Skip to main content

A Python package for processing research data and CVLaC information

Project description

autofillcvlac

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

Installation

pip install autofillcvlac

Usage

from autofillcvlac import flatten, authenticate_cvlac
from autofillcvlac.core import get_research_products, filter_products_by_year, create_products_dataframe

# 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]

# Authenticate with CVLaC system
auth_result = authenticate_cvlac('Colombian', 'John Doe', '12345678', 'your_password')
if auth_result['status'] == 'success':
    print("Authentication successful!")
else:
    print(f"Authentication failed: {auth_result['message']}")

# Authenticate with CVLaC system for foreign nationality
auth_result = authenticate_cvlac('Extranjero - otra', 'John Doe', '12345678', 'your_password', 'Estados Unidos')
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
  • 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

Development

This package is built from research workflows originally developed in Jupyter notebooks for analyzing academic publication data from Latin American and Caribbean researchers.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

autofillcvlac-0.1.4.tar.gz (6.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

autofillcvlac-0.1.4-py3-none-any.whl (6.4 kB view details)

Uploaded Python 3

File details

Details for the file autofillcvlac-0.1.4.tar.gz.

File metadata

  • Download URL: autofillcvlac-0.1.4.tar.gz
  • Upload date:
  • Size: 6.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for autofillcvlac-0.1.4.tar.gz
Algorithm Hash digest
SHA256 1af373b3486a86ffdec42329c06e03f3c1d9af0c52a53abca4c73621d7a33782
MD5 ff09881c368c7ae73f2a82ac9fbb9303
BLAKE2b-256 f277c32dbb28bafb39206ad9240edc73b1947a324e0881657442e71a95253380

See more details on using hashes here.

File details

Details for the file autofillcvlac-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: autofillcvlac-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 6.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for autofillcvlac-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 6299b35666c8440e12a2b3b75bcb77d5175f805602fa108d9cc3285fe9e936f5
MD5 92655b564cfe05969534dde3bd0575da
BLAKE2b-256 bc632fd8de163620d60fdb0f4239dd5bd6b2fada663d06701d7032899cb0cf94

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page