TickerLab Python SDK
Python client library for the TickerLab financial market data API.
Installation
pip install tickerlab
To enable automatic Pandas DataFrame conversion for time-series and tabular data:
pip install "tickerlab[pandas]"
Quick Start
import tickerlab as tl
# Set API authentication token
tl.set_token("YOUR_API_KEY")
# Fetch daily historical K-line data
df = tl.get_kline("000001.SZ", period="1d", start="2026-01-01", adjust="qfq")
print(df.tail())
# Fetch real-time market quote snapshot
snapshot = tl.get_snapshot("600519.SH")
print(snapshot)
# Fetch technical indicators (MACD, RSI, KDJ, BOLL, MA, EMA)
macd = tl.get_indicators("000001.SZ", indicator="macd")
print(macd.tail())
Authentication
Authentication can be configured programmatically or via environment variable:
export TICKERLAB_API_KEY="YOUR_API_KEY"
import tickerlab as tl
# When TICKERLAB_API_KEY is present in environment, manual set_token is optional
df = tl.get_kline("000001.SZ")
Method Reference
| Method | Description | Return Type |
|---|---|---|
get_kline(symbol, period='1d', start=None, end=None, adjust='qfq') |
Historical OHLCV market bars | DataFrame / dict |
get_snapshot(symbol) |
Real-time market quote snapshot | dict / DataFrame |
get_daily_basic(symbol, start=None, end=None) |
Valuation metrics (PE, PB, turnover, market cap) | DataFrame |
get_indicators(symbol, indicator='macd', period='1d') |
Calculated technical indicators | DataFrame |
get_trade_calendar(start=None, end=None) |
Market trading days and settlement schedule | DataFrame |
get_stock_list() |
Master instrument list and metadata | DataFrame |
search_stocks(query) |
Symbol and name search | DataFrame |
get_macro(indicator='cpi') |
Macroeconomic indicator series | DataFrame |
get_financial_ratios(symbol) |
Financial statement ratios | DataFrame |
query(endpoint, params={}) |
Low-level generic API request | dict / list |
License
MIT License. See LICENSE for details.
1 maintainer
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