Update main.py

main.py

@@ -232,6 +232,69 @@ def htmlToDataframe(htmlTable):
   dataFrame = pd.DataFrame(data = data, columns = list_header)
   return dataFrame
 
+def datavisualisation_chiffres_cles_emplois(url):
+    response = requests.get(url)
+    soup = BeautifulSoup(response.text, "lxml")
+
+    alldemandeurs = ''
+    allsalaires = ''
+    alldifficultes = ''
+    allrepartitions = ''
+    allentreprises = ''
+    allembauches = soup.select('p.population_category')
+    allnumembauchesfirst = soup.select('p.population_main-num.data')
+    allnumembauches = removeTags(allnumembauchesfirst[0]).split('\xa0')
+    allnumembauches = ''.join(allnumembauches)
+    allnumoffres = removeTags(allnumembauchesfirst[1]).split('\xa0')
+    allnumoffres = ''.join(allnumoffres)
+    alldetailembauches = soup.select('p.hiring_text.ng-star-inserted')
+    allnumevolutionembauches = soup.select('p.main.ng-star-inserted')
+    alldetailevolutionembauches = soup.select('p.population_bubble-title')
+    alldemandeurs = "<table><tr><td>Indicateur</td><td>Valeur</td></tr><tr><td>" + removeTags(allembauches[0]) + " (" + removeTags(alldetailembauches[0]) + ");\nÉvolution demandeurs d'emploi (" + removeTags(alldetailevolutionembauches[0]) + ": " + removeTags(allnumevolutionembauches[0]) + ")</td><td>" + allnumembauches + "</td></tr>"
+    alldemandeurs += "<tr><td>" + removeTags(allembauches[1]) + " (" + removeTags(alldetailembauches[1]) + "); Évolution offres d'emploi (" + removeTags(alldetailevolutionembauches[1]) + ": " + removeTags(allnumevolutionembauches[1]) + ")</td><td>" + allnumoffres + "</td></tr>"
+    alldemandeurs += "</table>"
+
+    allFAP = soup.select('tr.sectorTable__line.ng-star-inserted')
+    allcategorie = soup.select('td.sectorTable__cell')
+    alltypesalaires = soup.select('th.sectorTable__cell')
+    allFAPsalaires = soup.select('p.sectorTable__cellValue')
+    if len(allFAPsalaires) >= 3:
+        allsalaires = "<table><tr><td>categorie</td><td>emploi</td><td>salaire</td></tr>"
+        allsalaires += "<tr><td>" + removeTags(alltypesalaires[1]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[0]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+        allsalaires += "<tr><td>" + removeTags(alltypesalaires[2]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[1]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+        allsalaires += "<tr><td>" + removeTags(alltypesalaires[3]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[2]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+        if len(allFAP) >= 2 and len(allFAPsalaires) == 6:
+            allsalaires += "<tr><td>" + removeTags(alltypesalaires[1]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[3]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+            allsalaires += "<tr><td>" + removeTags(alltypesalaires[2]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[4]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+            allsalaires += "<tr><td>" + removeTags(alltypesalaires[3]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[5]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
+        allsalaires += "</table>"
+
+    alltypedifficultes = soup.select('.tabs-main-content_persp-col2-bar.ng-star-inserted')
+    alldifficulte = soup.select('p.horizontal-graph_title')
+    allpcdifficulte = soup.select('div.horizontal-graph_data')
+    alldifficultes = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
+    for i in range(0,len(alltypedifficultes)):
+        alldifficultes += "<tr><td>" + removeTags(alldifficulte[i]) + "</td><td>" + removeTags(allpcdifficulte[i]).replace('Pour le territoire principal FRANCE pour les ' + removeTags(alldifficulte[i]),'').replace('%','') + "</td></tr>"
+    alldifficultes += "</table>"
+
+    alltyperepartitions = soup.select('div.hiring-contract_legende_item.ng-star-inserted')
+    allrepartition = soup.select('p.hiring-contract_legende_item_label')
+    allpcrepartition = soup.select('span.hiring-contract_legende_item-first')
+    allrepartitions = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
+    for i in range(0,len(alltyperepartitions)):
+        allrepartitions += "<tr><td>" + removeTags(allrepartition[i]).replace('(' + removeTags(allpcrepartition[i]) + ')','') + "</td><td>" + removeTags(allpcrepartition[i]).replace('%','').replace(',','.') + "</td></tr>"
+    allrepartitions += "</table>"
+
+    allentrepriserepartitions = soup.select('div.horizontal-graph_pattern.sm-bubble_wrapper > span')
+    allentreprise = soup.select('span.sr-only')
+    allpcentreprise = soup.select('span.data.ng-star-inserted')
+    allentreprises = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
+    for i in range(0,len(allentrepriserepartitions)):
+        allentreprises += "<tr><td>" + removeTags(allentrepriserepartitions[i])[0:-4] + "</td><td>" + removeTags(allentrepriserepartitions[i])[-4:].replace('%','').replace(',','.') + "</td></tr>"
+    allentreprises += "</table>"
+
+    return [alldemandeurs, allsalaires, alldifficultes, allrepartitions, allentreprises]
+
 def listToString(list):
     return str(list)
 
@@ -281,7 +344,7 @@ def rename(orig_author: str):
 async def on_action(action):
     romeListArray = ast.literal_eval(action.value)
     for j in range(0, len(romeListArray)):
-        table = await datavisualisation_chiffres_cles_emplois("https://dataemploi.pole-emploi.fr/metier/chiffres-cles/NAT/FR/" + romeListArray[j])
+        table = datavisualisation_chiffres_cles_emplois("https://dataemploi.pole-emploi.fr/metier/chiffres-cles/NAT/FR/" + romeListArray[j])
         plot_demandeur = plotDemandeur(htmlToDataframe(table[0]), romeListArray[j])
         if len(table[1]) > 0:
             plot_salaire = plotSalaire(htmlToDataframe(table[1]))
@@ -524,70 +587,6 @@ async def document_chiffres_cles_emplois(url, codes):
             allentreprise = ""
         all = all + "\n\nChiffres-clés Métier : \n**" + allTitre + "**:\n◉ Demandeurs d'emploi et Offres d'emploi : " + allEmbauches.replace("Plus de données sur les Demandeurs d'emploi","").replace("Plus de données","") + ".\n◉ Salaires proposés dans les offres : " + allSalaires + ".\n◉ Salaires médians constatés : " + allSalairesMedian + ".\n◉ Difficultés de recrutement pour les entreprises : " + alldiff + ".\n◉ Origine des difficultés : " + alldiffOrigin + ".\n◉ Répartition des embauches par type de contrat : " + allTypeContrat + ".\n◉ Répartition des embauches par taille d'entreprise : " + allentreprise + "."
     return all
-
-@cl.step(type="tool")
-async def datavisualisation_chiffres_cles_emplois(url):
-    response = requests.get(url)
-    soup = BeautifulSoup(response.text, "lxml")
-
-    alldemandeurs = ''
-    allsalaires = ''
-    alldifficultes = ''
-    allrepartitions = ''
-    allentreprises = ''
-    allembauches = soup.select('p.population_category')
-    allnumembauchesfirst = soup.select('p.population_main-num.data')
-    allnumembauches = removeTags(allnumembauchesfirst[0]).split('\xa0')
-    allnumembauches = ''.join(allnumembauches)
-    allnumoffres = removeTags(allnumembauchesfirst[1]).split('\xa0')
-    allnumoffres = ''.join(allnumoffres)
-    alldetailembauches = soup.select('p.hiring_text.ng-star-inserted')
-    allnumevolutionembauches = soup.select('p.main.ng-star-inserted')
-    alldetailevolutionembauches = soup.select('p.population_bubble-title')
-    alldemandeurs = "<table><tr><td>Indicateur</td><td>Valeur</td></tr><tr><td>" + removeTags(allembauches[0]) + " (" + removeTags(alldetailembauches[0]) + ");\nÉvolution demandeurs d'emploi (" + removeTags(alldetailevolutionembauches[0]) + ": " + removeTags(allnumevolutionembauches[0]) + ")</td><td>" + allnumembauches + "</td></tr>"
-    alldemandeurs += "<tr><td>" + removeTags(allembauches[1]) + " (" + removeTags(alldetailembauches[1]) + "); Évolution offres d'emploi (" + removeTags(alldetailevolutionembauches[1]) + ": " + removeTags(allnumevolutionembauches[1]) + ")</td><td>" + allnumoffres + "</td></tr>"
-    alldemandeurs += "</table>"
-
-    allFAP = soup.select('tr.sectorTable__line.ng-star-inserted')
-    allcategorie = soup.select('td.sectorTable__cell')
-    alltypesalaires = soup.select('th.sectorTable__cell')
-    allFAPsalaires = soup.select('p.sectorTable__cellValue')
-    if len(allFAPsalaires) >= 3:
-        allsalaires = "<table><tr><td>categorie</td><td>emploi</td><td>salaire</td></tr>"
-        allsalaires += "<tr><td>" + removeTags(alltypesalaires[1]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[0]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-        allsalaires += "<tr><td>" + removeTags(alltypesalaires[2]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[1]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-        allsalaires += "<tr><td>" + removeTags(alltypesalaires[3]) + "</td><td>" + removeTags(allcategorie[0]) + "</td><td>" + removeTags(allFAPsalaires[2]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-        if len(allFAP) >= 2 and len(allFAPsalaires) == 6:
-            allsalaires += "<tr><td>" + removeTags(alltypesalaires[1]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[3]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-            allsalaires += "<tr><td>" + removeTags(alltypesalaires[2]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[4]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-            allsalaires += "<tr><td>" + removeTags(alltypesalaires[3]) + "</td><td>" + removeTags(allcategorie[4]) + "</td><td>" + removeTags(allFAPsalaires[5]).replace('\xa0','').replace(' ','').replace('€','') + "</td></tr>"
-        allsalaires += "</table>"
-
-    alltypedifficultes = soup.select('.tabs-main-content_persp-col2-bar.ng-star-inserted')
-    alldifficulte = soup.select('p.horizontal-graph_title')
-    allpcdifficulte = soup.select('div.horizontal-graph_data')
-    alldifficultes = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
-    for i in range(0,len(alltypedifficultes)):
-        alldifficultes += "<tr><td>" + removeTags(alldifficulte[i]) + "</td><td>" + removeTags(allpcdifficulte[i]).replace('Pour le territoire principal FRANCE pour les ' + removeTags(alldifficulte[i]),'').replace('%','') + "</td></tr>"
-    alldifficultes += "</table>"
-
-    alltyperepartitions = soup.select('div.hiring-contract_legende_item.ng-star-inserted')
-    allrepartition = soup.select('p.hiring-contract_legende_item_label')
-    allpcrepartition = soup.select('span.hiring-contract_legende_item-first')
-    allrepartitions = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
-    for i in range(0,len(alltyperepartitions)):
-        allrepartitions += "<tr><td>" + removeTags(allrepartition[i]).replace('(' + removeTags(allpcrepartition[i]) + ')','') + "</td><td>" + removeTags(allpcrepartition[i]).replace('%','').replace(',','.') + "</td></tr>"
-    allrepartitions += "</table>"
-
-    allentrepriserepartitions = soup.select('div.horizontal-graph_pattern.sm-bubble_wrapper > span')
-    allentreprise = soup.select('span.sr-only')
-    allpcentreprise = soup.select('span.data.ng-star-inserted')
-    allentreprises = "<table><tr><td>Indicateur</td><td>Valeur</td></tr>"
-    for i in range(0,len(allentrepriserepartitions)):
-        allentreprises += "<tr><td>" + removeTags(allentrepriserepartitions[i])[0:-4] + "</td><td>" + removeTags(allentrepriserepartitions[i])[-4:].replace('%','').replace(',','.') + "</td></tr>"
-    allentreprises += "</table>"
-
-    return [alldemandeurs, allsalaires, alldifficultes, allrepartitions, allentreprises]
     
 @cl.step(type="tool")
 async def datavisualisation_statistiques_emplois(results_df):