autofillcvlac 0.1.20

A Python package for processing research data and CVLaC information

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

Usage

from autofillcvlac import flatten, 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

# Flatten a list of lists
nested_list = [[1, 2], [3, 4], [5]]
flat_list = flatten(nested_list)
print(flat_list)  # [1, 2, 3, 4, 5]

# Get research products and extract data for CVLaC forms
response = get_research_products('67dc9885444bab3c3f1a7df2')
if response.status_code == 200:
    products = response.json().get('data', [])
    
    # Filter journal articles missing in CvLAC
    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']}")
            # Use extracted data directly with fill_scientific_article
            # result = fill_scientific_article(**extracted_data)

# Authenticate with CVLaC system
auth_result = authenticate_cvlac('Colombian', 'John Doe', '12345678', 'your_password')
if auth_result['status'] == 'success':
    print("Authentication successful!")
    
    # Fill scientific article form
    article_result = fill_scientific_article(
        title="Machine Learning Applications in Healthcare",
        article_type="111",  # Completo
        initial_page="15",
        final_page="28", 
        language="EN",
        year=2023,
        month=6,
        volume="10",
        issue="2",
        publication_medium="H",  # 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']}")

# Authenticate with CVLaC system for foreign nationality
auth_result = authenticate_cvlac('Extranjero - otra', 'John Doe', 'dummy', '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']}")

# Get research products from API
response = get_research_products('67dc9885444bab3c3f1a7df2')
if response.status_code == 200:
    products = response.json().get('data', [])
    
    # Filter products by year
    filtered_products = filter_products_by_year(products, 2002)
    
    # Create DataFrame for analysis
    df = create_products_dataframe(filtered_products)
    print(df.head())

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 Latin American and Caribbean researchers.