btgsolutions-dataservices-python-client 3.2.8

Python package containing several classes and data for extracting and manipulating market and trading data.

BTG Solutions - Data Services

Real time and historical Financial Market Data, News, Corporate Events and more. More information at https://dataservices.btgpactualsolutions.com/.

Installation

pip3 install btgsolutions-dataservices-python-client

Documentation

The official documentation is hosted at https://python-client-docs.dataservices.btgpactualsolutions.com/

Examples

Real Time Data

Market Data Stream (optimized for performance)

import btgsolutions_dataservices as btg
ws = btg.MarketDataFeed(api_key='YOUR_API_KEY', data_type='books', data_subtype='stocks')
ws.run()
ws.subscribe(['PETR4'])

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Market Data Stream

Books

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='books', instruments=['PETR4', 'VALE3'])
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Books, Top Of Book (n=1)

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='books')
ws.run(on_message=lambda message: print(message))
ws.subscribe(['PETR4', 'VALE3'], n=1)

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Trades

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='trades', instruments=['PETR4', 'VALE3'])
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Trades, delayed (15 minutes delay)

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='trades', stream_type='delayed', instruments=['PETR4', 'VALE3'])
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Books, throttle (1 second throttle)

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='books', stream_type='throttle', instruments=['PETR4', 'VALE3'])
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Trades, NASDAQ (US)

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', exchange='nasdaq', data_type='trades')
ws.run(on_message=lambda message: print(message))
ws.subscribe(['AMZN', 'GOOG', 'TSLA'])

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Trades, BMV (MX)

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', exchange='bmv', data_type='trades')
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Security Status

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='instrument_status', data_subtype='stocks')
ws.run(on_message=lambda message: print(message))
ws.instrument_status('PETR4')
ws.instrument_status_history('PETR4')

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Settlement Price

import btgsolutions_dataservices as btg
ws = btg.MarketDataWebSocketClient(api_key='YOUR_API_KEY', data_type='settlement-price', instruments=['ABEVOU25', 'WINV25'])
ws.run(on_message=lambda message: print(message))

## Getting the last event (settlement-price) of ABEVOU25:
# ws.get_last_event(['ABEVOU25'])

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

Intraday Candles

import btgsolutions_dataservices as btg
int_candles = btg.IntradayCandles(api_key='YOUR_API_KEY')
int_candles.get_intraday_candles(market_type='stocks', tickers=['PETR4', 'VALE3'], candle_period='1m', delay='delayed', mode='relative', timezone='UTC', market_status='regular', raw_data=True)

Intraday Tick Data

import btgsolutions_dataservices as btg
intra_tickdata = btg.IntradayTickData(api_key='YOUR_API_KEY')
intra_tickdata.get_trades(ticker='PETR4')

Quotes

import btgsolutions_dataservices as btg
quotes = btg.Quotes(api_key='YOUR_API_KEY')
quotes.get_quote(market_type = 'stocks', tickers = ['PETR4', 'VALE3'])

Ticker Last Trade

import btgsolutions_dataservices as btg
last_event = btg.TickerLastEvent(api_key='YOUR_API_KEY')
last_event.get_trades(data_type='equities', ticker='VALE3')

Ticker Last Top of Book

import btgsolutions_dataservices as btg
last_event = btg.TickerLastEvent(api_key='YOUR_API_KEY')
last_event.get_tobs(data_type='equities')

Ticker Last Trading Status

import btgsolutions_dataservices as btg
last_event = btg.TickerLastEvent(api_key='YOUR_API_KEY')
last_event.get_status(tickers=['PETR4','VALE3'])

Ticker Last Polling - Top of Books

import btgsolutions_dataservices as btg
last_event = btg.TickerLastEventPolling(api_key='YOUR_API_KEY', data_type='top-of-books', data_subtype='stocks')
last_event.get()

Historical Data

Historical Candles

Interday

import btgsolutions_dataservices as btg
hist_candles = btg.HistoricalCandles(api_key='YOUR_API_KEY')
hist_candles.get_interday_history_candles(ticker='PETR4',  market_type='stocks', corporate_events_adj=True, start_date='2023-10-01', end_date='2023-10-13', rmv_after_market=True, timezone='UTC', raw_data=False, round=False)

Intraday

import btgsolutions_dataservices as btg
hist_candles = btg.HistoricalCandles(api_key='YOUR_API_KEY')
hist_candles.get_intraday_history_candles(ticker='PETR4',  market_type='stocks', corporate_events_adj=True, date='2023-10-06', candle='1m', rmv_after_market=True, timezone='UTC', raw_data=False, round=True)

Available Tickers

import btgsolutions_dataservices as btg
hist_candles = btg.HistoricalCandles(api_key='YOUR_API_KEY')
hist_candles.get_available_tickers(market_type='stocks', date='2025-05-29')

Plot Candles

import btgsolutions_dataservices as btg
hist_candles = btg.HistoricalCandles(api_key='YOUR_API_KEY')
hist_candles.get_intraday_history_candles(ticker='PETR4',  market_type='stocks', corporate_events_adj=True, date='2023-10-06', candle='1m', rmv_after_market=True, timezone='UTC', raw_data=False).plot(x='candle_time', y='close_price', kind='scatter')

Historical Candles Crypto

Interday

import btgsolutions_dataservices as btg
hist_candles_crypto = btg.HistoricalCandlesCrypto(api_key='YOUR_API_KEY')
hist_candles_crypto.get_interday_history_candles(ticker='BTC', currency='BRL', exchange='consolidated', start_date='2025-06-01', end_date='2025-07-01', timezone='UTC', raw_data=False)

Intraday

import btgsolutions_dataservices as btg
hist_candles_crypto = btg.HistoricalCandlesCrypto(api_key='YOUR_API_KEY')
hist_candles_crypto.get_intraday_history_candles(ticker='BTC', currency='BRL', exchange='consolidated', date='2025-06-01', candle='1h', timezone='America/Sao_Paulo', raw_data=False)

Available Tickers

import btgsolutions_dataservices as btg
hist_candles_crypto = btg.HistoricalCandlesCrypto(api_key='YOUR_API_KEY')
hist_candles_crypto.get_available_tickers(exchange='coinbase', date='2023-01-13')

Historical Tick Data (Bulk Data)

Available Tickers

import btgsolutions_dataservices as btg
bulk_data = btg.BulkData(api_key='YOUR_API_KEY')
bulk_data.get_available_tickers(date='2023-07-03', data_type='trades', prefix='PETR')

Get Data

import btgsolutions_dataservices as btg
bulk_data = btg.BulkData(api_key='YOUR_API_KEY')
bulk_data.get_data(ticker='DI1F18', date='2017-01-02', data_type='trades')
# bulk_data.get_data(ticker='PETR4', date='2024-01-22', data_type='books')
# bulk_data.get_data(ticker='VALE3', date='2024-04-01', data_type='trades-and-book-events')
# bulk_data.get_data(ticker='PETR4', date='2025-05-07', data_type='instrument-status')

Security List

import btgsolutions_dataservices as btg
bulk_data = btg.BulkData(api_key='YOUR_API_KEY')
bulk_data.get_security_list(date='2025-05-07')

Market Data Channels

import btgsolutions_dataservices as btg
bulk_data = btg.BulkData(api_key='YOUR_API_KEY')
bulk_data.get_market_data_channels(date='2026-01-30')

Compressed Data (PCAP files)

import btgsolutions_dataservices as btg
bulk_data = btg.BulkData(api_key='YOUR_API_KEY')
bulk_data.get_compressed_data(channel='98', date='2026-01-30', data_type='instruments')
# bulk_data.get_compressed_data(channel='98', date='2026-01-30', data_type='incremental', feed='feedA')
# bulk_data.get_compressed_data(channel='98', date='2026-01-30', data_type='snapshot')

Alternative Data

High Frequency News Stream

import btgsolutions_dataservices as btg
ws = btg.HFNWebSocketClient(api_key='YOUR_API_KEY', country='brazil')
ws.run(on_message=lambda message: print(message))

## The following is optional to keep the program running in a .py file:
# from time import sleep
# while True:
#   sleep(1)

High Frequency News

import btgsolutions_dataservices as btg
hfn = btg.HighFrequencyNews(api_key='YOUR_API_KEY')
hfn.latest_news()

OPA

import btgsolutions_dataservices as btg
public_sources = btg.PublicSources(api_key='YOUR_API_KEY')
public_sources.get_opas(start_date='2022-10-01', end_date='2024-10-01')

STOCK LOAN

import btgsolutions_dataservices as btg
stock_loan = btg.StockLoan(api_key='YOUR_API_KEY')
stock_loan.get_trades()
stock_loan.get_paginated_trades(page=1, limit=1000, ticker ='PETR4')
stock_loan.get_available_tickers()

Company Fundamentals

Company General Information

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.general_info(ticker='PETR4')

Income Statement

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.income_statement(ticker='PETR4')

Balance Sheet

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.balance_sheet(ticker='PETR4')

Cash Flow

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.cash_flow(ticker='PETR4')

Valuation

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.valuation(ticker='PETR4')

Ratios

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.ratios(ticker='PETR4')

Growth

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.growth(ticker='PETR4')

Interims

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.interims(ticker='PETR4')

All Financial Tables

import btgsolutions_dataservices as btg
company_data = btg.CompanyData(api_key='YOUR_API_KEY')
company_data.all_financial_tables(ticker='PETR4')

Reference Data

Corporate Events

import btgsolutions_dataservices as btg
corporate_events = btg.CorporateEvents(api_key='YOUR_API_KEY')
corporate_events.get(start_date='2024-05-01', end_date='2024-05-31')
# corporate_events.get(start_date='2024-05-01', end_date='2024-05-31', tickers=['VALE3'])

Broker Reference

import btgsolutions_dataservices as btg
broker_reference = btg.BrokerReference(api_key='YOUR_API_KEY')
broker_reference.get()

Ticker Reference Data

import btgsolutions_dataservices as btg
ref = btg.ReferenceData(api_key='YOUR_API_KEY')
ref.ticker_reference(tickers=['VALE3','PETR4'])