bcra-py
An unofficial Python wrapper to interact with the official API of the Central Bank of the Argentine Republic (BCRA).
bcra-py allows to easily query financial information, monetary statistics, exchange rates, debtors' credit risk, reported checks, and the BCRA's transparency regime. The library supports exporting the results directly to Pandas DataFrames, CSV, JSON, or Excel.
Features
- Monetary Statistics (
monetarias): Query monetary variables and their methodology using dynamic properties. - Exchange Rates (
cambiarias): Retrieve the list of supported currencies and the official exchange rates. - Central de Deudores (
deudores): Search for credit status, historical debt reports, and rejected checks using a CUIT/CUIL/CDI. - Checks (
cheques): Get a list of financial entities and query reported (stolen/lost) checks. - Transparency (
transparencia): Access comparative financial data regarding savings accounts, term deposits, credit cards, and loans. - Data Export: Easily convert API responses to
pandas.DataFrame,CSV,JSON, orExcel.
Installation
pip install bcra-py
Or install locally from source:
git clone https://github.com/marpeand/bcra-py.git
cd bcra-py
pip install .
Quick Start
from bcrapy.client import BCRAClient
# Initialize the client
client = BCRAClient()
# Example 1: Query the BADLAR rate (dynamically generated monetary variable)
df_badlar = client.monetarias.badlar_bancos_privados(
desde="2023-01-01",
hasta="2023-01-31"
).to_dataframe()
print(df_badlar.head())
# Example 2: Query the 'Central de Deudores' (Credit Risk) using a CUIT/CUIL (e.g. Banco Nación)
deudores_resp = client.deudores.deudas("30-50001091-2")
print(deudores_resp.to_dataframe())
# Example 3: Query today's exchange rates
cotizaciones = client.cambiarias.cotizaciones()
print(cotizaciones.to_dataframe())
# Export data to CSV / JSON / Excel
res = client.transparencia.plazos_fijos()
res.to_csv("plazos_fijos.csv")
res.to_excel("plazos_fijos.xlsx")
res.to_json("plazos_fijos.json")
Module Overview
| Resource | Description | Example Methods |
|---|---|---|
client.monetarias |
Monetary statistics | metodologia(), badlar_bancos_privados(), reservas_internacionales() |
client.cambiarias |
Currencies and exchange rates | maestros(), cotizaciones(fecha), cotizacion(moneda) |
client.deudores |
Credit info and debtors | deudas(cuit), deudas_historicas(cuit), cheques_rechazados(cuit) |
client.cheques |
Banking entities and checks | entidades(), denunciados(codigoEntidad, numeroCheque) |
client.transparencia |
Bank products comparison | caja_ahorro(), plazos_fijos(), tarjetas_de_credito(), prestamos_personales() |
License
This project is licensed under the terms of the MIT License.
Metadata
Release files for bcra-py 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bcra_py-0.1.0.tar.gz | 19.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bcra_py-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 42.5 kB
Release files / bcra_py-0.1.0.tar.gz
| Download URL | bcra_py-0.1.0.tar.gz |
|---|---|
| Size | 19.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
4cf256979431cdb87ec9d6869ec5ee8e701874a956594211af89594f121a2176
|
|
BLAKE2b-256 checksum How to use checksums |
6af7a3c657746b45b1b15bff78127c4329adb5673247989eb21ef9ec71e22c39
|
| Upload date | |
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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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Transparency logRelease files / bcra_py-0.1.0-py3-none-any.whl
| Download URL | bcra_py-0.1.0-py3-none-any.whl |
|---|---|
| Size | 23.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
03534385e387eac56c793f10ef0000588a65994eda75dced111ce964a2989e6e
|
|
BLAKE2b-256 checksum How to use checksums |
00c51f7508cd1906db3f14f77000f9a56556034b44a5b392a6193195df28cdb7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 9, 2026.
Transparency log