Skip to main content

Printing out the entire Table Row of one or more found elements

This is my code so far:

from bs4 import BeautifulSoup
import requests
import re

day = input("Für welchen tag willst du den vertretungsplan sehen? \n Heute = 1, Morgen = 2, Übermorgen = 3 \n")
if day == 1 or 2 or 3:
    pass
else:
    print("Bitte gebe eine zahl von 1-3 ein!")

url = f"https://jenaplan-weimar.de/vplan/Vertretungsplaene/SchuelerInnen/subst_00{day}.htm"
result = requests.get(url)
doc = BeautifulSoup(result.text, "html.parser")
wunschklasse = input("Für welche Klasse möchtest du den Vertretungsplan sehen? (Achtung, bitte beachte die Abkürzungen!) ")
klasse = doc.find_all(text=re.compile(f"{wunschklasse}.*"))
# parent = klasse[0].parent
# parent2 = parent.parent
# parent3 = parent2.parent

if klasse == []:
    print("Sry aber deine gewählte Klasse hat keine Vertertung bzw keinen Ausfall")
else:
    print(f"Für {wunschklasse} wurde folgendes gefunden: {klasse}")

As you can see, I let the user gives me a value, that then is being searched in the table. So far, all found values are being printed out, but I also want to print out the entire table row where the Value is standing in. In the end, it should give me all aviable information to the value from the user. Thank you for your help



source https://stackoverflow.com/questions/71638172/printing-out-the-entire-table-row-of-one-or-more-found-elements

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype
Post a Comment
Read more

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...
Post a Comment
Read more

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...
Post a Comment
Read more