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How to use add_selector method in autotest
Best Python code snippet using autotest_python
data_base_manager.py
Source:data_base_manager.py 
...18 Renvoie le dataframe contenant l'id, le groupe et le mot de passe associer a chaque utilisateur19 """20 request = (21 Request(distinct=True)22 .add_selector("client.{}".format(config["table"]["client"]["groupe"]), "id")23 .add_selector(24 "client.{}".format(config["table"]["client"]["mot_de_passe"]), "pwd"25 )26 .add_table(config["table"]["client"]["nom_table"], "client")27 .add_condition(28 Condition("client.{} = 1".format(config["table"]["client"]["acces"]), "AND")29 )30 )31 data: pd.DataFrame = request.run(conn2)32 return data33# DEPRECIATED34def get_client_name_from_ref(ref: str) -> str:35 """Documentation36 A partir d'un ref client renvoie l'Intitule du client correspondant37 Parametre:38 ref: référence du client39 Sortie:40 L'intitule du client41 """42 data: pd.DataFrame = pd.read_sql_query(43 "select client.[NOM CLIENT FACTURE] NOM from "44 + config["table"]["client"]["nom_table"]45 + " client "46 + " where '"47 + ref48 + "' = client.[N° CLIENT FACTURE]",49 conn2,50 )51 if len(list(data["NOM"])) == 0:52 print(53 "ERROR client pas dans la table permettant les jointures (ref: " + ref + ")"54 )55 return None56 return str(list(data["NOM"])[0])57def get_id_cpt(58 client: Union[str, None] = None,59 type_energie: Union[str, None] = None,60 name_bat: Union[str, None] = None,61 group: Union[str, None] = None,62) -> List[str]:63 """Documentation64 Parametre:65 client: l'intitule du client ([NOM CLIENT FACTURE]), du compte connecté s'il doit être restreint66 Sortie:67 la liste des id des compteurs68 """69 if client is None and type_energie is None and name_bat is None and group is None:70 request = (71 Request(distinct=True)72 .add_selector(73 "histo.{}".format(config["table"]["histo"]["id_cpt"]), "Id_CPT"74 )75 .add_table(config["table"]["histo"]["nom_table"], "histo")76 .set_order_by("Id_CPT")77 )78 data: pd.DataFrame = request.run(conn)79 return list(data["Id_CPT"])80 request = (81 Request(distinct=True)82 .add_selector("cpt.{}".format(config["table"]["compteur"]["id_cpt"]), "Id_CPT")83 .add_table(config["table"]["compteur"]["nom_table"], "cpt")84 .set_order_by("Id_CPT")85 )86 if client is not None or group is not None:87 # Lien entre la table cpt et client88 request.add_table(89 config["table"]["client"]["nom_table"], "client"90 ).add_condition(91 Condition(92 "cpt.{} = client.{}".format(93 config["table"]["compteur"]["id_client"],94 config["table"]["client"]["id"],95 ),96 "AND",97 ),98 )99 # Condition sur le groupe100 if group is not None:101 request.add_condition(102 Condition(103 "client.{} = '{}'".format(config["table"]["client"]["groupe"], group),104 "AND",105 )106 )107 # Condition sur le client108 if client is not None:109 request.add_condition(110 Condition(111 "client.{} = '{}'".format(config["table"]["client"]["nom"], client),112 "AND",113 )114 )115 # Condition sur le type d'énergie116 if type_energie is not None:117 request.add_condition(118 Condition(119 "cpt.{} = '{}'".format(120 config["table"]["compteur"]["type_energie"], type_energie121 ),122 "AND",123 )124 )125 if name_bat is not None:126 # Jointure des tables batiment et compteur127 # request.add_table(config["table"]["batiment"]["nom_table"], "bat")128 # request.add_condition(129 # Condition(130 # "cpt.{} = bat.{}".format(131 # config["table"]["compteur"]["nom_batiment"],132 # config["table"]["batiment"]["nom"],133 # ),134 # "AND",135 # )136 # )137 request.add_condition(138 Condition(139 "cpt.{} = '{}'".format(140 config["table"]["compteur"]["nom_batiment"], name_bat141 )142 )143 )144 data: pd.DataFrame = request.run(conn2)145 return list(data["Id_CPT"])146def get_groupe() -> List[str]:147 """Documentation148 Récupère la liste des groupes149 """150 request: Request = (151 Request(distinct=True)152 .add_selector("client.{}".format(config["table"]["client"]["groupe"]), "groupe")153 .add_table(config["table"]["client"]["nom_table"], "client")154 .set_order_by("groupe")155 )156 data: pd.DataFrame = request.run(conn)157 return list(data["groupe"])158def get_client(159 id_cpt: Union[str, None] = None,160 name_bat: Union[str, None] = None,161 type_energie: Union[str, None] = None,162 group: Union[str, None] = None,163) -> List[str]:164 """Documentation165 Récupère la liste des clients en fonction du groupe sélectionné166 """167 request: Request = (168 Request(distinct=True)169 .add_selector(170 "client.{}".format(config["table"]["client"]["nom"]), "Nom_Client"171 )172 .add_table(config["table"]["client"]["nom_table"], "client")173 .set_order_by("Nom_Client")174 )175 if group is not None:176 request.add_condition(177 Condition(178 "client.{} = '{}'".format(config["table"]["client"]["groupe"], group),179 "AND",180 )181 )182 data: pd.DataFrame = request.run(conn2)183 return list(data["Nom_Client"])184def get_type_energie(185 id_cpt: Union[str, None] = None,186 name_bat: Union[str, None] = None,187 name_client: Union[str, None] = None,188) -> List[str]:189 """Documentation190 On selectionne les types d'energie sans prendre en considération les autres filtres191 """192 request: Request = (193 Request(distinct=True)194 .add_selector(195 "cpt.{}".format(config["table"]["compteur"]["type_energie"]), "Type_Energie"196 )197 .add_table(config["table"]["compteur"]["nom_table"], "cpt")198 .set_order_by("Type_Energie")199 )200 data: pd.DataFrame = request.run(conn2)201 return list(data["Type_Energie"])202def get_batiment(203 id_cpt: Union[str, None] = None,204 type_energie: Union[str, None] = None,205 name_client: Union[str, None] = None,206 group: Union[str, None] = None,207) -> List[str]:208 """Documentation209 Récupère les noms de batiments en fonction du groupe et des clients sélectionnés210 """211 request: Request = (212 Request(distinct=True)213 .add_selector(214 "bat.{}".format(config["table"]["batiment"]["nom"]), "Nom_Batiment"215 )216 .add_table(config["table"]["batiment"]["nom_table"], "bat")217 .set_order_by("Nom_Batiment")218 )219 if group is not None or name_client is not None:220 # Ajout de la jointure entre les deux tables221 request.add_table(222 config["table"]["client"]["nom_table"], "client"223 ).add_condition(224 Condition(225 "bat.{} = client.{}".format(226 config["table"]["batiment"]["ref_client"],227 config["table"]["client"]["ref"],228 ),229 "AND",230 ),231 )232 if group is not None:233 request.add_condition(234 Condition(235 "client.{} = '{}'".format(config["table"]["client"]["groupe"], group)236 )237 )238 if name_client is not None:239 request.add_condition(240 Condition(241 "client.{} = '{}'".format(config["table"]["client"]["nom"], name_client)242 )243 )244 data: pd.DataFrame = request.run(conn2)245 return list(data["Nom_Batiment"])246def get_data(247 id_cpt: List[str], startDate: datetime.datetime, endDate: datetime.datetime248) -> pd.DataFrame:249 """Documentation250 A partir d'une paire de date, d'un id de capteur, cette fonction va interroger la base de donneée251 Parametre:252 id_cpt: une list d'id de compteur253 startDate: une date de départ254 endDate: une date d'arrive > startDate255 Sortie:256 data: DataFrame contenant les valeurs des compteurs et tout autres informations257 """258 if type(id_cpt) != list:259 id_cpt = [id_cpt]260 request: Request = (261 Request()262 .add_selector("*")263 .add_table(config["table"]["histo"]["nom_table"])264 .add_condition(265 Condition(266 "{} >= '{}'".format(267 config["table"]["histo"]["temps"], startDate.strftime("%d/%m/%Y")268 )269 )270 )271 .add_condition(272 Condition(273 "{} <= '{}'".format(274 config["table"]["histo"]["temps"], endDate.strftime("%d/%m/%Y")275 )276 )277 )278 .add_condition(279 Condition(280 "{} in ('{}')".format(281 config["table"]["histo"]["id_cpt"], "','".join(id_cpt)282 )283 )284 )285 .set_order_by(286 "{}, {}".format(287 config["table"]["histo"]["temps"], config["table"]["histo"]["id_cpt"]288 )289 )290 )291 data: pd.DataFrame = request.run(conn)292 return data293# Obselete294def get_conso(295 id_cpt: List[str],296 startDate: datetime.datetime,297 endDate: datetime.datetime,298 periode: str,299) -> pd.DataFrame:300 """Documentation301 A partir d'une paire de date, d'une periode, d'un id de capteur cette fonction va calculer la consomation302 Parameter:303 id_cpt: list des id des compteurs304 start_date: une date départ305 end_date: une date d'arrive > start_date306 periode: Valeur prédéfini d'une periode sur laquel est calculé les consommation (ex: jours, trim, an, ...)307 Sortie:308 data: DataFrame contenant les consommations associées aux compteurs309 """310 # TODO Changer les requetes par de simple requetes sur des vues311 # Voir pour le calul de la conso312 # Requete conso par jour313 if periode == "jour":314 data: pd.DataFrame = pd.read_sql_query(315 "select vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), DAY(vc2.TS)) TS, SUM(vc2.Value - vc1.Value) Conso"316 " from"317 " v_conso vc1,"318 " v_conso vc2"319 " where"320 " vc1.Id_CPT in " + "('" + "','".join(id_cpt) + "')"321 " and vc1.TS >= '"322 + startDate.strftime("%d/%m/%Y")323 + "' and vc1.TS <= '"324 + endDate.strftime("%d/%m/%Y")325 + "' and vc1.Id_CPT = vc2.Id_CPT"326 " and vc1.Num = vc2.Num - 1"327 " group by vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), DAY(vc2.TS))"328 " order by vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), DAY(vc2.TS))",329 con=conn,330 )331 # Requete conso par mois332 if periode == "mois":333 data: pd.DataFrame = pd.read_sql_query(334 "select vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), 1) TS, SUM(vc2.Value - vc1.Value) Conso"335 " from"336 " v_conso vc1,"337 " v_conso vc2"338 " where"339 " vc1.Id_CPT in " + "('" + "','".join(id_cpt) + "')"340 " and vc1.TS >= '"341 + startDate.strftime("%d/%m/%Y")342 + "' and vc1.TS <= '"343 + endDate.strftime("%d/%m/%Y")344 + "' and vc1.Id_CPT = vc2.Id_CPT"345 " and vc1.Num = vc2.Num - 1"346 " group by vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), 1)"347 " order by vc1.Id_CPT, datefromparts(YEAR(vc2.TS), MONTH(vc2.TS), 1)",348 con=conn,349 )350 # Requete pour la consomation par trimestre351 if periode == "trim":352 data: pd.DataFrame = pd.read_sql_query(353 "select vc1.Id_CPT, YEAR(vc2.TS) + MONTH(vc2.TS) / 3 / 10. TS, SUM(vc2.Value - vc1.Value) Conso"354 " from"355 " v_conso vc1,"356 " v_conso vc2"357 " where"358 " vc1.Id_CPT in " + "('" + "','".join(id_cpt) + "')"359 " and vc1.TS >= '"360 + startDate.strftime("%d/%m/%Y")361 + "' and vc1.TS <= '"362 + endDate.strftime("%d/%m/%Y")363 + "' and vc1.Id_CPT = vc2.Id_CPT"364 " and vc1.Num = vc2.Num - 1"365 " group by vc1.Id_CPT, YEAR(vc2.TS) + MONTH(vc2.TS) / 3 / 10."366 " order by vc1.Id_CPT, YEAR(vc2.TS) + MONTH(vc2.TS) / 3 / 10.",367 con=conn,368 )369 if periode == "sge":370 pass371 # print(data)372 return data373FACTURATION_DATE: pd.DataFrame = None374def get_facturation_date() -> pd.DataFrame:375 """Documentation376 Cette fonction renvoies les dates de facturation,377 elles sont récupéré de la BD une fois à chaque redémarage de l'application378 Sortie:379 FACTURATION_DATE: Liste des dates de facturation380 """381 global FACTURATION_DATE382 if FACTURATION_DATE is None:383 request: Request = (384 Request()385 .add_selector(386 "Year({})".format(config["table"]["base_temps"]["date"]), "Annee"387 )388 .add_selector(389 "Month({})".format(config["table"]["base_temps"]["date"]), "Mois"390 )391 .add_selector(392 "Day({})".format(config["table"]["base_temps"]["date"]), "Jour"393 )394 .add_table(config["table"]["base_temps"]["nom_table"])395 .add_condition(396 Condition(397 "{} = '{}'".format(398 config["table"]["base_temps"]["type"], "date facturation"399 )400 )401 )402 .set_order_by(config["table"]["base_temps"]["date"])403 )404 data: pd.DataFrame = request.run(conn)405 data = data.apply(pd.to_numeric)...
main_window.py
Source:main_window.py
...38 self.setLayout(self.layout)39 self.setWindowTitle("Image finder")40 self.show()41 def add_filter_selectors(self):42 self.add_selector(43 'File format',44 SelectFormatWindow(lambda x: self.model.update_filters('format', x)),45 100,46 False,47 'format',48 )49 self.add_selector(50 'Animal',51 SelectAnimalWindow(lambda x: self.model.update_filters('animal', x)),52 150,53 True,54 'animal',55 )56 self.add_selector(57 'Style',58 SelectStyleWindow(lambda x: self.model.update_filters('style', x)),59 200,60 False,61 'style',62 )63 self.add_selector(64 'Body parts',65 SelectBodyWindow(lambda x: self.model.update_filters('body', x)),66 250,67 True,68 'body',69 )70 def add_selector(self, label, window, ay, with_weight, model_label):71 widget = FilterSelectorWidget(72 label,73 window,74 ay,75 with_weight,76 lambda x: self.set_weight(model_label, x),77 model_label,78 self,79 )80 self.widgets.append(widget)81 self.layout.addWidget(widget)82 def add_results_presentation_selector(self):83 combo_box = QComboBox(self)84 for pres in [p for p in ResultsPresentation]:...
menu.py
Source:menu.py
...12 assert 'select_level_cb' in cb_list13 level_list = get_level_list()14 map_list = get_map_list()15 assert len(level_list) > 0# and len(map_list) > 016 level_selector = self.menu.add_selector('', level_list, onchange=cb_list['select_level_cb'])17 # Set default level, maybe a litte hack here18 cb_list['select_level_cb'](*level_list[level_selector.get_value()[1]])19 # map_selector = self.menu.add_selector('', level_list, onchange=cb_list['select_level_cb'])20 # # Set default level, maybe a litte hack here21 # cb_list['select_level_cb'](*level_list[level_selector.get_value()[1]])22 self.menu.add_button('Quit', pygame_menu.events.EXIT)23 def add_level(self, level_list, cb):24 self.menu.add_selector('Level :' , level_list, on_change=cb)25 26 def add_map(self, map_list, cb):27 self.menu.add_selector('Map :' , map_list, on_change=cb)28 def display(self):...
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