forked from artemium/428-backtester
Add private Freqtrade scaffold for partner backtesting.
Ship SampleStrategy and Integral workflow scripts without proprietary V15 logic, Pine, or run results. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Artemii Peretiachenko
commit
99de26e7f0
13 changed files with 831 additions and 0 deletions
41
.gitignore
vendored
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41
.gitignore
vendored
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# Freqtrade runtime / data
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user_data/data/
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user_data/logs/
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user_data/plot/
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user_data/backtest_results/
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user_data/hyperopt_results/
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user_data/hyperopts/
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user_data/strategies/*.json
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user_data/notebooks/
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user_data/*.sqlite
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user_data/*.sqlite-journal
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user_data/tradesv3.dryrun.sqlite*
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user_data/freqtradeservice.json
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user_data/hyperopt.lock
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# Proprietary strategy + Pine (local only — do not push)
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user_data/strategies/V15_5_LTF*
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v15_5_LTF.txt
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*.bak
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*.bak_*
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# Local backtest / hyperopt run dumps
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results/
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# Secrets / local overrides
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user_data/config_private.json
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.env
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*.pem
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# Python
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__pycache__/
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*.py[cod]
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*.egg-info/
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.venv/
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venv/
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# OS / IDE
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.DS_Store
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.idea/
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.vscode/
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*.swp
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106
README.md
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106
README.md
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# 428 Backtester — Integral (Freqtrade)
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Local Freqtrade scaffold for backtesting on **Binance Futures BTC/USDT:USDT**, **15m** (+ **6h** informative data), built around the Integral workflow.
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No Jupyter. Reports come from Freqtrade CLI + HTML plots (`plot-profit`, trade chart).
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Ship a **SampleStrategy** by default. Drop your own strategy under `user_data/strategies/` and point scripts at it with `STRATEGY=YourClassName`.
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## Requirements
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- **Preferred:** Docker + Docker Compose (`freqtradeorg/freqtrade:stable_plot`)
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- **Fallback:** Python 3.12 venv with `freqtrade` + `plotly` (scripts use this automatically if Docker is missing)
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- ~2+ GB disk for OHLCV history
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### Local venv setup (no Docker)
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```bash
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/opt/homebrew/opt/python@3.12/bin/python3.12 -m venv .venv
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source .venv/bin/activate
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pip install -U pip 'freqtrade[hyperopt]' plotly
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```
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## Quick start
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```bash
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# 1) Download futures candles (15m + 6h). Default timerange from 2024-07-01.
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./scripts/download_data.sh
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# 2) Run baseline backtest (SampleStrategy; full history from 2024-07-01)
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./scripts/backtest.sh
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# 3) Hyperopt buy/sell params on in-sample range (default 20240701-20260101)
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./scripts/hyperopt.sh
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# EPOCHS=200 LOSS=SharpeHyperOptLossDaily ./scripts/hyperopt.sh
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# 4) Apply best epoch params, then OOS backtest (default 20260101-)
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./scripts/apply_hyperopt_params.sh
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TIMERANGE=20260101- ./scripts/backtest.sh
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# 5) Equity + trade charts (pick a shorter range for readable plots)
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TIMERANGE=20250101-20250201 ./scripts/plot.sh
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```
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Scripts auto-detect Docker; if absent they use `.venv/bin/freqtrade`.
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### Your strategy
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```bash
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# Place YourStrategy.py in user_data/strategies/
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STRATEGY=YourStrategy ./scripts/backtest.sh
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STRATEGY=YourStrategy ./scripts/hyperopt.sh
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```
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Or set `"strategy": "YourStrategy"` in `user_data/config.json` / `docker-compose.yml`.
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### Custom timerange
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```bash
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TIMERANGE=20240101-20250601 ./scripts/download_data.sh
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TIMERANGE=20240101-20250601 ./scripts/backtest.sh
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```
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### Direct docker compose
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```bash
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docker compose run --rm freqtrade download-data \
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--config /freqtrade/user_data/config.json \
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--trading-mode futures -t 15m 6h -p BTC/USDT:USDT --timerange 20240701-
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docker compose run --rm freqtrade backtesting \
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--config /freqtrade/user_data/config.json \
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--strategy SampleStrategy --timeframe 15m --timerange 20240701-
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```
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## Project layout
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| Path | Role |
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|------|------|
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| [`user_data/strategies/SampleStrategy.py`](user_data/strategies/SampleStrategy.py) | Placeholder strategy (replace with yours) |
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| [`user_data/config.json`](user_data/config.json) | Binance futures dry-run / backtest config |
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| [`scripts/`](scripts/) | download / backtest / hyperopt / plot helpers |
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| [`docker-compose.yml`](docker-compose.yml) | `freqtradeorg/freqtrade:stable_plot` |
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## Optimization
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Primary tool: **Freqtrade Hyperopt** (Optuna TPE) over strategy `IntParameter` / `DecimalParameter` spaces.
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Default split used by scripts:
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- **IS / hyperopt:** `TIMERANGE=20240701-20260101`
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- **OOS backtest:** `TIMERANGE=20260101-`
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```bash
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./scripts/hyperopt.sh # IS search
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./scripts/apply_hyperopt_params.sh # write user_data/strategies/<Strategy>.json
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TIMERANGE=20260101- ./scripts/backtest.sh # OOS with best params
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# Defaults again: remove the JSON override
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rm -f user_data/strategies/SampleStrategy.json
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```
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If optimizable params change `populate_indicators` (not only entry/exit columns), keep `--analyze-per-epoch` (default in `hyperopt.sh`). Without it every epoch can repeat the baseline result.
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## Notes
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- **Fees / funding:** `config.json` sets `fee: 0.0005` (5 bps). Funding rates download with futures data when available; treat equity as approximate.
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- **Private logic:** proprietary strategies and run artifacts stay local (see `.gitignore`). Do not commit them to this repo.
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18
docker-compose.yml
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18
docker-compose.yml
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---
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services:
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freqtrade:
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# _plot image includes plotly for plot-profit / plot-dataframe
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image: freqtradeorg/freqtrade:stable_plot
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restart: "no"
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container_name: freqtrade-backtester
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volumes:
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- "./user_data:/freqtrade/user_data"
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ports:
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- "127.0.0.1:8080:8080"
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# Default: no long-running trade process; use scripts/*.sh via docker compose run
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command: >
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trade
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--logfile /freqtrade/user_data/logs/freqtrade.log
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--db-url sqlite:////freqtrade/user_data/tradesv3.sqlite
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--config /freqtrade/user_data/config.json
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--strategy SampleStrategy
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3
requirements.txt
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3
requirements.txt
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freqtrade[hyperopt]>=2025.1
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plotly>=5.0
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scipy>=1.11
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21
scripts/_env.sh
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21
scripts/_env.sh
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#!/usr/bin/env bash
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# Resolve freqtrade binary: prefer docker compose, else local .venv
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set -euo pipefail
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ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
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cd "$ROOT"
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if command -v docker >/dev/null 2>&1 && docker compose version >/dev/null 2>&1; then
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freqtrade() {
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docker compose run --rm freqtrade "$@"
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}
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elif [[ -x "$ROOT/.venv/bin/freqtrade" ]]; then
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# shellcheck disable=SC1091
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source "$ROOT/.venv/bin/activate"
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freqtrade() {
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"$ROOT/.venv/bin/freqtrade" "$@"
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}
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else
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echo "Neither Docker nor .venv/bin/freqtrade found." >&2
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echo "Install Docker Desktop, or: python3.12 -m venv .venv && .venv/bin/pip install freqtrade plotly" >&2
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exit 1
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fi
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83
scripts/apply_hyperopt_params.sh
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83
scripts/apply_hyperopt_params.sh
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#!/usr/bin/env bash
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set -euo pipefail
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# shellcheck disable=SC1091
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source "$(dirname "$0")/_env.sh"
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# Export best (or N-th) hyperopt epoch into strategy params JSON so backtesting
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# picks them up: user_data/strategies/<Strategy>.json
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STRATEGY="${STRATEGY:-SampleStrategy}"
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EPOCH="${EPOCH:--1}"
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OUT="${OUT:-user_data/strategies/${STRATEGY}.json}"
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TMP="$(mktemp)"
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trap 'rm -f "$TMP"' EXIT
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freqtrade hyperopt-show \
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--config user_data/config.json \
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-n "${EPOCH}" \
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--print-json \
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--no-header >"$TMP"
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PYTHON_BIN="${ROOT}/.venv/bin/python"
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if [[ ! -x "${PYTHON_BIN}" ]]; then
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PYTHON_BIN="$(command -v python3)"
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fi
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"${PYTHON_BIN}" - "$TMP" "$STRATEGY" "$OUT" <<'PY'
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import json, sys
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from pathlib import Path
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src, strategy, out = sys.argv[1], sys.argv[2], sys.argv[3]
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raw = Path(src).read_text().strip()
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# hyperopt-show may print log noise; keep the last JSON object
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start = raw.rfind("{")
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if start < 0:
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raise SystemExit(f"No JSON found in hyperopt-show output:\n{raw[:500]}")
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payload = json.loads(raw[start:])
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KNOWN = ("buy", "sell", "roi", "stoploss", "trailing", "protection")
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def expand_tp_combo(sell: dict) -> dict:
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"""If sell has tp_rr_combo 'a,b,c', mirror into tp1_rr/tp2_rr/tp3_rr."""
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combo = sell.get("tp_rr_combo")
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if combo is None:
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return sell
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if isinstance(combo, (list, tuple)) and len(combo) == 3:
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a, b, c = (float(x) for x in combo)
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sell["tp_rr_combo"] = f"{a},{b},{c}"
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elif isinstance(combo, str) and "," in combo:
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a, b, c = (float(x) for x in combo.split(","))
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else:
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return sell
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sell["tp1_rr"] = a
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sell["tp2_rr"] = b
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sell["tp3_rr"] = c
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return sell
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def as_params(obj: dict) -> dict:
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if "params" in obj and isinstance(obj["params"], dict):
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raw_params = obj["params"]
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if any(k in raw_params for k in KNOWN):
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params = {k: v for k, v in raw_params.items() if k in KNOWN}
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else:
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params = {"buy": raw_params} if raw_params else {}
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elif any(k in obj for k in KNOWN):
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params = {k: v for k, v in obj.items() if k in KNOWN}
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else:
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params = {"buy": obj} if obj else {}
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if "sell" in params and isinstance(params["sell"], dict):
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params["sell"] = expand_tp_combo(dict(params["sell"]))
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return params
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params = as_params(payload)
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doc = {
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"strategy_name": strategy,
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"params": params,
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}
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Path(out).write_text(json.dumps(doc, indent=2) + "\n")
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print(f"Wrote {out}")
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print(json.dumps(params, indent=2))
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PY
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16
scripts/backtest.sh
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16
scripts/backtest.sh
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#!/usr/bin/env bash
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set -euo pipefail
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# shellcheck disable=SC1091
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source "$(dirname "$0")/_env.sh"
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TIMERANGE="${TIMERANGE:-20240701-}"
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STRATEGY="${STRATEGY:-SampleStrategy}"
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freqtrade backtesting \
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--config user_data/config.json \
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--strategy "${STRATEGY}" \
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--timeframe 15m \
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--timerange "${TIMERANGE}" \
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--breakdown day \
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--cache none \
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"$@"
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15
scripts/download_data.sh
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15
scripts/download_data.sh
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#!/usr/bin/env bash
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set -euo pipefail
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# shellcheck disable=SC1091
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source "$(dirname "$0")/_env.sh"
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TIMERANGE="${TIMERANGE:-20240701-}"
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PAIRS="${PAIRS:-BTC/USDT:USDT}"
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freqtrade download-data \
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--config user_data/config.json \
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--exchange binance \
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--trading-mode futures \
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--pairs ${PAIRS} \
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--timeframes 15m 6h \
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--timerange "${TIMERANGE}"
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38
scripts/hyperopt.sh
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38
scripts/hyperopt.sh
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#!/usr/bin/env bash
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set -euo pipefail
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# shellcheck disable=SC1091
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source "$(dirname "$0")/_env.sh"
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# In-sample range for hyperopt; use a later TIMERANGE for OOS backtest.
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# --analyze-per-epoch is required when buy/sell params change populate_indicators
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# (not only entry/exit columns). Set ANALYZE_PER_EPOCH=0 to disable.
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TIMERANGE="${TIMERANGE:-20240701-20260101}"
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STRATEGY="${STRATEGY:-SampleStrategy}"
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EPOCHS="${EPOCHS:-100}"
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SPACES="${SPACES:-buy sell}"
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LOSS="${LOSS:-SharpeHyperOptLossDaily}"
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JOBS="${JOBS:-}"
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ANALYZE_PER_EPOCH="${ANALYZE_PER_EPOCH:-1}"
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# shellcheck disable=SC2206
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SPACES_ARR=(${SPACES})
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ARGS=(
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--config user_data/config.json
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--strategy "${STRATEGY}"
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--timeframe 15m
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--timerange "${TIMERANGE}"
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--spaces "${SPACES_ARR[@]}"
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--hyperopt-loss "${LOSS}"
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-e "${EPOCHS}"
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)
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if [[ "${ANALYZE_PER_EPOCH}" != "0" ]]; then
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ARGS+=(--analyze-per-epoch)
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fi
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if [[ -n "${JOBS}" ]]; then
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ARGS+=(-j "${JOBS}")
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fi
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freqtrade hyperopt "${ARGS[@]}" "$@"
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32
scripts/plot.sh
Executable file
32
scripts/plot.sh
Executable file
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#!/usr/bin/env bash
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set -euo pipefail
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# shellcheck disable=SC1091
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source "$(dirname "$0")/_env.sh"
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TIMERANGE="${TIMERANGE:-20250101-20250201}"
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PAIR="${PAIR:-BTC/USDT:USDT}"
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STRATEGY="${STRATEGY:-SampleStrategy}"
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mkdir -p user_data/plot
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echo "==> plot-profit (equity curve)"
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freqtrade plot-profit \
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--config user_data/config.json \
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--strategy "${STRATEGY}" \
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--timerange "${TIMERANGE}" \
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--timeframe 15m \
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"$@"
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||||
echo "==> trade chart (price / signals / SL·TP / fills / volume)"
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PYTHON_BIN="${ROOT}/.venv/bin/python"
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if [[ ! -x "${PYTHON_BIN}" ]]; then
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PYTHON_BIN="python3"
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fi
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"${PYTHON_BIN}" "$(dirname "$0")/plot_trades_chart.py" \
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--config user_data/config.json \
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--strategy "${STRATEGY}" \
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--pair "${PAIR}" \
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--timerange "${TIMERANGE}" \
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--timeframe 15m
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echo "HTML plots are under user_data/plot/"
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335
scripts/plot_trades_chart.py
Normal file
335
scripts/plot_trades_chart.py
Normal file
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#!/usr/bin/env python3
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"""
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Clean trade chart: price, signals, SL/TP levels, filled trades, volume.
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Price / signals / SL·TP / fills — no indicator clutter.
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"""
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||||
from __future__ import annotations
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||||
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||||
import argparse
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import logging
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import sys
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||||
from datetime import UTC, datetime
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from pathlib import Path
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||||
import pandas as pd
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||||
import plotly.graph_objects as go
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||||
from plotly.subplots import make_subplots
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||||
from freqtrade.configuration import Configuration
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from freqtrade.data.btanalysis import extract_trades_of_period
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from freqtrade.data.converter import trim_dataframe
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.misc import pair_to_filename
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from freqtrade.plot.plotting import init_plotscript, store_plot_file
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from freqtrade.resolvers import ExchangeResolver, StrategyResolver
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||||
from freqtrade.strategy import IStrategy
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||||
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
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||||
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||||
logging.basicConfig(level=logging.INFO, format="%(message)s")
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||||
logger = logging.getLogger("plot_trades_chart")
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||||
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||||
SIGNAL_SIZE = 16
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||||
TRADE_SIZE = 14
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||||
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||||
LEVEL_STYLES = {
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||||
"sl": ("SL", "#e74c3c", "solid", 2),
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||||
"tp1": ("TP1", "#27ae60", "solid", 1.5),
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||||
"tp2": ("TP2", "#2ecc71", "dash", 1.2),
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||||
"tp3": ("TP3", "#1abc9c", "dot", 1.2),
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||||
}
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||||
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||||
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||||
def _signal_scatter(
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||||
data: pd.DataFrame, column: str, color: str, direction: str, size: int
|
||||
) -> go.Scatter | None:
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||||
if column not in data.columns:
|
||||
return None
|
||||
df = data[data[column] == 1]
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||||
if df.empty:
|
||||
return None
|
||||
return go.Scatter(
|
||||
x=df["date"],
|
||||
y=df["close"],
|
||||
mode="markers",
|
||||
name=column,
|
||||
marker=dict(
|
||||
symbol=f"triangle-{direction}-dot",
|
||||
size=size,
|
||||
line=dict(width=1.5, color=color),
|
||||
color=color,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def _levels_for_trade(row: pd.Series, candles: pd.DataFrame) -> dict[str, float] | None:
|
||||
"""Read frozen SL/TP from the entry candle (strategy columns)."""
|
||||
open_ts = pd.Timestamp(row["open_date"])
|
||||
if open_ts.tzinfo is None:
|
||||
open_ts = open_ts.tz_localize("UTC")
|
||||
dates = pd.to_datetime(candles["date"], utc=True)
|
||||
matched = candles.loc[dates <= open_ts]
|
||||
if matched.empty:
|
||||
return None
|
||||
candle = matched.iloc[-1]
|
||||
prefix = "short" if bool(row.get("is_short", False)) else "long"
|
||||
out: dict[str, float] = {}
|
||||
for key in ("sl", "tp1", "tp2", "tp3"):
|
||||
col = f"{prefix}_{key}"
|
||||
if col not in candle.index or pd.isna(candle[col]):
|
||||
return None
|
||||
out[key] = float(candle[col])
|
||||
return out
|
||||
|
||||
|
||||
def _tp1_fill_time(row: pd.Series) -> pd.Timestamp | None:
|
||||
orders = row.get("orders")
|
||||
if not isinstance(orders, list):
|
||||
return None
|
||||
for order in orders:
|
||||
tag = str(order.get("ft_order_tag") or "")
|
||||
if tag == "tp1" or tag.startswith("tp1"):
|
||||
ts = order.get("order_filled_timestamp") or order.get("order_filled_date")
|
||||
if ts is None:
|
||||
return None
|
||||
if isinstance(ts, (int, float)):
|
||||
return pd.to_datetime(ts, unit="ms", utc=True)
|
||||
return pd.to_datetime(ts, utc=True)
|
||||
return None
|
||||
|
||||
|
||||
def _add_trade_levels(fig: go.Figure, trades: pd.DataFrame, candles: pd.DataFrame) -> None:
|
||||
seen: set[str] = set()
|
||||
for _, row in trades.iterrows():
|
||||
levels = _levels_for_trade(row, candles)
|
||||
if not levels:
|
||||
continue
|
||||
x0, x1 = row["open_date"], row["close_date"]
|
||||
if pd.isna(x1):
|
||||
continue
|
||||
be_from = _tp1_fill_time(row)
|
||||
|
||||
for key, price in levels.items():
|
||||
name, color, dash, width = LEVEL_STYLES[key]
|
||||
show = name not in seen
|
||||
if show:
|
||||
seen.add(name)
|
||||
|
||||
if key == "sl" and be_from is not None and be_from > x0:
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=[x0, be_from],
|
||||
y=[price, price],
|
||||
mode="lines",
|
||||
name=name,
|
||||
showlegend=show,
|
||||
line=dict(color=color, width=width, dash=dash),
|
||||
hovertemplate=f"{name}: %{{y:.1f}}<extra></extra>",
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
be_name = "SL (BE)"
|
||||
be_show = be_name not in seen
|
||||
if be_show:
|
||||
seen.add(be_name)
|
||||
entry = float(row["open_rate"])
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=[be_from, x1],
|
||||
y=[entry, entry],
|
||||
mode="lines",
|
||||
name=be_name,
|
||||
showlegend=be_show,
|
||||
line=dict(color="#f39c12", width=2, dash="dash"),
|
||||
hovertemplate=f"{be_name}: %{{y:.1f}}<extra></extra>",
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
else:
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=[x0, x1],
|
||||
y=[price, price],
|
||||
mode="lines",
|
||||
name=name,
|
||||
showlegend=show,
|
||||
line=dict(color=color, width=width, dash=dash),
|
||||
hovertemplate=f"{name}: %{{y:.1f}}<extra></extra>",
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
|
||||
|
||||
def _add_filled_trades(fig: go.Figure, trades: pd.DataFrame) -> None:
|
||||
if trades is None or trades.empty:
|
||||
return
|
||||
|
||||
desc = trades.apply(
|
||||
lambda r: (
|
||||
f"{r['profit_ratio']:.2%}, "
|
||||
+ (f"{r['enter_tag']}, " if pd.notna(r.get('enter_tag')) else "")
|
||||
+ f"{r['exit_reason']}, "
|
||||
+ f"{r['trade_duration']} min"
|
||||
),
|
||||
axis=1,
|
||||
)
|
||||
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=trades["open_date"],
|
||||
y=trades["open_rate"],
|
||||
mode="markers",
|
||||
name="Trade entry",
|
||||
text=desc,
|
||||
marker=dict(symbol="circle-open", size=TRADE_SIZE, line=dict(width=2.5), color="cyan"),
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
|
||||
wins = trades["profit_ratio"] > 0
|
||||
losses = ~wins
|
||||
if wins.any():
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=trades.loc[wins, "close_date"],
|
||||
y=trades.loc[wins, "close_rate"],
|
||||
mode="markers",
|
||||
name="Exit - Profit",
|
||||
text=desc[wins],
|
||||
marker=dict(
|
||||
symbol="square-open", size=TRADE_SIZE, line=dict(width=2.5), color="green"
|
||||
),
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
if losses.any():
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=trades.loc[losses, "close_date"],
|
||||
y=trades.loc[losses, "close_rate"],
|
||||
mode="markers",
|
||||
name="Exit - Loss",
|
||||
text=desc[losses],
|
||||
marker=dict(
|
||||
symbol="square-open", size=TRADE_SIZE, line=dict(width=2.5), color="red"
|
||||
),
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
|
||||
|
||||
def build_figure(pair: str, data: pd.DataFrame, trades: pd.DataFrame) -> go.Figure:
|
||||
fig = make_subplots(
|
||||
rows=2,
|
||||
cols=1,
|
||||
shared_xaxes=True,
|
||||
row_width=[1, 4],
|
||||
vertical_spacing=0.02,
|
||||
)
|
||||
fig.update_layout(
|
||||
title=f"{pair} — trades",
|
||||
xaxis_rangeslider_visible=False,
|
||||
legend=dict(orientation="h", yanchor="bottom", y=1.02, x=0),
|
||||
margin=dict(t=80, b=40),
|
||||
modebar_add=["v1hovermode", "toggleSpikeLines"],
|
||||
)
|
||||
fig.update_yaxes(title_text="Price", row=1, col=1)
|
||||
fig.update_yaxes(title_text="Volume", row=2, col=1)
|
||||
|
||||
fig.add_trace(
|
||||
go.Candlestick(
|
||||
x=data["date"],
|
||||
open=data["open"],
|
||||
high=data["high"],
|
||||
low=data["low"],
|
||||
close=data["close"],
|
||||
name="Price",
|
||||
increasing_line_color="#26a69a",
|
||||
decreasing_line_color="#ef5350",
|
||||
),
|
||||
row=1,
|
||||
col=1,
|
||||
)
|
||||
|
||||
for scatter in (
|
||||
_signal_scatter(data, "enter_long", "#2ecc71", "up", SIGNAL_SIZE),
|
||||
_signal_scatter(data, "exit_long", "#e74c3c", "down", SIGNAL_SIZE),
|
||||
_signal_scatter(data, "enter_short", "#3498db", "down", SIGNAL_SIZE),
|
||||
_signal_scatter(data, "exit_short", "#9b59b6", "up", SIGNAL_SIZE),
|
||||
):
|
||||
if scatter is not None:
|
||||
fig.add_trace(scatter, row=1, col=1)
|
||||
|
||||
if trades is not None and not trades.empty:
|
||||
_add_trade_levels(fig, trades, data)
|
||||
_add_filled_trades(fig, trades)
|
||||
|
||||
fig.add_trace(
|
||||
go.Bar(
|
||||
x=data["date"],
|
||||
y=data["volume"],
|
||||
name="Volume",
|
||||
marker_color="DarkSlateGrey",
|
||||
marker_line_color="DarkSlateGrey",
|
||||
),
|
||||
row=2,
|
||||
col=1,
|
||||
)
|
||||
return fig
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--config", default="user_data/config.json")
|
||||
parser.add_argument("--strategy", default="SampleStrategy")
|
||||
parser.add_argument("--timerange", default=None)
|
||||
parser.add_argument("--pair", default="BTC/USDT:USDT")
|
||||
parser.add_argument("--timeframe", default="15m")
|
||||
parser.add_argument("--outfile", default=None)
|
||||
args = parser.parse_args()
|
||||
|
||||
cfg = Configuration.from_files([args.config])
|
||||
cfg["strategy"] = args.strategy
|
||||
cfg["timeframe"] = args.timeframe
|
||||
cfg["pairs"] = [args.pair]
|
||||
if args.timerange:
|
||||
cfg["timerange"] = args.timerange
|
||||
cfg.setdefault("trade_source", "file")
|
||||
|
||||
strategy = StrategyResolver.load_strategy(cfg)
|
||||
exchange = ExchangeResolver.load_exchange(cfg)
|
||||
IStrategy.dp = DataProvider(cfg, exchange)
|
||||
strategy.ft_bot_start()
|
||||
strategy_safe_wrapper(strategy.bot_loop_start)(current_time=datetime.now(UTC))
|
||||
|
||||
plot_elements = init_plotscript(cfg, list(exchange.markets), strategy.startup_candle_count)
|
||||
timerange = plot_elements["timerange"]
|
||||
trades = plot_elements["trades"]
|
||||
|
||||
pair = args.pair
|
||||
if pair not in plot_elements["ohlcv"]:
|
||||
raise SystemExit(f"No OHLCV for {pair}")
|
||||
|
||||
data = strategy.analyze_ticker(plot_elements["ohlcv"][pair], {"pair": pair})
|
||||
data = trim_dataframe(data, timerange)
|
||||
|
||||
if not trades.empty:
|
||||
trades_pair = trades.loc[trades["pair"] == pair]
|
||||
trades_pair = extract_trades_of_period(data, trades_pair)
|
||||
else:
|
||||
trades_pair = trades
|
||||
|
||||
fig = build_figure(pair, data, trades_pair)
|
||||
out_name = args.outfile or f"freqtrade-plot-{pair_to_filename(pair)}-{args.timeframe}.html"
|
||||
store_plot_file(fig, filename=out_name, directory=Path(cfg["user_data_dir"]) / "plot")
|
||||
logger.info("Open: user_data/plot/%s", out_name)
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
60
user_data/config.json
Normal file
60
user_data/config.json
Normal file
|
|
@ -0,0 +1,60 @@
|
|||
{
|
||||
"max_open_trades": 1,
|
||||
"stake_currency": "USDT",
|
||||
"stake_amount": "unlimited",
|
||||
"tradable_balance_ratio": 0.99,
|
||||
"fiat_display_currency": "USD",
|
||||
"dry_run": true,
|
||||
"dry_run_wallet": 10000,
|
||||
"cancel_open_orders_on_exit": false,
|
||||
"trading_mode": "futures",
|
||||
"margin_mode": "isolated",
|
||||
"unfilledtimeout": {
|
||||
"entry": 10,
|
||||
"exit": 10,
|
||||
"exit_timeout_count": 0,
|
||||
"unit": "minutes"
|
||||
},
|
||||
"entry_pricing": {
|
||||
"price_side": "same",
|
||||
"use_order_book": true,
|
||||
"order_book_top": 1,
|
||||
"price_last_balance": 0.0,
|
||||
"check_depth_of_market": {
|
||||
"enabled": false,
|
||||
"bids_to_ask_delta": 1
|
||||
}
|
||||
},
|
||||
"exit_pricing": {
|
||||
"price_side": "same",
|
||||
"use_order_book": true,
|
||||
"order_book_top": 1
|
||||
},
|
||||
"exchange": {
|
||||
"name": "binance",
|
||||
"key": "",
|
||||
"secret": "",
|
||||
"ccxt_config": {},
|
||||
"ccxt_async_config": {},
|
||||
"pair_whitelist": [
|
||||
"BTC/USDT:USDT"
|
||||
],
|
||||
"pair_blacklist": []
|
||||
},
|
||||
"pairlists": [
|
||||
{
|
||||
"method": "StaticPairList"
|
||||
}
|
||||
],
|
||||
"timeframe": "15m",
|
||||
"dataformat_ohlcv": "feather",
|
||||
"dataformat_trades": "feather",
|
||||
"fee": 0.0005,
|
||||
"strategy": "SampleStrategy",
|
||||
"bot_name": "428-backtester",
|
||||
"initial_state": "running",
|
||||
"force_entry_enable": false,
|
||||
"internals": {
|
||||
"process_throttle_secs": 5
|
||||
}
|
||||
}
|
||||
63
user_data/strategies/SampleStrategy.py
Normal file
63
user_data/strategies/SampleStrategy.py
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
"""
|
||||
Minimal sample strategy for the 428 / Integral backtester scaffold.
|
||||
|
||||
Replace this file (or add your own under user_data/strategies/) and set
|
||||
STRATEGY=<ClassName> when running scripts. Defaults in config / compose
|
||||
point here so a fresh clone backtests without proprietary logic.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.strategy import IStrategy, IntParameter
|
||||
import talib.abstract as ta
|
||||
|
||||
|
||||
class SampleStrategy(IStrategy):
|
||||
"""EMA crossover + RSI filter — placeholder only, not a production system."""
|
||||
|
||||
INTERFACE_VERSION = 3
|
||||
timeframe = "15m"
|
||||
can_short = True
|
||||
|
||||
minimal_roi = {"0": 0.04, "60": 0.02, "180": 0.01, "360": 0}
|
||||
stoploss = -0.03
|
||||
trailing_stop = False
|
||||
process_only_new_candles = True
|
||||
startup_candle_count = 50
|
||||
|
||||
buy_rsi = IntParameter(20, 40, default=30, space="buy", optimize=True)
|
||||
sell_rsi = IntParameter(60, 80, default=70, space="sell", optimize=True)
|
||||
|
||||
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
dataframe["ema_fast"] = ta.EMA(dataframe, timeperiod=12)
|
||||
dataframe["ema_slow"] = ta.EMA(dataframe, timeperiod=26)
|
||||
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
|
||||
return dataframe
|
||||
|
||||
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
dataframe.loc[
|
||||
(dataframe["ema_fast"] > dataframe["ema_slow"])
|
||||
& (dataframe["rsi"] < self.buy_rsi.value)
|
||||
& (dataframe["volume"] > 0),
|
||||
"enter_long",
|
||||
] = 1
|
||||
|
||||
dataframe.loc[
|
||||
(dataframe["ema_fast"] < dataframe["ema_slow"])
|
||||
& (dataframe["rsi"] > self.sell_rsi.value)
|
||||
& (dataframe["volume"] > 0),
|
||||
"enter_short",
|
||||
] = 1
|
||||
return dataframe
|
||||
|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
dataframe.loc[
|
||||
(dataframe["ema_fast"] < dataframe["ema_slow"]) & (dataframe["volume"] > 0),
|
||||
"exit_long",
|
||||
] = 1
|
||||
dataframe.loc[
|
||||
(dataframe["ema_fast"] > dataframe["ema_slow"]) & (dataframe["volume"] > 0),
|
||||
"exit_short",
|
||||
] = 1
|
||||
return dataframe
|
||||
Loading…
Add table
Reference in a new issue