Access CleanJobData from Python for data science, analytics, and AI training.
Install the requests library.
pip install requestsFetch job listings with a GET request.
import requests
res = requests.get('https://api.cleanjobdata.com/jobs',
headers={'X-API-Key': 'your-key'},
params={'query': 'software engineer', 'limit': 50})
jobs = res.json()['data']Load job data into pandas for analysis.
import pandas as pd
df = pd.DataFrame(jobs)
print(df['salary'].describe())Yes — it's plain REST/JSON, so httpx.AsyncClient or aiohttp work exactly like requests: `async with httpx.AsyncClient() as client: res = await client.get('https://api.cleanjobdata.com/jobs', headers={'X-API-Key': API_KEY}, params={'title': 'engineer', 'remote': 'true'})`. This matters most if you're fanning out requests across several filters or cursors concurrently — watch `X-RateLimit-Remaining`, since concurrent calls burn the per-second bucket faster than sequential ones.
Not a dedicated package — the API is a handful of plain JSON endpoints, so a `requests.Session` with your key set as a default header covers it: `session = requests.Session(); session.headers.update({'X-API-Key': API_KEY})`, then `session.get('https://api.cleanjobdata.com/jobs', params={'limit': 50}).json()['data']`. That's usually all the abstraction a Python project needs on top of the REST API.