This project provides a Python client for interacting with the Nubela API, specifically for querying LinkedIn profiles.

• Easy-to-use interface for querying Nubela profiles
• Caching mechanism to store and reuse previous query results
• Offline mode for development and testing
• Configurable settings using environment variables

To install the required dependencies, run:

pip install requests pydantic-settings

from nubela_api import NubelaAPI, NubelaSettings

settings = NubelaSettings(api_key="your_api_key_here")

api = NubelaAPI(settings=settings, offline=False)

linkedin_url = "https://www.linkedin.com/in/example-profile" response = api.query_linkedin(linkedin_url)

print(response.full_name) print(response.occupation)

You can pass custom parameters to the API call:

custom_params = { "linkedin_profile_url": "https://www.linkedin.com/in/example-profile", "extra": "include", "skills": "include", } response = api.query(custom_params)

The client automatically caches responses. To disable caching for a specific query:

response = api.query_linkedin(linkedin_url, use_cache=False)

For development or testing, you can enable offline mode:

api = NubelaAPI(settings=settings, offline=True)

This will raise a ValueError if an API call is attempted.

You can configure the API client using environment variables:

• NUBELA_API_KEY: Your Nubela API key
• NUBELA_API_ENDPOINT: The API endpoint (default: "https://nubela.co/proxycurl/api/v2/linkedin")

The client will raise exceptions for various error conditions:

• ValueError: If the API key is missing or if trying to make an API call in offline mode
• OfflineError: Custom exception for offline-related errors (not currently used in the provided code)

Contributions are welcome! Please feel free to submit a Pull Request.

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