=simple_print_callback, sections_days: Optional[dict[str, list[date]]] = None, ): - print( - f"{datetime.now()}: _prepare_reports: begin, folder: {file_path}" - ) + print(f"{datetime.now()}: _prepare_reports: begin, folder: {file_path}") current_dir = os.path.dirname(os.path.abspath(__file__)) if template == "default": @@ -49,9 +47,7 @@ def prepare_reports( ) elif template == "yearly_bike": pass - print( - f"{datetime.now()}: _prepare_reports: ended, folder: {file_path}" - ) + print(f"{datetime.now()}: _prepare_reports: ended, folder: {file_path}") def _prepare_default_reports( @@ -62,9 +58,7 @@ def _prepare_default_reports( sections_days: Optional[dict[str, list[date]]] = None, ): """Write default reports to disk (1 per section in count, per week)""" - print( - f"{datetime.now()}: _prepare_default_reports: begin, count: {count}" - ) + print(f"{datetime.now()}: _prepare_default_reports: begin, count: {count}") # We do by section and not by count because of special cases. sections = models.Section.objects.filter( lane__id_installation__count=count @@ -102,9 +96,7 @@ def _prepare_default_reports( workbook.save(filename=output) - print( - f"{datetime.now()}: _prepare_default_reports: ended, count: {count}" - ) + print(f"{datetime.now()}: _prepare_default_reports: ended, count: {count}") def _prepare_yearly_report( diff --git a/comptages/core/statistics.py b/comptages/core/statistics.py index b04384a..d20f4d7 100644 --- a/comptages/core/statistics.py +++ b/comptages/core/statistics.py @@ -55,9 +55,7 @@ def get_time_data( .annotate(thm=Sum("times")) .values("import_status", "date", "hour", "thm") ) - print( - f"statistics.py : get_time_data - qs.query={str(qs.query)}" - ) + print(f"statistics.py : get_time_data - qs.query={str(qs.query)}") df = DataFrame.from_records(qs) if not df.empty: @@ -116,9 +114,7 @@ def get_time_data_yearly( print( f"statistics.py : get_time_data_yearly - Nothing found !!! for Year: {year}. Section: {section}. Lane: {lane}. Direction: {direction}. !!!)" ) - print( - f"statistics.py : get_time_data_yearly - qsa.query={str(qs.query)}" - ) + print(f"statistics.py : get_time_data_yearly - qsa.query={str(qs.query)}") df = DataFrame.from_records(qs) if not df.empty: @@ -224,9 +220,7 @@ def get_category_data( .order_by("cat_code") .values("cat_name", "cat_code", "cat_name_code", "value") ) - print( - f"statistics.py : get_category_data - qs.query={str(qs.query)}" - ) + print(f"statistics.py : get_category_data - qs.query={str(qs.query)}") df = DataFrame.from_records(qs) return df @@ -581,7 +575,8 @@ def get_special_periods(first_day, last_day) -> QuerySet[models.SpecialPeriod]: def get_month_data( section: models.Section, - start, end, + start, + end, direction=None, exclude_trash=False, ) -> DataFrame: @@ -631,9 +626,7 @@ def get_valid_days(year: int, section: models.Section) -> int: .order_by("date") .values("date", "hour", "tj") ) - print( - f"statistics.py : get_valid_days - iterator.query={str(iterator.query)}" - ) + print(f"statistics.py : get_valid_days - iterator.query={str(iterator.query)}") def count_valid_blocks(acc: dict, item: dict) -> dict[str, int]: date = item["date"] diff --git a/comptages/report/yearly_report_bike.py b/comptages/report/yearly_report_bike.py index a295b6d..0206b4b 100644 --- a/comptages/report/yearly_report_bike.py +++ b/comptages/report/yearly_report_bike.py @@ -449,9 +449,7 @@ def total(self, categories=[1]) -> float: import_status=definitions.IMPORT_STATUS_DEFINITIVE, ) results = qs.aggregate(res=Sum("times"))["res"] - print( - f"yearly_report_bike.py : total - results.query:{str(results.query)}" - ) + print(f"yearly_report_bike.py : total - results.query:{str(results.query)}") return results @@ -467,9 +465,7 @@ def max_day(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("-total") ) - print( - f"yearly_report_bike.py : max_day - qs.query:{str(qs.query)}" - ) + print(f"yearly_report_bike.py : max_day - qs.query:{str(qs.query)}") return qs[0]["total"], qs[0]["date"] @@ -485,9 +481,7 @@ def max_month(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("-total") ) - print( - f"yearly_report_bike.py : max_month - qs.query:{str(qs.query)}" - ) + print(f"yearly_report_bike.py : max_month - qs.query:{str(qs.query)}") return qs[0]["total"], qs[0]["month"] @@ -503,9 +497,7 @@ def min_month(self, categories=[1]) -> tuple[str, Any]: .annotate(total=Sum("times")) .order_by("total") ) - print( - f"yearly_report_bike.py : min_month - qs.query:{str(qs.query)}" - ) + print(f"yearly_report_bike.py : min_month - qs.query:{str(qs.query)}") return qs[0]["total"], qs[0]["month"] @@ -785,9 +777,7 @@ def get_category_data_by_dow( return qs def run(self): - print( - f"{datetime.now()}: YRB_run - begin... ({self.path_to_output_dir})" - ) + print(f"{datetime.now()}: YRB_run - begin... ({self.path_to_output_dir})") current_dir = path.dirname(path.abspath(__file__)) template = path.join(current_dir, "template_yearly_bike.xlsx") workbook = load_workbook(filename=template) @@ -810,7 +800,9 @@ def render_section_dist(value: Union[str, Decimal, None]) -> str: section_start_dist = render_section_dist(section.start_dist) section_end_dist = render_section_dist(section.end_dist) - ws["B3"] = f""" + ws[ + "B3" + ] = f""" Poste de comptage : {section.id} Axe : {section.owner}:{section.road}{section.way} PR {section.start_pr} + {section_start_dist} m à PR {section.end_pr} + {section_end_dist} m