PriceHub: Unified Python Package for Collecting OHLC Prices from Binance, Bybit, Coinbase, OKX, Kraken, KuCoin, and Bitget APIs into a DataFrame
It supports multiple markets, including spot and futures, and provides flexible timestamp inputs and a wide range of intervals.
Effective trading begins with thorough data analysis, visualization, and backtesting. This package simplifies access to such data, providing a unified solution for retrieving OHLC information across various broker APIs.
📚 Full documentation: https://eslazarev.github.io/pricehub/
pip install pricehubfrom pricehub import get_ohlc
# One call, any exchange → a ready-to-use pandas DataFrame
df = get_ohlc("binance_spot", "BTCUSDT", "1d", "2024-10-01", "2024-10-05")
print(df)Same call signature for every supported exchange and market — just change the broker:
get_ohlc("bybit_linear", "ETHUSDT", "1h", "2024-10-01", "2024-10-02")
get_ohlc("okx_futures", "BTC-USDT", "4h", "2024-10-01", "2024-10-02")
get_ohlc("kraken_spot", "XBTUSDT", "1d", "2024-10-01", "2024-10-05")No API keys required for public market data. Large date ranges are paginated automatically.
Need OHLC candles from several crypto exchanges in Python? You could wire up each exchange SDK yourself, or wrangle a heavier general-purpose library. PriceHub does one thing well: a single function that returns a clean pandas.DataFrame from any supported exchange.
| PriceHub | ccxt |
single-exchange SDKs ( python-binance, …) |
|
|---|---|---|---|
| Unified interface across 7 exchanges | ✅ | ✅ | ❌ (one exchange each) |
Returns a pandas.DataFrame directly |
✅ | ❌ (list of lists) | ❌ (raw JSON) |
| Pagination over large date ranges | ✅ (default) | ⚙️ (opt-in paginate) |
❌ (manual) |
| All raw fields from the official API | ✅ | ❌ (OHLCV only) | ✅ |
| No API keys for public data | ✅ | ✅ | ✅ |
| Lightweight dependencies | ✅ (4) | ❌ (more) | varies |
| Focused scope (OHLC only) | ✅ | ❌ (full trading) | ❌ (full trading) |
Use PriceHub when you need historical/recent OHLC data for backtesting, research, ML datasets, or dashboards — without per-exchange boilerplate.
Reach for ccxt when you need full trading functionality (placing orders, balances, websockets) across dozens of venues.
- Quickstart
- Why PriceHub?
- Supported Brokers
- Key Features
- Supported Intervals
- Installation
- Function Reference
- Example Usage
- Save data to CSV, Excel, Parquet files
- Retrieve OHLC data from Binance Spot for a 6-hour interval
- Retrieve OHLC data from Bybit Spot for a 1-day interval
- Retrieve OHLC data from KuCoin Spot for a 1-hour interval
- Retrieve OHLC data from KuCoin Futures for a 1-hour interval
- Plot Close 1d data with matplotlib: BTCUSDT Futures on Binance for the last year
- Plot OHLC 1w data with plotly: BTCUSDT Spot on Binance for the last five years
- Create custom intervals 10m for SOLUSDT Spot on Bybit for the last month
- Binance Spot
- Binance Futures
- Bybit Spot
- Bybit Linear (Futures)
- Bybit Inverse
- Coinbase Spot
- OKX Spot
- OKX Futures
- Kraken Spot
- Kraken Futures
- KuCoin Spot
- KuCoin Futures
- Bitget Spot
- Bitget Futures
- Unified Interface: Supports multiple brokers and markets (spot, futures) with a single interface.
- Unified Intervals: Use the same interval format across all brokers.
- Timestamp Flexibility: Accepts timestamps (start, end) in various formats (int, float, string, Arrow, pandas, datetime).
- No Credential Requirement: Fetch public market data without authentication.
- Extended Date Ranges: This package will paginate and collect all data across large date ranges.
- All fields from official API: Retrieve all fields available in the official API (e.g.,
Number of trades,Taker buy base asset volume).
(depends on the broker)
- Seconds:
1s - Minutes:
1m,3m,5m,15m,30m - Hours:
1h,2h,4h,6h,12h - Days:
1d,3d - Weeks:
1w - Months:
1M
pip install pricehubdef get_ohlc(broker: SupportedBroker, symbol: str, interval: Interval, start: Timestamp, end: Timestamp) -> pd.DataFrame
Retrieves OHLC data for the specified broker, symbol, interval, and date range.
-
Parameters:
broker: The broker to fetch data from (e.g.,binance_spot,bybit_spot,okx_futures,kraken_spot).symbol: The trading pair symbol (e.g.,BTCUSDT).interval: The interval for OHLC data (1m,1h,1d, etc.).start: Start time of the data (supports various formats).end: End time of the data (supports various formats).
-
Returns:
pandas.DataFrame: A DataFrame containing OHLC data.
from pricehub import get_ohlc
df = get_ohlc("binance_spot", "BTCUSDT", "1d", "2024-10-01", "2024-10-05")
df.to_csv("btcusdt_1d_2024-10-01_2024-10-05.csv") # Save to CSV
df.to_excel("btcusdt_1d_2024-10-01_2024-10-05.xlsx") # Save to Excel
df.to_parquet("btcusdt_1d_2024-10-01_2024-10-05.parquet") # Save to Parquet, requires 'pyarrow', 'fastparquet'from pricehub import get_ohlc
df = get_ohlc(
broker="binance_spot",
symbol="BTCUSDT",
interval="6h",
start="2024-10-01",
end="2024-10-02"
)
print(df) Open High Low Close Volume Close time Quote asset volume Number of trades Taker buy base asset volume Taker buy quote asset volume Ignore
Open time
2024-10-01 00:00:00 63309.0 63872.0 63000.0 63733.9 39397.714 2024-10-01 05:59:59.999 2.500830e+09 598784.0 19410.785 1.232417e+09 0.0
2024-10-01 06:00:00 63733.9 64092.6 63683.1 63699.9 32857.923 2024-10-01 11:59:59.999 2.100000e+09 446330.0 15865.753 1.014048e+09 0.0
2024-10-01 12:00:00 63700.0 63784.0 61100.0 62134.1 242613.990 2024-10-01 17:59:59.999 1.512287e+10 2583155.0 112641.347 7.022384e+09 0.0
2024-10-01 18:00:00 62134.1 62422.3 60128.2 60776.8 114948.208 2024-10-01 23:59:59.999 7.031801e+09 1461890.0 54123.788 3.312086e+09 0.0
2024-10-02 00:00:00 60776.7 61858.2 60703.3 61466.7 51046.012 2024-10-02 05:59:59.999 3.133969e+09 668558.0 27191.919 1.669187e+09 0.0from pricehub import get_ohlc
df = get_ohlc(
broker="bybit_spot",
symbol="ETHUSDT",
interval="1d",
start=1727740800.0, # Unix timestamp in seconds for "2024-10-01"
end=1728086400000, # Unix timestamp in ms for "2024-10-05"
)
print(df) Open High Low Close Volume Turnover
Open time
2024-10-01 2602.00 2659.31 2413.15 2447.95 376729.77293 9.623060e+08
2024-10-02 2447.95 2499.82 2351.53 2364.01 242498.88477 5.914189e+08
2024-10-03 2364.01 2403.50 2309.75 2349.91 242598.38255 5.716546e+08
2024-10-04 2349.91 2441.82 2339.15 2414.67 178050.43782 4.254225e+08
2024-10-05 2414.67 2428.69 2389.83 2414.54 106665.69595 2.573030e+08from pricehub import get_ohlc
df = get_ohlc(
broker="kucoin_spot",
symbol="BTC-USDT",
interval="1h",
start="2024-10-01",
end="2024-10-02"
)
print(df)from pricehub import get_ohlc
df = get_ohlc(
broker="kucoin_futures",
symbol="XBTUSDTM",
interval="1h",
start="2024-10-01",
end="2024-10-02"
)
print(df)from datetime import datetime, timedelta
import matplotlib.pyplot as plt
from pricehub import get_ohlc
now = datetime.now()
df = get_ohlc("binance_futures", "BTCUSDT", "1d", now - timedelta(days=365), now)
df["Close"].plot()
plt.show()
from datetime import datetime, timedelta
import plotly.graph_objects as go
from pricehub import get_ohlc
now = datetime.now()
df = get_ohlc("binance_spot", "BTCUSDT", "1w", now - timedelta(days=365 * 5), now)
fig = go.Figure(data=go.Candlestick(x=df.index, open=df['Open'], high=df['High'], low=df['Low'], close=df['Close']))
fig.update_layout()
fig.show()
from datetime import datetime, timedelta
from pricehub import get_ohlc
now = datetime.now()
df = get_ohlc("bybit_spot", "SOLUSDT", "5m", now - timedelta(days=31), now)
df_10m = (
df.resample(
"10min",
).agg(
{
"Open": "first",
"High": "max",
"Low": "min",
"Close": "last",
"Volume": "sum",
}
)
)
print(df.head())
print(df_10m.head())#5m
Open High Low Close Volume Turnover
Open time
2024-11-07 17:40:00 194.13 194.66 194.03 194.54 3391.378 6.592576e+05
2024-11-07 17:45:00 194.54 195.48 194.44 195.41 6075.927 1.184312e+06
2024-11-07 17:50:00 195.41 195.71 195.06 195.69 4073.276 7.961276e+05
2024-11-07 17:55:00 195.69 196.16 195.59 195.93 8774.224 1.719060e+06
2024-11-07 18:00:00 195.93 196.83 195.73 196.34 5075.807 9.973238e+05
#10m
Open High Low Close Volume
Open time
2024-11-07 17:40:00 194.13 195.48 194.03 195.41 9467.305
2024-11-07 17:50:00 195.41 196.16 195.06 195.93 12847.500
2024-11-07 18:00:00 195.93 196.83 194.66 195.29 12506.671
2024-11-07 18:10:00 195.29 196.13 194.70 195.58 20437.030
2024-11-07 18:20:00 195.58 196.00 194.84 195.81 16388.688PriceHub is actively maintained. Issues and pull requests are typically reviewed within one week.
-
Daily live checks: A scheduled GitHub Actions workflow (
providers-health.yml) hits every supported exchange API once per day with a small sample request and verifies real data is returned. Current status is reflected in the Providers Health badge above. -
Versioning: Semantic Versioning 2.0. Breaking changes will only land in major releases.
-
Python support: All non-end-of-life Python versions (currently 3.8 through 3.13). End-of-life Python versions are dropped in the next minor release after they reach EOL.
-
Dependency policy: Direct dependencies are kept minimal (
pandas,pydantic,arrow,requests). New dependencies are added only when they enable a feature that cannot be reasonably implemented in-tree. -
API stability: The public surface (
get_ohlc, broker identifiers, supported intervals) follows SemVer. Returned DataFrame column names mirror upstream exchange APIs and may change if an exchange renames fields — such changes are documented in release notes. -
Reporting issues: See GitHub Issues. For security-sensitive reports, email
elazarev@gmail.comdirectly.
If you use PriceHub in academic work, please cite it. See CITATION.cff or the Citation page. The Concept DOI 10.5281/zenodo.20304963 always points to the latest release; version-specific DOIs are listed on the Zenodo record.
Released under the MIT License.