autofillcvlac

A Python package for processing research data and automatically fill the CVLaC (Curriculum Vitae de Latinoamérica y el Caribe) information.

Installation

pip install autofillcvlac

Complete Usage Example

For a comprehensive, step-by-step example of how to use this package, see the check_github.ipynb notebook. This Jupyter notebook demonstrates the complete workflow from API data extraction to CVLaC form filling.

Usage

Accessing Research Data from Impactu API

The cod_rh is the unique identifier for Colombian researchers registered in the Scienti platform of MINCIENCIAS. The Impactu API (https://impactu.colav.co/) provides access to research products that may be missing from researchers' CvLAC profiles.

from autofillcvlac import authenticate_cvlac, fill_scientific_article, extract_scientific_article_data
from autofillcvlac.core import get_research_products, filter_products_by_year, create_products_dataframe, filter_missing_journal_articles
import getpass

cod_rh = '0000177733'  # Example: Colombian researcher ID
products = get_research_products(cod_rh)

Finding Missing Journal Articles

Filter journal articles missing in CvLAC - these are articles from the last 5 years that are not yet registered in the researcher's Scienti profile:

missing_articles = filter_missing_journal_articles(products)

# Extract data for each article to use with fill_scientific_article
for product in missing_articles:
    extracted_data = extract_scientific_article_data(product)
    if extracted_data:
        print(f"Ready to fill: {extracted_data['title']}")
        print(f"Journal: {extracted_data.get('journal_name', 'N/A')}")
        print(f"Year: {extracted_data.get('year', 'N/A')}")

Secure Authentication

Use secure credential input for CVLaC authentication:

documento_identificacion = getpass.getpass('documento_identificacion: ')
password = getpass.getpass('password: ')

auth_result = authenticate_cvlac(nacionalidad='Colombiana', nombres='John Doe', 
                                documento_identificacion=documento_identificacion, 
                                password=password, headless=False)

Filling Scientific Article Forms

Once authenticated, you can fill scientific article forms using two approaches:

Example 1: Using Data Extracted from Impactu API

Use the first missing article found from the API and automatically fill the form with extracted data:

if auth_result['status'] == 'success':
    print("Authentication successful!")
    
    if missing_articles:
        first_article = missing_articles[0]
        extracted_data = extract_scientific_article_data(first_article)
        
        if extracted_data:
            print(f"Filling form for: {extracted_data['title']}")
            article_result = fill_scientific_article(**extracted_data)
            
            if article_result['status'] == 'success':
                print("Article form filled successfully!")
                from helium import get_driver
                driver = get_driver()
                driver.get_screenshot_as_file('result.png')
                print("Screenshot saved as result.png showing the filled form")
            else:
                print(f"Error: {article_result['message']}")

Example 2: Manual Form Filling with Custom Data

Fill the form manually with your own research article data:

    article_result = fill_scientific_article(
        title="Machine Learning Applications in Healthcare",
        article_type="111",
        initial_page="15",
        final_page="28", 
        language="EN",
        year=2023,
        month=6,
        volume="10",
        issue="2",
        publication_medium="Electrónico",
        website_url="https://example-journal.com/article/123",
        doi="10.1234/example.2023.123"
    )
    
    if article_result['status'] == 'success':
        print("Article form filled successfully!")
    else:
        print(f"Error: {article_result['message']}")
else:
    print(f"Authentication failed: {auth_result['message']}")

Foreign Nationality Authentication

For researchers with foreign nationality, use the extended authentication parameters:

auth_result = authenticate_cvlac(nacionalidad='Extranjero - otra', nombres='John Doe', 
                                documento_identificacion='dummy', password='your_password', 
                                pais_nacimiento='Estados Unidos', fecha_nacimiento='1990-05-15')
if auth_result['status'] == 'success':
    print("Authentication successful!")
else:
    print(f"Authentication failed: {auth_result['message']}")

Advanced Data Analysis

Perform additional data processing and analysis:

response = get_research_products(cod_rh)
if response.status_code == 200:
    products = response.json().get('data', [])
    
    filtered_products = filter_products_by_year(products, 2002)
    
    df = create_products_dataframe(filtered_products)
    print(df.head())

The screenshot above shows the CVLaC interface after successfully filling a scientific article form using the fill_scientific_article(**extracted_data) function. The form fields are automatically populated with data extracted from the Impactu API.

Key Features: Impactu API Integration

This package leverages the Impactu API (https://impactu.colav.co/) to identify research products missing from Colombian researchers' CvLAC profiles:

• cod_rh: The unique identifier for Colombian researchers registered in the Scienti platform of MINCIENCIAS
• Missing Product Detection: Automatically identifies journal articles from the last 5 years that haven't been registered in CvLAC
• Automated Data Extraction: Converts research product metadata into CVLaC form parameters
• Seamless Integration: Direct workflow from API data to form filling with fill_scientific_article(**extracted_data)

The API provides comprehensive research data that researchers can use to keep their CvLAC profiles up-to-date with their latest publications.

Features

• Fetch research products from the Impactu API
• Filter products by publication year and source
• Filter journal articles missing in CvLAC by criteria (issue #39)
• Extract scientific article data from research product dictionaries for CVLaC forms
• Convert research data to pandas DataFrames for analysis
• Extract citation counts from multiple sources (OpenAlex, Scholar)
• Process author information and external IDs
• Authenticate with CVLaC (Curriculum Vitae de Latinoamérica y el Caribe) system using web automation
• Fill scientific article forms in CVLaC with metadata including title, type, pages, language, publication details, and DOI

Development

This package is built from research workflows originally developed in Jupyter notebooks for analyzing academic publication data from Colombian researchers registered in the Scienti platform of MINCIENCIAS.