travail sur les données du médialab en vue de faire un bilan de l'empreinte écologique du médialab sur https://apps.labos1point5.org/ges-1point5

convert_patos_to_ges_1p5.py

# convertit le fichier tenu par Benjamin sur le matériel du médialab en un fichier utilisable par l'outil

import csv

input_path = "./inputs/inventaire-ordis-medialab-noID.csv"

# Modele;Fabricant;Type
results = []
with open(input_path, newline="") as csvfile:
  reader = csv.DictReader(csvfile, delimiter=";")
  for row in reader:
    # print(dict(row))
    if row["Modèle [Réf article]"] ==  "":
      continue
    matos_type = "laptop"
    if "ECR" in row["identifiant"]:
      matos_type = "monitor"
    elif "PAD" in row["identifiant"]:
      matos_type = "Tablette"
    elif "PST" in row["identifiant"]:
      matos_type = "fixe"
    elif "disque dur" in row["Modèle [Réf article]"].lower():
      matos_type = "Disque dur"
    clean = {
      "Modele": row["Modèle [Réf article]"],
      "Fabricant": row["Marque [Réf article]"],
      "Type": matos_type
    }
    results.append(clean)

with open('./outputs/inventaire_utilisable.csv', 'w', newline='') as csvfile:
  columns = results[0].keys()
  entries = csv.DictWriter(csvfile, fieldnames=columns)
  entries.writeheader()
  entries.writerows(results)

convert_transport_to_ges_1p5.py

# convertit un fichier issu de cytric au format demandé par l'outil pour les transports

import csv
import re

input = "./outputs/cytric_dedoublonne.csv";

mode_map = {
  "RAIL": "train",
  "AIR": "avion"
}

converted_data = []
with open(input, "r", newline="") as csvfile:
  reader = csv.DictReader(csvfile)
  for i, row in enumerate(reader):
    depart = row["Destination Depart"].replace("CEDEX", "")
    (ville_depart, pays_depart) = re.match("(.*)\((.*)\)", depart).groups()

    arrivee = row["Destination Arrivee"].replace("CEDEX", "")
    (ville_arrivee, pays_arrivee) = re.match("(.*)\((.*)\)", arrivee).groups()

    converted_row = {
      "# mission": str(i + 1),
      "Date de départ": row["Date de Debut/Depart"],
      "Ville de départ": ville_depart.strip(),
       "Pays de départ": pays_depart.strip(),
       "Ville de destination": ville_arrivee.strip(),
       "Pays de destination": pays_arrivee.strip(),
       "Mode de déplacement": mode_map[row["Activite Type"]],
       "Nb de personnes dans la voiture": "1",
       "Aller Retour (OUI si identiques, NON si différents)": "NON",
       "Motif du déplacement (optionnel)": row["TYPE DE MISSION (CC3)"],
       "Statut de l'agent (optionnel)": ""
    }
    converted_data.append(converted_row)

with open('./outputs/cytric_utilisable.csv', 'w', newline='') as csvfile:
  columns = converted_data[0].keys()
  entries = csv.DictWriter(csvfile, fieldnames=columns)
  entries.writeheader()
  entries.writerows(converted_data)

dedoublonnage_cytric.py

# dédoublonne des exports issus de Cytric

import csv

f1_path = "./inputs/Mission2023_9RA9-noID.csv"
f2_path = "./inputs/Missions2023_Division Medialab-noID.csv"

output_path = "./outputs/cytric_dedoublonne.csv";

def footprint(entry):
  return entry['Date de Debut/Depart'] + entry['Destination Depart'] + entry['UID (MATRI)'] + entry['NUMERO ORDRE DE MISSION (CC1)']

def csv_to_map(f_path):
  with open(f_path, 'r', newline='') as f1:
    str = f1.readlines()
    str = '\n'.join(str).replace('\ufeff', '').split('\n')
    entries = csv.DictReader(str, delimiter=";")

    output = {}
    for e in entries:
      fp = footprint(e)
      output[fp] = dict(e)
  return output

map_1 = csv_to_map(f1_path)
map_2 = csv_to_map (f2_path)

merged = {**map_1, **map_2}
merged = list(merged.values())

with open(output_path, 'w', newline='') as csvfile:
  columns = merged[0].keys()
  entries = csv.DictWriter(csvfile, fieldnames=columns)
  entries.writeheader()
  entries.writerows(merged)