Upwork Job Extractor ⚡

Pricing

Pay per event

Try for free

Go to Apify Store

Upwork Job Extractor ⚡

Try for free

upwork job extractor ⚡| 0.001 | fast, cheap, cost-effective, reliable, up-to-date, and highly stable data scraping service, optimized for long-term use with the fastest crawling speeds, low container usage, and pricing to boost your upwork job scraper performance!

Pricing

Pay per event

Rating

4.6

(9)

Developer

Flash Mage

Maintained by Community

Actor stats

Bookmarked

479

Total users

Monthly active users

7.2 hours

Issues response

3 days ago

Last modified

Categories

Jobs

Automation

Lead generation

You can access the Upwork Job Extractor ⚡ programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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 = { "update_job_ids": [
9        "1974229435317190991",
10        "1974184115785526950",
11        "1974229291820489729",
12        "1974229162153307814",
13        "1974229143502953454",
14        "1974229140898021711",
15        "1974229039236750318",
16        "1974183702387982672",
17        "1974228964049387855",
18        "1974183649217059822",
19    ] }
20
21# Run the Actor and wait for it to finish
22run = client.actor("flash_mage/upwork").call(run_input=run_input)
23
24# Fetch and print Actor results from the run's dataset (if there are any)
25print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
26for item in client.dataset(run["defaultDatasetId"]).iterate_items():
27    print(item)
28
29# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Upwork Job Extractor ⚡| Upwork Job Scraper API in Python

The Apify API client for Python is the official library that allows you to use Upwork Job Extractor ⚡ API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Upwork Job Extractor ⚡ API in JavaScript

Upwork Job Extractor ⚡ API through CLI

Upwork Job Extractor ⚡ OpenAPI definition

Upwork Job Extractor ⚡ API

Upwork Job Scraper🔥

nec/upwork-job-scraper

Streamline your Upwork.com job search

NEC

217

1.1

Upwork Job Scraper

deltaspider/upwork-job-scraper

Automatically and efficiently scrape Upwork.com job listings.

delta spider

230

2.8

Upwork Extractor

jupri/upwork

💫 Scrape Upwork.com Jobs

cat

1.3K

4.7

Upwork Details Scraper

corpusculus/upwork-details-scraper

Search for jobs on upwork.

oxo

1.5

Upwork Job Scraper

getdataforme/upwork-actor

Apify actor that scrapes Upwork job listings, extracting titles, descriptions, skills, and posting details. Perfect for market research, competitive analysis, and lead generation....

GetDataForMe

235

3.0

Upwork Job Scraper

matthewjames/upwork-job-scraper

Scrape recent and relevant Upwork.com jobs, bypasses captchas.

Matthew James

387

4.4

Upwork Jobs Scraper

jyaba/upwork-jobs-scraper

The Upwork Job Scraper is a powerful Apify Actor designed to extract job postings from Upwork efficiently and reliably. It automates the process of gathering detailed job data, including titles, descriptions, budgets, skills, and publication times and businesses to analyze opportunities at scale.

Jyaba

Upwork Job Scraper

neatrat/upwork-job-scraper

Scrape Upwork jobs without limits 🌟 Bypass CAPTCHAs & apply custom filters.

Neatrat

1.7K

4.5

Upwork | Search |Job(s) | Scraper (No Cookies) (Richest output)

memo23/upwork-jobs-scraper

Extract detailed Upwork job listings with our scraper. Get job descriptions, budgets, required skills, client history, and engagement terms in a structured format. Perfect for market research and competitive analysis.