Parse CSV to database

This commit is contained in:
Emmy D'Anello 2023-02-12 17:22:40 +01:00
parent e22a039aa8
commit 39fdfce38f
Signed by: ynerant
GPG Key ID: 3A75C55819C8CF85
1 changed files with 63 additions and 27 deletions

90
app.py
View File

@ -7,10 +7,12 @@ import json
from pytz import timezone
import requests
import click
from flask import Flask
from flask.cli import AppGroup
from flask_migrate import Migrate
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import Boolean, Column, Date, Integer, String, Time
from sqlalchemy import Boolean, Column, Date, DateTime, Integer, String, Time
from tqdm import tqdm
import config
@ -18,6 +20,10 @@ import config
app = Flask(__name__)
cli = AppGroup('tgvmax', help="Manage the TGVMax dataset.")
app.cli.add_command(cli)
app.config |= config.FLASK_CONFIG
db = SQLAlchemy(app)
@ -29,19 +35,25 @@ class Train(db.Model):
id = Column(String, primary_key=True)
day = Column(Date, index=True)
number = Column(Integer, index=True)
entity = Column(String(255))
axe = Column(String(255), index=True)
entity = Column(String(10))
axe = Column(String(32), index=True)
orig_iata = Column(String(5), index=True)
dest_iata = Column(String(5), index=True)
orig = Column(String(255))
dest = Column(String(255))
dep = Column(String(255))
orig = Column(String(32))
dest = Column(String(32))
dep = Column(Time)
arr = Column(Time)
tgvmax = Column(Boolean, index=True)
remaining_seats = Column(Integer)
remaining_seats = Column(Integer, default=-1)
last_modification = Column(DateTime)
expiration_time = Column(DateTime)
@cli.command("update-dataset")
def update_dataset():
"""
Query the latest version of the SNCF OpenData dataset, as a CSV file.
"""
try:
resp = requests.get('https://ressources.data.sncf.com/explore/dataset/tgvmax/information/')
content = resp.content.decode().split('<script type="application/ld+json">')[1].split('</script>')[0].strip()
@ -76,37 +88,61 @@ def update_dataset():
print(e)
def parse_trains(*, filter_day: date | None = None,
filter_number: int | None = None,
filter_tgvmax: bool | None = None):
trains = []
@cli.command("parse-csv")
@click.option('-F', '--flush', type=bool, is_flag=True, help="Flush the database before filling it.")
def parse_trains(flush: bool = False):
"""
Parse the CSV file and store it to the database.
"""
if flush:
print("Flush database…")
db.session.query(Train).delete()
last_modification = datetime.utcfromtimestamp(os.path.getmtime('tgvmax.csv')).replace(tzinfo=timezone('UTC'))
with open('tgvmax.csv') as f:
first_line = True
for line in csv.reader(f, delimiter=';'):
already_seen = set()
for line in tqdm(csv.reader(f, delimiter=';')):
if first_line:
first_line = False
continue
train = Train(*line)
train.day = date.fromisoformat(train.day)
train.number = int(train.number)
train.dep = time.fromisoformat(train.dep)
train.arr = time.fromisoformat(train.arr)
train.tgvmax = train.tgvmax == 'OUI'
if filter_day is not None and train.day != filter_day:
train_id = f"{line[1]}-{line[0]}-{line[4]}-{line[5]}"
if train_id in already_seen:
# Some trains are mysteriously duplicated, concerns only some « Intercités de nuit »
# and the Brive-la-Gaillarde -- Paris
# and, maybe, for Roubaix-Tourcoing
if line[3] != "IC NUIT" and line[1] != '3614' and not (line[4] == 'FRADP' and line[5] == 'FRADM'):
print("Duplicate:", train_id)
continue
if filter_number is not None and train.number != filter_number:
continue
train = Train(
id=train_id,
day=date.fromisoformat(line[0]),
number=int(line[1]),
entity=line[2],
axe=line[3],
orig_iata=line[4],
dest_iata=line[5],
orig=line[6],
dest=line[7],
dep=time.fromisoformat(line[8]),
arr=time.fromisoformat(line[9]),
tgvmax=line[10] == 'OUI',
last_modification=last_modification,
expiration_time=last_modification,
)
if flush:
db.session.add(train)
else:
db.session.merge(train)
if filter_tgvmax is not None and train.tgvmax != filter_tgvmax:
continue
if line[3] == "IC NUIT" or line[1] == '3614' or (line[4] == 'FRADP' and line[5] == 'FRADM'):
already_seen.add(train_id)
trains.append(train)
return trains
db.session.commit()
def find_routes(day, orig, dest):