Download comments from Linkedin with Python
Use Linkedin Company Ads to get comments from Linkedin with Python. Want to grab comments from Linkedin? Linkedin Company Ads makes it quick and easy. Just tell it what to download and you’ll get your Linkedin comment available offline, for whenever you want it.
1Get an Apify account
You can’t get data from the inside of the platform if you’re not authorized in it. So to get started, create an Apify account. It only takes a minute and it's free of charge.
Sign up for free
2Initialize the API using your token
After you’ve registered, it’s time to add your secret authentication token. You can find your API token on the Integrations page in Apify Console.
Get your token in Console3Define input and copy it in JSON
To get the data from Linkedin you first need to use Linkedin Company Ads to extract it. So let’s add a simple input and transfer it to your code. You can copy your input as a JSON from the Linkedin Company Ads’s Input tab in Console.
4Integrate Apify into your codebase
Finally, call the Linkedin Company Ads from your Python project. Use Apify Client or Endpoints. You’ll be able to export scraped Linkedin data in no time by running the sample code below ↓.
5Monitor your Linkedin Company Ads runs
Head over to our dashboard and see how Linkedin Company Ads runs are executed in real time. Here you can also download the run logs and keep an eye on the API’s performance.
Go to dashboardGet your Python project up and running
Add-on to step 4: start your Python project by executing this code snippet in your go-to environment.
1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9 "companies": [
10 "https://www.linkedin.com/company/financial-times/",
11 "https://www.linkedin.com/company/bloomberg-news/",
12 ],
13 "ad_limit": 15,
14 "ad_description": "yes",
15}
16
17# Run the Actor and wait for it to finish
18run = client.actor("saswave/linkedin-company-ads").call(run_input=run_input)
19
20# Fetch and print Actor results from the run's dataset (if there are any)
21print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
22for item in client.dataset(run["defaultDatasetId"]).iterate_items():
23 print(item)
24
25# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
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Web scraping is a handy method for collecting information from various websites. It's like having a digital assistant that visits web pages on your behalf, pulling out the details you need such as prices, descriptions, addresses, and contact information. But it's more than just text; this tool can also download images and videos, making it a comprehensive way to gather content from the online world. It takes care of all the complex, technical parts, so you don't have to.
Web scraping is a method where you choose websites to collect specific content, including text, images, and videos. You begin by identifying the web pages that host the visual media you're interested in. Next, you use a web scraping tool tailored to locate the parts of the page containing the images or videos you want to download. Once the tool is set up and run, it navigates to the chosen web pages, identifies the images and videos, and downloads them for you. It's a streamlined way to gather pictures and videos from online sources without having to manually download each item.
Yes, web scraping is legal for gathering public information from websites. But be careful with personal or confidential data, as well as intellectual property, because laws and regulations might protect them. It's good practice to check the website's rules or terms of service to know what's allowed. If you're not sure, getting legal advice can help ensure you're using web scraping correctly and within the law.
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