Metadata-Version: 2.1
Name: linkedframe
Version: 1.0.1
Summary: A library for enriching data with LinkedIn and Google Search API and Proxy Curl
Author: Nitin Kapoor
Author-email: officialnitinkapoor@gmail.com
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.12
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: requests
Requires-Dist: tqdm
Requires-Dist: googlesearch-python
Requires-Dist: proxycurl
Requires-Dist: openai
Requires-Dist: python-dotenv
Requires-Dist: pydantic
Provides-Extra: dev
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: pytest-cov ; extra == 'dev'

# 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:

```bash
pip install linkedframe
```

## Usage

To get started with LinkedFrame, follow these steps:

**Step 1: Import the necessary modules**
```python
from linkedframe.enrichment import LinkedInDataEnrichmentProcessor
```

**Step 2: Initialize the `LinkedInDataEnrichmentProcessor` with your API keys**
```python
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**
```python
df = pd.DataFrame({'email': ['example@example.com']})
```

**Step 4: Process the emails to enrich the DataFrame with LinkedIn data**
```python
processed_df = df_processor.process_emails(df, email_col='email')
```

**Step 5: Analyze and use the enriched data as needed**
```python
print(processed_df)
```

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.

