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Quickstart

The simplest way to search is to initialize the client and call the search endpoint. PyWuzzuf handles pagination and session management automatically.

import asyncio
from pywuzzuf import WuzzufClient

async def main():
    async with WuzzufClient() as client:
        print("🔍 Searching for 'Python Developer'...")

        # Fetch the first 5 results
        result = await client.jobs.search("Python Developer").limit(5).all()

        for job in result.items:
            print(f"- {job.attributes.title}")

if __name__ == "__main__":
    asyncio.run(main())

from pywuzzuf import SyncWuzzufClient

with SyncWuzzufClient() as client:
    print("🔍 Searching for 'Python Developer'...")

    # Fetch the first 5 results
    result = client.jobs.search("Python Developer").limit(5).all()

    for job in result.items:
        print(f"- {job.attributes.title}")

Expected Output:

🔍 Searching for 'Python Developer'...
- Senior Python Developer
- Python Backend Engineer (Django)
- Data Scientist (Python)
- ...

2. Accessing Job Data

Each result is an EnrichedJob object. This means the standard job attributes are available, and the associated Company data is pre-fetched for you.

Job Attributes

Core metadata lives under .attributes:

job.attributes.title        # "Senior Python Developer"
job.attributes.description  # Full HTML description
job.attributes.posted_at    # datetime object (UTC)
job.attributes.location     # Location object (City, Country)

Company Enrichment

Unlike raw API responses, PyWuzzuf attaches the full company profile directly to the job object:

if job.company:
    print(f"Company: {job.company.attributes.name}")
    print(f"Website: {job.company.attributes.website}")

Data Completeness & Null Values

Job listings depend entirely on the recruiter or company filling out the job post application on Wuzzuf.

Common missing fields include:

  • job.company (if enrichment fails or data is absent)
  • job.attributes.requirements
  • job.attributes.salary details

Always use defensive checks when accessing these attributes:

# Safe access pattern
salary = job.attributes.salary
if salary and salary.min:
    print(f"Salary: {salary.min} - {salary.max}")

if job.company:
    print(f"Company: {job.company.attributes.name}")

For advanced auditing, refer to the Data Quality Report in the Data Models documentation.

3. Filtering Results

Use SearchFilters to narrow down your search. For example, finding jobs posted in the last 24 hours.

from pywuzzuf import SearchFilters, DateRange

filters = SearchFilters(posted_within=DateRange.LAST_24_HOURS)

result = await client.jobs.search("DevOps").filter(filters).all()
print(f"Found {len(result.items)} recent DevOps jobs.")

from pywuzzuf import SearchFilters, DateRange

filters = SearchFilters(posted_within=DateRange.LAST_24_HOURS)

result = client.jobs.search("DevOps").filter(filters).all()
print(f"Found {len(result.items)} recent DevOps jobs.")

4. Running Your Script

Save your code to a file (e.g., main.py) and run it.

uv run main.py

python main.py

Next Steps

  • Filtering Guide: Dive deep into location, career level, and date filters.
  • Pagination: Learn how to handle large datasets and progress tracking.
  • Resilience: Handle rate limits and bot detection gracefully.