flowex
Real-time multi-exchange crypto market data for Python — powered by Go via cgo shared library. WebSocket streaming, order book metrics, technical indicators, and per-symbol actor workers for Binance, Bybit, and Bitget.
No subprocess, no gRPC, no serialization overhead on the hot path. The Go runtime lives inside the Python process. Every symbol gets its own goroutine. get_snapshot() hits the atomic store directly.
Install
pip install flowex
Quick start
import time
from flowex import Manager
mgr = Manager("binance")
mgr.subscribe(["BTCUSDT", "ETHUSDT", "SOLUSDT"])
time.sleep(2)
snap = mgr.get_snapshot("BTCUSDT")
print(snap.depth.spread_bps)
print(snap.depth.mid_price)
print(snap.candles[-1].close)
# Technical indicators (RSI, MACD, Bollinger Bands, etc.)
if snap.indicators:
print(snap.indicators.rsi_14)
print(snap.indicators.macd_line)
print(snap.indicators.bb_upper)
mgr.close()
Or use as a context manager:
with Manager("binance") as mgr:
mgr.subscribe(["BTCUSDT"])
time.sleep(2)
snap = mgr.get_snapshot("BTCUSDT")
Supported exchanges
- Binance — futures WebSocket (candles, depth, aggTrade)
- Bybit — linear futures WebSocket
- Bitget — USDT futures WebSocket
API
Manager(exchange)
Create a manager for an exchange. Initializes the Go runtime and WebSocket connections.
mgr = Manager("binance") # or "bybit", "bitget"
mgr.subscribe(symbols)
Subscribe to all streams (candle, depth, trade) for one or more symbols.
mgr.subscribe("BTCUSDT")
mgr.subscribe(["BTCUSDT", "ETHUSDT", "SOLUSDT"])
mgr.subscribe_candle(symbol) / subscribe_depth(symbol) / subscribe_trade(symbol)
Subscribe to individual stream types for granular control.
mgr.subscribe_candle("BTCUSDT") # candles only
mgr.subscribe_depth("ETHUSDT") # depth only
mgr.subscribe_trade("SOLUSDT") # trades only
mgr.get_snapshot(symbol) -> Snapshot | None
Get the latest point-in-time snapshot for a symbol.
snap = mgr.get_snapshot("BTCUSDT")
snap.timestamp # Unix ms
snap.depth # DepthMetrics
snap.candles # list[CandleHLCV]
snap.trades # list[NormalizedTrade]
snap.indicators # TechnicalIndicators | None
mgr.get_all_snapshots() -> dict[str, Snapshot]
Get snapshots for all subscribed symbols in one call.
mgr.get_status() -> dict
Get manager status info (subscribed symbols, connection state).
mgr.get_depth_history(symbol, count=0) -> list[DepthMetrics]
Get recent depth metrics from the ring buffer. count=0 returns the full buffer (default 100 entries).
history = mgr.get_depth_history("BTCUSDT", count=10)
for m in history:
print(m.mid_price, m.spread_bps)
mgr.get_depth_by_time_range(symbol, start_ms, end_ms) -> list[DepthMetrics]
Get depth metrics within a Unix-millisecond time window.
import time
now = int(time.time() * 1000)
metrics = mgr.get_depth_by_time_range("BTCUSDT", now - 30_000, now)
mgr.unsubscribe(symbol)
Remove all streams for a symbol.
mgr.unsubscribe_stream(symbol, stream)
Remove a specific stream type: "candle", "depth", or "trade".
mgr.unsubscribe_stream("BTCUSDT", "depth")
mgr.close()
Shutdown all managers and WebSocket connections.
Data models
TechnicalIndicators
Computed from candle history (needs ~20+ bars):
| Field | Description |
|---|---|
rsi_14 |
RSI (14-period) |
sma_20 / sma_50 / sma_200 |
Simple Moving Averages |
ema_9 / ema_12 / ema_20 / ema_21 / ema_26 / ema_50 / ema_200 |
Exponential Moving Averages |
macd_line / signal_line / histogram |
MACD |
bb_upper / bb_middle / bb_lower |
Bollinger Bands (20, 2σ) |
atr |
Average True Range (14-period) |
stoch_rsi |
Stochastic RSI |
mmi |
Market Manipulation Index (0–100) |
ma_summary / oscillator_sum / overall_sum |
Signal summary (-2 to 2) |
DepthMetrics
Order book metrics computed from raw depth data:
| Field | Description |
|---|---|
mid_price |
(best_bid + best_ask) / 2 |
spread_bps |
Spread in basis points |
bid_liquidity_10 |
USD liquidity, top 10 bid levels |
ask_liquidity_10 |
USD liquidity, top 10 ask levels |
imbalance_ratio_10 |
bid_liq / ask_liq (>1 = bullish) |
slippage_buy_10k |
Estimated slippage % for $10k buy |
Plus 70+ more fields: liquidity at 5/10/20/50 levels, volumes, imbalance deltas, largest walls, slippage at 8 USD sizes, velocity, momentum, z-scores, and depth quality metrics.
CandleHLCV
candle.ts # Unix ms
candle.open
candle.high
candle.low
candle.close
candle.volume
NormalizedTrade
trade.timestamp # Unix ms
trade.price
trade.size
trade.side # "buy" or "sell"
trade.symbol
Architecture
Python process
|
+-- ctypes loads libflowex.so <-- Go runtime starts inside Python
| |
| +-- Manager (binance)
| | +-- Worker: BTCUSDT -> atomic snapshot
| | +-- Worker: ETHUSDT -> atomic snapshot
| | +-- Worker: SOLUSDT -> atomic snapshot
| |
| +-- Manager (bybit)
| +-- Worker: BTCUSDT -> atomic snapshot
|
+-- mgr.subscribe(["BTCUSDT"]) -> FlowexSubscribeBatch()
+-- mgr.get_snapshot("BTCUSDT") -> FlowexGetSnapshot() -> atomic.Load -> JSON -> Python
+-- mgr.get_all_snapshots() -> FlowexGetSnapshots() -> one call, all symbols
Build from source
Requires Go 1.22+ and Python 3.10+.
# macOS (Apple Silicon)
make build-mac
# Linux (amd64)
make build-linux
# All platforms (requires cross-compilers)
make build-all
License
MIT
Metadata
Release files for flowex 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| flowex-0.3.1.tar.gz | 15.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| flowex-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.2 MB
Release files / flowex-0.3.1.tar.gz
| Download URL | flowex-0.3.1.tar.gz |
|---|---|
| Size | 15.6 MB |
| Tags | Source |
|
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| Download URL | flowex-0.3.1-py3-none-any.whl |
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| Size | 15.6 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
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