Skip to main content

How to download chromedriver instead of webpage with python requests library

Today I'm creating a Python script to find a specific version of chromedriver here. My intention is to make a request to the URL containing the specific version of chromedriver I need to download and save it to the same directory as the script. However, each time I run my code to install a file, say chromedriver_win32.zip in this folder, I end up downloading the webpage it is stored on instead of the file itself.

Here's my script:

#Get the exact folder name containing the version we need to download
chromedriverVersionUrl = "https://chromedriver.storage.googleapis.com/LATEST_RELEASE_100"
response = requests.get(chromedriverVersionUrl)
latestVersionNumber = response.text

#Target the folder of the exact version we need to download and download it!
downloadUrl = "https://chromedriver.storage.googleapis.com/index.html?path=" + latestVersionNumber + "/chromedriver_win32.zip"

#Make the request and write the response to a file
r = requests.get(downloadUrl, allow_redirects=True)
open('chromedriver.zip', 'wb').write(r.content)

Every time, chromedriver.zip ends up being a very small file that windows says is a corrupted zip file. I tried downloading the contents as a .txt file and it turned out I was just downloading the webpage.

I have tried using wget and the dload libraries to download this file in addition to requests, but they have all yielded the same result. Could someone please show me what I might be doing wrong?



source https://stackoverflow.com/questions/75803718/how-to-download-chromedriver-instead-of-webpage-with-python-requests-library

Comments

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

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...

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...