bcbpy

Python client for the BCB SGS (Sistema Gerenciador de Series Temporais) API from the Banco Central do Brasil.

Fetch Brazilian economic and financial time series as pandas DataFrames with a simple, Pythonic interface. Includes 115 curated series codes covering exchange rates, interest rates, inflation, GDP, employment, and more.

Installation

pip install bcbpy

Or from source:

git clone https://github.com/TeodoroRodrigo/bcbpy.git
cd bcbpy
pip install -r requirements.txt

Requirements

• Python 3.10+
• pandas
• requests

Quick Start

from bcbpy import fetch_series, fetch_last, fetch_multiple, INTEREST_RATES, EXCHANGE_RATES

# Last 10 CDI daily rates
cdi = fetch_last(INTEREST_RATES["CDI_DAILY"], n=10)
print(cdi)

# USD/BRL exchange rate for 2024
usd = fetch_series(EXCHANGE_RATES["USD_SALE_DAILY"], start_date="2024-01-01", end_date="2024-12-31")
print(usd)

# Multiple series merged into one DataFrame
df = fetch_multiple(
    {"CDI": INTEREST_RATES["CDI_DAILY"], "SELIC": INTEREST_RATES["SELIC_DAILY"]},
    start_date="2024-01-01",
    end_date="2024-12-31",
)
print(df.tail())

API Reference

Functions

fetch_series(code, start_date=None, end_date=None)

Fetch a time series by its SGS numeric code. Returns a pandas DataFrame indexed by date.

from bcbpy import fetch_series

# Accepts YYYY-MM-DD or DD/MM/YYYY date formats
ipca = fetch_series(433, start_date="2023-01-01", end_date="2024-12-31")

fetch_last(code, n=10)

Fetch the last N observations of a series.

from bcbpy import fetch_last

selic = fetch_last(11, n=5)

fetch_multiple(codes_dict, start_date=None, end_date=None)

Fetch multiple series and merge them into a single DataFrame, one column per series.

from bcbpy import fetch_multiple

df = fetch_multiple({"CDI": 12, "SELIC": 11, "TR": 226}, start_date="2024-01-01")

list_codes(category=None)

Print all available series codes. Pass a category name to filter.

from bcbpy import list_codes

list_codes()                        # all 115 codes across 14 categories
list_codes("INTEREST_RATES")        # only interest rate codes

search_codes(keyword)

Search codes by keyword (case-insensitive). Returns a dict of matches.

from bcbpy import search_codes

results = search_codes("IPCA")      # finds 15 IPCA-related codes
results = search_codes("USD")       # finds USD exchange rate codes

Exceptions

Exception	When
SGSError	Base exception for all API errors
SGSRateLimitError	API returns HTTP 429 (too many requests)
SGSEmptyResponseError	No data returned for the given query

Error Handling

from bcbpy import fetch_series, SGSRateLimitError, SGSEmptyResponseError

try:
    df = fetch_series(433, start_date="2024-01-01")
except SGSRateLimitError:
    print("Rate limited — wait and retry")
except SGSEmptyResponseError:
    print("No data for this date range")

Available Series Codes

115 curated codes organized in 14 categories:

Category	Series	Examples
EXCHANGE_RATES	6	USD/BRL daily sale/purchase, monthly averages
INTEREST_RATES	10	Selic, CDI, TR, TBF, TJLP
INFLATION	17	IPCA, INPC, IGP-M, IGP-DI, IPC-Fipe
IPCA_BREAKDOWN	11	Tradeable, non-tradeable, durables, services, cores
IPCA_CATEGORIES	9	Food, housing, transport, health, education
GDP	13	GDP current/constant/USD, per capita, quarterly components
EMPLOYMENT	7	Unemployment rate, labor force, income
INDUSTRIAL_PRODUCTION	7	Manufacturing, mining, capital/intermediate/consumer goods
FINANCIAL_MARKETS	7	Gold, Bovespa, IMA-B
SAVINGS	2	Savings rate and return
CONFIDENCE	4	Consumer (ICC) and business (ICEI) confidence
ECONOMIC_ACTIVITY	1	IBC-Br (GDP proxy, seasonally adjusted)
BASIC_BASKET	16	Cost of living by capital city
EXCHANGE_RATE_INDEX	5	Real effective exchange rate (USD, EUR, JPY, ARS)

Use any code directly by number or via the category dictionaries:

from bcbpy import INFLATION, GDP

# These are equivalent:
fetch_series(433)
fetch_series(INFLATION["IPCA"])

API Limits

• Date range: max 10 years per query (BCB restriction since March 2025)
• Rate limiting: HTTP 429 on excessive requests (no official limit documented)
• Date formats: the client accepts both YYYY-MM-DD and DD/MM/YYYY

Project Structure

bcbpy/
├── bcbpy/
│   ├── __init__.py      # Public API exports
│   ├── client.py        # API client functions and exceptions
│   ├── codes.py         # 115 curated series codes in 14 categories
│   └── constants.py     # Base URLs and API configuration
├── main.py              # CLI demo script
├── pyproject.toml       # PyPI packaging metadata
├── BCB_API_REFERENCE.md # Full SGS + Olinda API reference guide
└── README.md

Data Source

All data is fetched from the BCB Open Data Portal under the Open Database License (ODbL).

License

MIT (see LICENSE). The BCB data accessed through this client remains under ODbL; users must comply with ODbL when redistributing data.