linkedframe 1.0.3

A library for enriching data with LinkedIn and Google Search API and Proxy Curl

LinkedFrame

LinkedFrame is a Python library designed to enrich data using LinkedIn, Google Search API, and Proxy Curl. It provides tools to fetch and process LinkedIn data, making it easier to integrate and analyze professional information.

Features

• Google Search Integration: Search for LinkedIn profiles using email addresses.
• Proxy Curl Integration: Fetch detailed LinkedIn profile data.
• Data Enrichment: Enhance LinkedIn data with additional information such as educational level, work field, and profile language using OpenAI.

Installation

To install LinkedFrame, use pip:

pip install linkedframe

Usage

To get started with LinkedFrame, follow these steps:

Step 1: Import the necessary modules

from linkedframe.enrichment import LinkedInDataEnrichmentProcessor

Step 2: Initialize the LinkedInDataEnrichmentProcessor with your API keys

df_processor = LinkedInDataEnrichmentProcessor(
    cse_id="your_cse_id",
    google_console_api_key="your_google_console_api_key",
    openai_key="your_openai_key",
    proxycurl_api_key="your_proxycurl_api_key"
)

Step 3: Prepare your DataFrame with email addresses

df = pd.DataFrame({'email': ['[e-mail]']})

Step 4: Process the emails to enrich the DataFrame with LinkedIn data

processed_df = df_processor.process_emails(df, email_col='email')

Step 5: Analyze and use the enriched data as needed

print(processed_df)

Step 6: Check the ProxyCurl API limit

df_processor.get_limits()

This is a basic example to demonstrate how to use LinkedFrame for data enrichment.

To use LinkedFrame, you will need the following API keys:

• Google Custom Search Engine (CSE) ID
• Google Console API Key
• OpenAI API Key
• ProxyCurl API Key

These API keys are required to initialize the LinkedInDataEnrichmentProcessor and utilize the library's features.