wip

assemblee_nationale/README.md

@@ -0,0 +1,27 @@
+# Assemblée Nationale
+
+This institution is the french lower house of the french parliament.
+
+First of all, you need to load historic datas.
+
+Those tools are used to scrap :
+
+* Representatives basic informations
+    * AN code, Name, Nationality, Sex, Birth date and place, job
+* Types of entities
+    * Code and name of different types of entities linked to the house
+* Entities
+    * Type, Country, Name, Code, Picture, Start and End of each entity
+* Roles of representatives
+    * Code and name
+* Membership
+    * Link between Representatives and Entities : Start and End of their memberships
+
+
+## Schemas
+
+https://www.assemblee-nationale.fr/opendata/Schemas_Entites/AMO/Schemas_Organes.html
+
+
+Keep in mind that all those datas can be used to do a first push into politikorama and
+that they should be subject to human proof-reading.

assemblee_nationale/load_datas.py

@@ -10,14 +10,18 @@ import requests
 
 url = "https://data.assemblee-nationale.fr/static/openData/repository/15/amo/tous_acteurs_mandats_organes_xi_legislature/AMO30_tous_acteurs_tous_mandats_tous_organes_historique.json.zip"
 
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+data_source = os.path.join(data_root, "assemblee_nationale.zip")
+data_target = os.path.join(data_root, "json")
+
 # Cleaning old data
 try:
-    os.remove("../tmp/assemblee_nationale.zip")
+    os.remove(data_source)
 except FileNotFoundError:
     # No file to remove
     pass
 try:
-    shutil.rmtree("../tmp/json")
+    shutil.rmtree(data_target)
 except FileNotFoundError:
     # No folder to remove
     pass
@@ -26,10 +30,10 @@ except FileNotFoundError:
 print("Downloading archive")
 with requests.get(url, stream=True) as result:
     result.raise_for_status()
-    with open("../tmp/assemblee_nationale.zip", "wb") as f:
+    with open(data_source, "wb") as f:
         for chunk in result.iter_content(chunk_size=8192):
             f.write(chunk)
 print("Unpacking archive")
-shutil.unpack_archive("../tmp/assemblee_nationale.zip", "../tmp/")
+shutil.unpack_archive(data_source, data_root)
 
-os.remove("../tmp/assemblee_nationale.zip")
+os.remove(data_source)

assemblee_nationale/schemas.txt

@@ -1 +0,0 @@
-https://www.assemblee-nationale.fr/opendata/Schemas_Entites/AMO/Schemas_Organes.html

assemblee_nationale/scrap_entities.py

@@ -7,16 +7,23 @@ import csv
 from datetime import datetime
 import json
 import os
+import sys
+
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+target_root = os.path.join(data_root, "assemblee_nationale")
 
 # Extract representatives
-print("Scraping entities")
-with open("../tmp/assemblee_nationale_entities.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_source = os.path.join(data_root, "json/organe")
+data_target = os.path.join(target_root, "assemblee_nationale_entities.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["type_code", "country_iso2", "name", "code", "picture", "start", "end"])
 
-    for filename in os.listdir("../tmp/json/organe"):
+    for filename in os.listdir(data_source):
+        print(".", end="")
+        sys.stdout.flush()
         # Loading informations
-        with open(os.path.join("../tmp/json/organe", filename)) as file_handler:
+        with open(os.path.join(data_source, filename)) as file_handler:
             organe = json.load(file_handler)["organe"]
         type_raw = organe["codeType"]
         name = organe["libelle"]

assemblee_nationale/scrap_memberships.py

@@ -7,18 +7,25 @@ import csv
 from datetime import datetime
 import json
 import os
+import sys
 
 from slugify import slugify
 
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+target_root = os.path.join(data_root, "assemblee_nationale")
+
 # Extract representatives
-print("Scraping memberships")
-with open("../tmp/assemblee_nationale_memberships.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_source = os.path.join(data_root, "json/acteur")
+data_target = os.path.join(target_root, "assemblee_nationale_memberships.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["representative_slug", "role_code", "entity_code", "start", "end"])
 
-    for filename in os.listdir("../tmp/json/acteur"):
+    for filename in os.listdir(data_source):
+        print(".", end="")
+        sys.stdout.flush()
         # Loading informations
-        with open(os.path.join("../tmp/json/acteur", filename)) as file_handler:
+        with open(os.path.join(data_source, filename)) as file_handler:
             acteur = json.load(file_handler)["acteur"]
         identity = acteur["etatCivil"]["ident"]
         representative_slug = slugify(f"{identity['prenom']} {identity['nom']}")
@@ -26,6 +33,8 @@ with open("../tmp/assemblee_nationale_memberships.csv", "w", encoding="utf-8", n
         if isinstance(mandats, dict):
             mandats = [mandats]
         for mandat in mandats:
+            print(".", end="")
+            sys.stdout.flush()
             role_code = mandat["infosQualite"].get("codeQualite", "")
             start = mandat.get("dateDebut", None)
             end = mandat.get("dateFin", None)

assemblee_nationale/scrap_representatives.py

@@ -8,16 +8,21 @@ import json
 import os
 import sys
 
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+target_root = os.path.join(data_root, "assemblee_nationale")
+
 # Extract representatives
-with open("../tmp/assemblee_nationale_representatives.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_source = os.path.join(data_root, "json/acteur")
+data_target = os.path.join(target_root, "assemblee_nationale_representatives.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["code", "name", "picture", "nationality", "sex", "birth_date", "birth_place", "job"])
 
-    for filename in os.listdir("../tmp/json/acteur"):
+    for filename in os.listdir(data_source):
         print(".", end="")
         sys.stdout.flush()
         # Loading informations
-        with open(os.path.join("../tmp/json/acteur", filename)) as file_handler:
+        with open(os.path.join(data_source, filename)) as file_handler:
             acteur = json.load(file_handler)["acteur"]
         uid = f"AN_{acteur['uid']['#text'][2:]}"
         # Identity

assemblee_nationale/scrap_roles.py

@@ -8,18 +8,22 @@ import json
 import os
 import sys
 
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+target_root = os.path.join(data_root, "assemblee_nationale")
+
 # Extract roles
-print("Scraping roles")
-with open("../tmp/assemblee_nationale_roles.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_source = os.path.join(data_root, "json/acteur")
+data_target = os.path.join(target_root, "assemblee_nationale_roles.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["code", "name"])
 
     roles = []
-    for filename in os.listdir("../tmp/json/acteur"):
+    for filename in os.listdir(data_source):
         print(".", end="")
         sys.stdout.flush()
         # Loading informations
-        with open(os.path.join("../tmp/json/acteur", filename)) as file_handler:
+        with open(os.path.join(data_source, filename)) as file_handler:
             acteur = json.load(file_handler)["acteur"]
         mandats = acteur["mandats"]["mandat"]
         if isinstance(mandats, dict):

assemblee_nationale/scrap_types.py

@@ -43,18 +43,22 @@ TYPES = {
 }
 
 
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+target_root = os.path.join(data_root, "assemblee_nationale")
+
 # Extract types
-print("Scraping types")
-with open("../tmp/assemblee_nationale_types.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_source = os.path.join(data_root, "json/organe")
+data_target = os.path.join(target_root, "assemblee_nationale_types.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["code", "name"])
 
     types = {}
-    for filename in os.listdir("../tmp/json/organe"):
+    for filename in os.listdir(data_source):
         print(".", end="")
         sys.stdout.flush()
         # Loading informations
-        with open(os.path.join("../tmp/json/organe", filename)) as file_handler:
+        with open(os.path.join(data_source, filename)) as file_handler:
             organe = json.load(file_handler)["organe"]
         if organe["codeType"].upper() not in types:
             types[organe["codeType"].upper()] = TYPES.get(organe["codeType"].upper(), organe["codeType"].upper())

lqdn/README.md

@@ -0,0 +1,18 @@
+# La Quadrature du Net
+
+This organisation has collected a lot of important data about french representatives for
+years in their wiki (mediawiki engine).
+
+Those tools are used to scrap :
+
+* Representatives basic informations
+    * Name, Nationality, Sex, Birth date and place, job
+* Stances by Representatives
+    * Trying to find a matter and a subject for each stance, with a date and a source url
+* Votes by Representatives
+    * Trying to find a matter and a subject for each vote, with a date and a source url
+    No result is specified
+
+
+Keep in mind that all those datas can be used to do a first push into politikorama and
+that they should be subject to human proof-reading.

lqdn/list_deputes.py

@@ -1,13 +1,15 @@
 # encoding: utf-8
 
+import os
 from string import ascii_uppercase
-from time import sleep
 import sys
+from time import sleep
 
 from bs4 import BeautifulSoup
 import requests
 
 url = "https://wiki.laquadrature.net/index.php?title=Cat%C3%A9gorie:D%C3%A9put%C3%A9s&pagefrom="
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
 
 deputes = []
 for letter in ascii_uppercase:
@@ -25,6 +27,7 @@ for letter in ascii_uppercase:
             sys.stdout.flush()
     print()
 
-with open("../tmp/liste_deputes.txt", "w", encoding="utf-8") as file_handler:
+data_folder = os.path.join(data_root, "liste_deputes.txt")
+with open(data_folder, "w", encoding="utf-8") as file_handler:
     for depute in sorted(list(set(deputes))):
         file_handler.write(f"{depute}\n")

lqdn/scrap_representatives.py

@@ -3,30 +3,37 @@
 import csv
 from datetime import datetime
 import locale
+import os
 import re
 from string import ascii_uppercase
-from time import sleep
 import sys
+from time import sleep
 
 from bs4 import BeautifulSoup
 import requests
 from slugify import slugify
 
 url = "https://wiki.laquadrature.net/index.php?title=Cat%C3%A9gorie:D%C3%A9put%C3%A9s&pagefrom="
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
 locale.setlocale(locale.LC_ALL, "FR")
 
 deputes = []
-with open("../tmp/liste_deputes.txt", encoding="utf-8") as file_handler:
+data_source = os.path.join(data_root, "liste_deputes.txt")
+with open(data_source, encoding="utf-8") as file_handler:
     deputes = file_handler.read().splitlines()
 
 # Extract representatives
-with open("../tmp/lqdn_representatives.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_target = os.path.join(data_root, "lqdn_representatives.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["name", "picture", "nationality", "sex", "birth_date", "birth_place", "job"])
 
     for depute in deputes:
         print(".", end="")
         sys.stdout.flush()
+        try:
+            # Do not DDOS lqdn wiki ;o)
+            sleep(.2)
             # Loading informations
             content = requests.get(f"https://wiki.laquadrature.net/{depute}").text
             soup = BeautifulSoup(content, features="lxml")
@@ -59,3 +66,6 @@ with open("../tmp/lqdn_representatives.csv", "w", encoding="utf-8", newline="")
                 birth_city,
                 job_name,
             ])
+        except AttributeError:
+            print(f"\nError while scraping representative '{depute}'")
+            continue

lqdn/scrap_stances.py

@@ -2,22 +2,30 @@
 
 from datetime import datetime
 from string import ascii_uppercase
-from time import sleep
+import os
 import sys
+from time import sleep
 
 from bs4 import BeautifulSoup
 import csv
 import requests
 from slugify import slugify
 
-with open("../tmp/liste_deputes.txt") as file_handler:
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+
+data_source = os.path.join(data_root, "liste_deputes.txt")
+with open(data_source) as file_handler:
     deputes = file_handler.read().splitlines()
 
-with open("../tmp/lqdn_stances.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_target = os.path.join(data_root, "lqdn_stances.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
     writer.writerow(["name", "slug", "matter", "subject", "date", "extract", "source_url"])
 
     for depute in deputes:
+        print(".", end="")
+        sys.stdout.flush()
+        try:
             # Do not DDOS lqdn wiki ;o)
             sleep(.2)
             content = requests.get(f"https://wiki.laquadrature.net/{depute}").text
@@ -58,5 +66,6 @@ with open("../tmp/lqdn_stances.csv", "w", encoding="utf-8", newline="") as csvfi
                     stance_quote,
                     stance_link,
                 ])
-            print(".", end="")
-            sys.stdout.flush()
+        except AttributeError:
+            print(f"\nError while scraping stances for representative '{depute}'")
+            continue

lqdn/scrap_votes.py

@@ -2,45 +2,55 @@
 
 from datetime import datetime
 from string import ascii_uppercase
-from time import sleep
+import os
 import sys
+from time import sleep
 
 from bs4 import BeautifulSoup
 import csv
 import requests
 from slugify import slugify
 
-with open("lqdn_representatives.txt") as file_handler:
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+
+data_source = os.path.join(data_root, "liste_deputes.txt")
+with open(data_source) as file_handler:
     deputes = file_handler.read().splitlines()
 
-with open("lqdn_votes.csv", "w", encoding="utf-8", newline="") as csvfile:
+data_target = os.path.join(data_root, "lqdn_votes.csv")
+with open(data_target, "w", encoding="utf-8", newline="") as csvfile:
     writer = csv.writer(csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL)
-    writer.writerow(["name", "slug", "matter", "subject", "date", "extract", "source_url"])
+    writer.writerow(["name", "slug", "matter", "date", "source_url"])
 
     for depute in deputes:
+        print(".", end="")
+        sys.stdout.flush()
+        try:
             # Do not DDOS lqdn wiki ;o)
             sleep(.2)
             content = requests.get(f"https://wiki.laquadrature.net/{depute}").text
             soup = BeautifulSoup(content, features="lxml")
             deputy = soup.find("span", attrs={"class": "mw-headline"})
             if deputy is not None:
-            stance_author = deputy.text.split(",")[0].split(":")[1].strip()
+                vote_author = deputy.text.split(",")[0].split(":")[1].strip()
             else:
-            stance_author = depute
-        print(stance_author)
+                vote_author = depute
             votes = soup.find("span", attrs={"id": "Votes"}).parent.find_next_sibling("ul")
             if votes is not None:
                 for vote in votes.find_all("li"):
-                pass##print(f" {vote}")
-                writer.writerow([
-                    stance_author,
-                    slugify(stance_author),
-                    stance_matter,
-                    stance_subject,
-                    stance_date,
-                    stance_quote,
-                    stance_link,
-                ])
                     print(".", end="")
                     sys.stdout.flush()
+                    vote_date = datetime.strptime(vote.text.split()[0], "%d/%m/%Y")
+                    vote_matter = vote.find("a").text
+                    vote_url = vote.find("a").get("href")
+                    writer.writerow([
+                        vote_author,
+                        slugify(vote_author),
+                        vote_matter,
+                        datetime.strftime(vote_date, "%Y-%m-%d"),
+                        vote_url,
+                    ])
             print()
+        except (AttributeError, ValueError):
+            print(f"\nError while scraping stances for representative '{depute}'")
+            continue

parltrack/README.md

@@ -0,0 +1,12 @@
+# Parltrack
+
+This organisation collect all data from European Parliament.
+
+Those tools are used to scrap :
+
+* Representatives basic informations
+    * EP code, Name, Nationality, Sex, Birth date and place, job
+
+
+Keep in mind that all those datas can be used to do a first push into politikorama and
+that they should be subject to human proof-reading.

parltrack/parltrack.py

@@ -1,286 +0,0 @@
-# encoding: utf-8
-
-from datetime import datetime
-from io import StringIO, BytesIO
-import json
-import os
-import tempfile
-import zipfile
-
-import click
-import requests
-
-from app.model.address import AddressModel
-from app.model.contact import ContactModel
-from app.model.entity import EntityModel
-from app.model.membership import MembershipModel
-from app.model.representative import RepresentativeModel
-from app.model.type import TypeModel
-from command.json_reader import json_reader
-
-import json
-
-
-def import_representatives(filepath):
-    click.echo("Importing representatives from parltrack")
-    click.echo(" Reading file")
-    with open(filepath) as f:
-        meps = json.load(f)
-    for representative in meps:
-        click.echo(".", nl=False)
-
-    #for representative in json_reader(filepath):
-    #    click.echo(".", nl=False)
-
-
-
-
-def toto():
-    # Delete only things related to "Assemblée Nationale" !
-    MembershipModel.query.delete() #filter_by(source="Assemblée Nationale").delete()
-    RepresentativeModel.query.filter_by(source="Assemblée Nationale").delete()
-    AddressModel.query.filter_by(source="Assemblée Nationale").delete()
-    ContactModel.query.filter_by(source="Assemblée Nationale").delete()
-    EntityModel.query.filter_by(source="Assemblée Nationale").delete()
-    TypeModel.query.filter_by(source="Assemblée Nationale").delete()
-
-    url = "https://data.assemblee-nationale.fr/static/openData/repository/15/amo/tous_acteurs_mandats_organes_xi_legislature/AMO30_tous_acteurs_tous_mandats_tous_organes_historique.json.zip"
-    if False:
-        datas = BytesIO()
-        result = requests.get(url, stream=True)
-        datas.write(result.content)
-        datas.seek(0)
-        with tempfile.TemporaryDirectory() as tmpdir:
-            with zipfile.ZipFile(datas, "r") as zip_ref:
-                zip_ref.extractall(tmpdir)
-                print(tmpdir)
-            for root, dirs, files in os.walk(tmpdir):
-                if root.endswith("acteur"):
-                    for filename in files:
-                        print(os.path.join(root, filename))
-                    for filename in files[:1]:
-                        with open(os.path.join(root, filename)) as filehandler:
-                            data = json.load(filehandler)
-                            print(json.dumps(data, indent=2))
-    # Testing
-    tmpdir = "C:\\Users\\tbouchet\\Downloads\\json"
-    click.echo("  ", nl=False)
-    for root, dirs, files in os.walk(tmpdir):
-        if root.endswith("organe"):
-            with click.progressbar(files, label="Entities") as progress_files:
-                entities = []
-                for filename in progress_files:
-                    #print(filename)
-                    with open(os.path.join(root, filename)) as filehandler:
-                        data = json.load(filehandler)["organe"]
-
-                        # Type
-                        # file:///C:/Users/tbouchet/Downloads/html/Schemas_Entites/AMO/Schemas_Organes.html
-                        type_types = {
-                            "API": "Assemblée parlementaire internationale",
-                            "ASSEMBLEE": "Assemblée nationale",
-                            "ASSEXT": "Autres conseils",
-                            "ASSTOM": "Assemblée territoriale d’Outre-Mer",
-                            "CES": "Conseil économique, social et environnemental",
-                            "CJR": "Cour de justice de la République",
-                            "CMP": "Commissions mixtes paritaires",
-                            "CNPE": "Commissions d’enquêtes",
-                            "CNPS": "Commissions spéciales",
-                            "COMMUNE": "Conseil Municipal",
-                            "COMNL": "Autres commissions permanentes",
-                            "COMPER": "Commissions permanentes législatives",
-                            "COMSENAT": "Commissions du Sénat",
-                            "COMSPSENAT": "Commissions spéciales du Sénat",
-                            "CONFPT": "CONFPT",
-                            "CONSTITU": "Conseil constitutionnel",
-                            "DELEG": "Délégation parlementaire",
-                            "DELEGBUREAU": "Délégation du Bureau (de l’AN)",
-                            "DELEGSENAT": "Délégation du Sénat",
-                            "DEPARTEMENT": "Conseil général ou départemental",
-                            "EUROPE": "Mandat européen",
-                            "GA": "Groupe d’amitié",
-                            "GE": "Groupe d’études",
-                            "GEVI": "Groupe d’études à vocation internationale",
-                            "GOUVERNEMENT": "Gouvernement",
-                            "GP": "Groupe politique",
-                            "GROUPESENAT": "Groupe Sénat",
-                            "HCJ": "Haute Cour de justice",
-                            "INTCO": "Intercommunalité",
-                            "MINISTERE": "Ministère",
-                            "MISINFO": "Missions d’informations",
-                            "MISINFOCOM": "Missions d’information communes",
-                            "MISINFOPRE": "Missions d’information de la conférence des Présidents",
-                            "OFFPAR": "Office parlementaire ou délégation mixte",
-                            "ORGAINT": "Organisme international",
-                            "ORGEXTPARL": "Organisme extra parlementaire",
-                            "PARPOL": "Parti Politique",
-                            "PRESREP": "Présidence de la République",
-                            "REGION": "Conseil régional",
-                            "SENAT": "Mandat de sénateur",
-                        }
-                        type = TypeModel.query.filter_by(name = type_types[data["codeType"]]).first()
-                        if type is None:
-                            type = TypeModel()
-                            type.source = "Assemblée Nationale"
-                            type.source_uid = data["codeType"]
-                            type.name = type_types[data["codeType"]]
-                            type.save()
-
-                        # Entity
-                        entity = EntityModel(
-                            source = "Assemblée Nationale",
-                            source_uid = data["uid"],
-                            type_id = type.id,
-                            name = data["libelle"],
-                            code = data["libelleAbrev"],
-                            country_id = country.id,
-                        )
-                        if data["organeParent"] is not None:
-                            parent = EntityModel.query.filter_by(source_uid=data["organeParent"]).first()
-                            if parent is not None:
-                                entity.parent_id = parent.id
-                            else:
-                                print(data["uid"], data["organeParent"])
-                        entity.save()
-
-    for root, dirs, files in os.walk(tmpdir):
-        if root.endswith("acteur"):
-            with click.progressbar(files, label="Representatives") as progress_files:
-                for filename in progress_files:
-                    with open(os.path.join(root, filename)) as filehandler:
-                        data = json.load(filehandler)["acteur"]
-
-                        # Representative
-                        representative = RepresentativeModel()
-                        representative.source = "Assemblée Nationale"
-                        representative.source_uid = data["uid"]["#text"]
-                        nom = data["etatCivil"]["ident"]["nom"]
-                        prenom = data["etatCivil"]["ident"]["prenom"]
-                        representative.name = f"{prenom} {nom}"
-                        representative.nationality_id = country.id
-                        representative.birth_date = datetime.strptime(
-                            data["etatCivil"]["infoNaissance"]["dateNais"], "%Y-%m-%d"
-                        )
-                        if isinstance(data["etatCivil"]["infoNaissance"]["villeNais"], str):
-                            representative.birth_place = data["etatCivil"]["infoNaissance"][
-                                "villeNais"
-                            ]
-                        if isinstance(data["profession"]["libelleCourant"], str):
-                            representative.profession = data["profession"]["libelleCourant"]
-                        representative.save()
-
-                        # Address
-                        if data["adresses"].get("adresse", "") != "":
-                            address_types = {
-                                "0": "Parliament address",
-                                "1": "Address",
-                                "2": "Constituency address",
-                            }
-
-                            def manage_address(data_address):
-                                if data_address["type"] in address_types:
-                                    address = AddressModel()
-                                    address.representative_id = representative.id
-                                    address.source = "Assemblée Nationale"
-                                    address.source_uid = data_address["uid"]
-                                    address.name = address_types[data_address["type"]]
-                                    address.country_id = country.id
-                                    address.number = data_address["numeroRue"]
-                                    address.street = data_address["nomRue"]
-                                    address.miscellaneous = data_address[
-                                        "complementAdresse"
-                                    ]
-                                    address.city = data_address["ville"]
-                                    address.zipcode = data_address["codePostal"]
-                                    address.save()
-
-                            if isinstance(data["adresses"]["adresse"], list):
-                                for data_address in data["adresses"]["adresse"]:
-                                    manage_address(data_address)
-                            elif isinstance(data["adresses"]["adresse"], dict):
-                                manage_address(data["adresses"]["adresse"])
-
-                            # Contact
-                            contact_types = {
-                                "3": "Phone (Press contact)",
-                                "11": "Phone",
-                                "12": "Fax",
-                                "15": "Email",
-                                "22": "Website",
-                                "23": "Senate URL",
-                                "24": "Twitter",
-                                "25": "Facebook",
-                            }
-
-                            def manage_contact(data_contact):
-                                if data_contact["type"] in contact_types:
-                                    contact = ContactModel()
-                                    contact.representative_id = representative.id
-                                    contact.source = "Assemblée Nationale"
-                                    contact.source_uid = data_contact["uid"]
-                                    if data_contact["adresseDeRattachement"] is not None:
-                                        address = AddressModel.query.filter_by(
-                                            source_uid=data_contact["adresseDeRattachement"]
-                                        ).first()
-                                        if address is not None:
-                                            contact.address_id = address.id
-                                    contact.name = contact_types[data_contact["type"]]
-                                    contact.value = data_contact["valElec"]
-                                    contact.save()
-
-                            if isinstance(data["adresses"]["adresse"], list):
-                                for data_contact in data["adresses"]["adresse"]:
-                                    manage_contact(data_contact)
-                            elif isinstance(data["adresses"]["adresse"], dict):
-                                manage_contact(data["adresses"]["adresse"])
-
-                            # Unknown addresses ?
-                            if isinstance(data["adresses"]["adresse"], list):
-                                for data_address in data["adresses"]["adresse"]:
-                                    if data_address["type"] not in dict(
-                                        address_types, **contact_types
-                                    ):
-                                        print(
-                                            f"  => Unkown address type : {data_address['type']} in file {filename} : {data_address['typeLibelle']}"
-                                        )
-                            elif isinstance(data["adresses"]["adresse"], dict):
-                                data_address = data["adresses"]["adresse"]
-                                if data_address["type"] not in dict(
-                                    address_types, **contact_types
-                                ):
-                                    print(
-                                        f"  => Unkown address type : {data_address['type']} in file {filename} : {data_address['typeLibelle']}"
-                                    )
-
-                        if data["mandats"].get("mandat", "") != "":
-                            # Membership
-                            membership_types = {
-                                "Membre": "Member",
-                            }
-
-                            def manage_membership(data_membership):
-                                if data_membership["infosQualite"]["codeQualite"] in membership_types:
-                                    entity = EntityModel.query.filter_by(source_uid=data_membership["organes"]["organeRef"]).first()
-                                    if entity is None:
-                                        print("Organe inconnu", data_membership["organes"]["organeRef"])
-                                        return
-                                    membership = MembershipModel()
-                                    membership.representative_id = representative.id
-                                    membership.role = membership_types[data_membership["infosQualite"]["codeQualite"]]
-                                    membership.country_id = country.id
-                                    if data_membership["dateDebut"] is not None:
-                                        membership.start = datetime.strptime(
-                                            data_membership["dateDebut"], "%Y-%m-%d"
-                                        )
-                                    if data_membership["dateFin"] is not None:
-                                        membership.end = datetime.strptime(
-                                            data_membership["dateFin"], "%Y-%m-%d"
-                                        )
-                                    membership.entity_id = entity.id
-                                    membership.save()
-
-                            if isinstance(data["mandats"]["mandat"], list):
-                                for data_membership in data["mandats"]["mandat"]:
-                                    manage_membership(data_membership)
-                            elif isinstance(data["mandats"]["mandat"], dict):
-                                manage_membership(data["mandats"]["mandat"])

parltrack/scrap_representatives.py

@@ -0,0 +1,31 @@
+# encoding: utf-8
+
+import os
+import shutil
+
+import lzip
+
+url = "https://parltrack.org/dumps/ep_meps.json.lz"
+data_root = os.environ.get("POLITIKORAMA_DATA_ROOT", "../tmp")
+data_source = os.path.join(data_root, "ep_meps.json.lz")
+data_target = os.path.join(data_root, "json")
+
+# Cleaning old data
+try:
+    os.remove(data_source)
+except FileNotFoundError:
+    # No file to remove
+    pass
+try:
+    shutil.rmtree(data_target)
+except FileNotFoundError:
+    # No folder to remove
+    pass
+
+# Download and extract data
+print("Downloading archive")
+with open(data_source, "wb") as f:
+    for chunk in lzip.decompress_url_iter(url):
+        f.write(chunk)
+
+os.remove(data_source)