BCRA API Connector

A Python connector for the BCRA (Banco Central de la República Argentina) APIs, covering Principal Variables/Monetary Statistics, Cheques, Exchange Rate Statistics, and Central de Deudores (Debtor Registry).

Features

Comprehensive Data Access: Fetch Principal Variables, Monetary Statistics, Checks information, Exchange Rates, and Debtor Registry data.
Central de Deudores: Query debtor information, historical debts, and rejected checks by CUIT/CUIL.
DataFrame Support: Convert API responses to pandas DataFrames with to_dataframe() methods.
Historical Data: Easily retrieve and analyze historical time series for any variable.
Robustness: Built-in retry logic with exponential backoff and safe failure handling.
Developer Friendly:
- Full Type Hinting for better IDE support.
- Bilingual context (Spanish API / English Wrapper).
- Detailed debug logging.
Configurable: Options for SSL verification, retries, and timeouts.

Documentation

Full documentation, including installation instructions, usage examples, and API reference, is available at:

Installation

pip install bcra-connector

# With pandas support for DataFrame conversion
pip install "bcra-connector[pandas]"

# With numpy, needed only by get_variable_correlation()
pip install "bcra-connector[analytics]"

For detailed installation instructions and requirements, see our Installation Guide.

Quick Start

Get up and running in seconds:

from bcra_connector import BCRAConnector

connector = BCRAConnector()

# 1. Catalog of monetary series, with each one's latest value
variables = connector.get_principales_variables()
print(f"Found {len(variables)} series")

# 2. Latest value of a series, by ID (1 = Reservas internacionales)
latest = connector.get_latest_value(1)
print(f"Reserves: {latest.valor} on {latest.fecha}")

# 3. Last 30 days of a series, by name (newest first, as the API returns it)
history = connector.get_variable_history("Reservas internacionales", days=30)
for point in history[:5]:
    print(point.fecha, point.valor)

# 4. Official exchange rate: pesos per dollar
usd_ars = connector.get_currency_pair_evolution("USD", "ARS", days=7)
print(f"USD/ARS on {usd_ars[-1]['fecha']}: {usd_ars[-1]['tasa']}")

Contributing

Contributions are welcome! Please read our:

Security

For vulnerability reports, please review our Security Policy.

Change Log

See CHANGELOG.md for a list of changes and version updates.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

This project is not officially affiliated with or endorsed by the Banco Central de la República Argentina. Use at your own risk.

Metadata

Release files for bcra-connector 0.12.0

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Source distribution for bcra-connector 0.12.0
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File	Interpreter	ABI	Platform	Reset
bcra_connector-0.12.0-py3-none-any.whl 34.0 kB Sep 19, 2026	Python 3	none	any	Details

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Publishing repository: github.com/PPeitsch/bcra-connector
Publishing commit: github.com/PPeitsch/bcra-connector/tree/d3b6e0fa5e824438165366618c4c45a13b448bd7

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Publishing configuration: github.com/PPeitsch/bcra-connector/blob/d3b6e0fa5e824438165366618c4c45a13b448bd7/.github/workflows/test-and-publish.yaml
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Size	34.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`c7281dc4afead2a66bf2ec78cc79682086ff522e922e0f9df3777d04e773de17`
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Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

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Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/PPeitsch/bcra-connector
Publishing commit: github.com/PPeitsch/bcra-connector/tree/d3b6e0fa5e824438165366618c4c45a13b448bd7

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Publishing configuration: github.com/PPeitsch/bcra-connector/blob/d3b6e0fa5e824438165366618c4c45a13b448bd7/.github/workflows/test-and-publish.yaml
Publishing logs: github.com/PPeitsch/bcra-connector/actions/runs/35474088340/attempts/1

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