Rule-based cryptocurrency market analysis, signal generation, and Discord integration powered by public Bybit V5 market data.
Current release: v4.1.5. This release hardens candle validation and transient API handling, validates backtest interval continuity and persisted dataset provenance, optimizes the SMA baseline, clarifies metric semantics, and strengthens CI and protected-main governance. It builds on the PyPI distribution introduced in v4.1.1 and reproducible historical backtesting introduced in v4.1.0; the latest legacy release was v3.1.
Bybit-Predict analyzes OHLCV candles from Bybit and produces informational
market signals and reference levels. The current legacy-rule-based-v4
strategy uses candle shapes, volume power, percentiles, IQR, and
Fibonacci-inspired levels.
It does not use a machine-learning model and it is not a trading bot. It never places orders, asks for Bybit API credentials, or promises a market outcome.
Risk notice: Cryptocurrency markets are volatile. Results are informational only, are not financial advice, and must not be treated as a recommendation or guarantee to trade.
- One Bybit V5 K-line request retrieves up to 1,000 candles; the default analysis uses 180 instead of sending 180 individual requests.
- Typed, UTC-normalized
Candleand immutablePredictionResultmodels. - Stateless legacy strategy: concurrent analyses cannot mix their data.
- CLI for local use and an optional non-blocking Discord slash command.
- Active symbols validated using Bybit instrument metadata, not a hard-coded coin list.
- Tests, Ruff, Pyright, GitHub Actions CI, and Dependabot.
- Deterministic historical backtesting with saved CSV inputs, validated dataset manifests, explicit assumptions, performance metrics, and two simple baselines.
- Python 3.11 or later
- Internet access to Bybit public market endpoints
No Bybit account, API key, or API secret is needed for public market analysis. The optional Discord interface needs only a Discord bot token.
Install the CLI and its standard Bybit V5 dependency with:
python -m pip install bybit-predictInstall the optional Discord interface when you need it:
python -m pip install "bybit-predict[discord]"For an isolated command-line installation, use pipx:
pipx install bybit-predictgit clone https://github.com/KageRyo/Bybit-Predict.git
cd Bybit-Predict
uv venv --python 3.11 .venv
source .venv/bin/activate # Windows: .venv\\Scripts\\activate
uv pip install .For contributors, install development and optional Discord dependencies:
uv pip install -e ".[dev]"Analyze the default 180 four-hour candles:
bybit-predict analyze BTCUSDTChoose another supported Bybit interval and candle count:
bybit-predict analyze ETHUSDT --interval 60 --limit 240Example output:
Symbol: BTCUSDT
Strategy: legacy-rule-based-v4 (rule-based, not ML)
Timeframe: 240
Candles: 180
Trend: Bullish
Signal strength: 68.00%
Reference levels:
0% ...
23.6% ...
The CLI returns a non-zero status for invalid symbols, invalid parameters, or
market-data failures. You can also run python -m bybit_predict analyze BTCUSDT.
v4.1.0 adds a reproducible backtest command. It signals from a trailing
closed-candle window, executes non-neutral signals at the next candle open,
and exits at that candle close. The command prints its assumptions with metrics
and baselines; it does not make a trading claim.
bybit-predict backtest BTCUSDT \
--interval 240 \
--start 2024-01-01 \
--end 2025-01-01 \
--strategy legacy \
--window 180 \
--save-data data/btcusdt-2024-4h.csvRe-run against the saved, normalized CSV without downloading data again:
bybit-predict backtest BTCUSDT \
--interval 240 \
--start 2024-01-01 \
--end 2025-01-01 \
--strategy legacy \
--window 180 \
--data data/btcusdt-2024-4h.csv--start is inclusive, --end is exclusive, and date-only values mean
midnight UTC. See backtesting and evaluation for metric
definitions, baseline semantics, manifest validation, reproducibility
requirements, and important limitations. Saving a CSV also creates the
required <csv-name>.manifest.json sidecar; --data rejects missing,
malformed, mismatched, or tampered CSV/manifest pairs before replay.
The sidecar contains exactly schema_version, symbol, category, interval,
source, requested_start, requested_end, generated_at, and
content_sha256 (schema 1, source Bybit V5).
The report labels the public directional_accuracy field as close-to-close
directional accuracy: it compares the signal candle close with the next
candle close, not the next candle's open-to-close return. An adverse gap can
therefore make this metric correct while the simulated trade loses money; use
win rate and return metrics for execution outcomes.
CLI dataset paths must resolve under the current working directory: the
documented data/<file> form works, while .. traversal, paths outside that
root, and symlink components are rejected before a backtest runs.
The CLI also requires regular CSV and manifest files: existing hard-linked
outputs and special files such as FIFOs are rejected without blocking.
Install the Discord optional dependency, create a Discord application/bot, and
invite it with the bot and applications.commands scopes.
python -m pip install ".[discord]"
cp .env.example .envSet environment variables securely (for example by sourcing .env locally or
using your deployment secret manager):
export DISCORD_BOT_TOKEN="your-token"
# Optional: immediately sync commands to one development guild.
export DISCORD_GUILD_ID="your-development-guild-id"Then start the interface:
bybit-predict discordUse the slash command in Discord:
/predict symbol:BTCUSDT interval:240 candles:180
The command defers external market work to a thread, so a slow Bybit request does not block Discord's event loop. Responses include the strategy, trend, signal strength, candle period, and neutral reference levels rather than trading instructions.
Never commit .env, bot tokens, API keys, or downloaded data. They are
ignored by default.
| Variable | Required | Purpose |
|---|---|---|
DISCORD_BOT_TOKEN |
Discord only | Discord bot authentication token. |
DISCORD_GUILD_ID |
No | Development guild for immediate command syncing. |
BYBIT_TESTNET |
No | true opts into Bybit testnet public data; default is false. |
The market-data client intentionally exposes no Bybit credential settings: public K-line and instrument endpoints do not require authentication.
Bybit V5 public API
│
BybitV5MarketClient ──→ normalized UTC Candles
│
├── PredictionService ──→ LegacyRuleBasedStrategy ──→ PredictionResult
│ │ │
│ ├──────── CLI └── future strategies
│ └──────── Discord slash command
│
└── BacktestEngine ─────→ LegacyRuleBasedStrategy ──→ BacktestResult
│
├──────── historical CLI
└──────── saved CSV input/output
market/owns Bybit V5 requests, retry boundaries, pagination, and response normalization.strategies/contains pure, deterministic signal calculations and has no dependency on Bybit or Discord.services/composes market data with a strategy.interfaces/converts user input/output only.
LegacyRuleBasedStrategy is deliberately retained as the project’s historical
core. It classifies candle bodies and wicks, compares significant bullish and
bearish volume, and derives optional reference prices from IQR and percentile
calculations. It is explicitly named so later strategies can be compared
fairly. v4 intentionally fixes v3's zero/six-candle volume window, timezone
handling, and bearish Fibonacci label ordering; the exact compatibility
baseline and retained semantics are documented in
legacy strategy migration notes.
The v4.1.0 backtesting work (#25) defines a fixed trailing analysis window, next-open entry, same-candle-close exit, and neutral-as-cash behavior before calculating close-to-close directional accuracy, win rate, average return, maximum drawdown, and a zero-risk-rate Sharpe ratio. It compares the result with buy-and-hold and a 10/20 SMA directional baseline. See backtesting and evaluation for the exact rules and limitations. Until published results are independently interpreted in context, this project makes no claim that its signals predict future prices.
ruff check .
ruff format --check .
pyright
pytestpytest fails when total coverage falls below the 80% floor (the current
baseline is approximately 84%). Pyright remains in basic mode but now treats
missing imports as errors; the development extra installs the dependencies
needed by the checks.
Pull requests run these checks on Python 3.11, 3.12, and 3.13. See
CONTRIBUTING.md for local setup and the required
feature/<issue>-<description> branch convention.
Pushing a final release tag builds an sdist and universal wheel, validates them, publishes through PyPI Trusted Publishing, then creates a GitHub Release with the same artifacts. See PyPI publishing for the maintainer-only setup and release procedure. No long-lived PyPI API token is stored in this repository or its GitHub Actions secrets.
- v4.0.0: package architecture, public Bybit V5 client, stateless legacy strategy, CLI, Discord slash command, configuration, quality gates, and documentation.
- v4.1.0: reproducible backtesting and evaluation (#25).
- v4.1.1: PyPI distribution, Trusted Publishing, and package-release automation (#37).
- v4.1.2: documentation and PyPI metadata corrections (#40).
- v4.1.3: CI dependency maintenance and restoration of the complete GPL v2 license text.
- v4.1.4: standard GPL v2 distribution license, recognised by GitHub as GPL-2.0.
- v4.1.5: candle and API robustness, interval and dataset replay validation, linear SMA baseline computation, explicit metric semantics, enforced quality gates, and protected-main governance.
- Later: additional strategies may implement the same strategy contract; ML is a future option, not an implied feature.
The repository name, issues, forks, stars, merged pull requests, and Git history are intentionally preserved. Thanks to prior contributors, including RRAaru. New contributors are welcome—start with good first issues or read CONTRIBUTING.md.
Bybit-Predict is licensed under the GNU General Public License v2.0 or later.
Copyright © 2022–2026 CodeRyo Studio, Chien-Hsun Chang, and contributors. CodeRyo Studio is the project maintainer. See NOTICE for the complete attribution notice.