Linkedin Posts Informations Parser 馃煝 UpToDate 9 feb-2024 avatar
Linkedin Posts Informations Parser 馃煝 UpToDate 9 feb-2024
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Linkedin Posts Informations Parser 馃煝 UpToDate 9 feb-2024

Linkedin Posts Informations Parser 馃煝 UpToDate 9 feb-2024

saswave/linkedin-posts-informations-parser
Try for free

1 day trial then $19.00/month - No credit card required now

Allows you to extract all informations from a post (number of likes, comments, shares, video, image, document, article link with the exact date and time of the post). Input can be a /posts /company or /in url and it will parse multiple posts from the source (organic posts and promoted ads).

The code examples below show how to run the Actor and get its results. To run the code, you need to have an Apify account. Replace <YOUR_API_TOKEN> in the code with your API token, which you can find under Settings > Integrations in Apify Console. Learn mode

Node.js

Python

curl

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4client = ApifyClient("<YOUR_API_TOKEN>")
5
6# Prepare the Actor input
7run_input = {
8    "url": "https://www.linkedin.com/company/financial-times/",
9    "days_since_post": 30,
10    "cookies": [{
11            "domain": ".linkedin.com",
12            "expirationDate": 1716940616.08443,
13            "hostOnly": False,
14            "httpOnly": False,
15            "name": "test",
16            "path": "/",
17            "sameSite": "no_restriction",
18            "secure": True,
19            "session": False,
20            "storeId": "0",
21            "value": "fake",
22            "id": 1,
23        }],
24    "proxyConfiguration": { "useApifyProxy": True },
25}
26
27# Run the Actor and wait for it to finish
28run = client.actor("saswave/linkedin-posts-informations-parser").call(run_input=run_input)
29
30# Fetch and print Actor results from the run's dataset (if there are any)
31for item in client.dataset(run["defaultDatasetId"]).iterate_items():
32    print(item)
Developer
Community logoMaintained by Community
Actor metrics
  • 34 monthly users
  • 43.0% runs succeeded
  • 0.8 days response time
  • Created in Oct 2023
  • Modified 1 day ago

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