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Merge dev into main: download filename, multi-dir MCP, dashboard enhancements
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‎examples/open.py‎

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from investing_algorithm_framework import BacktestReport, recalculate_backtests, retag_backtests
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batch_one_path = os.path.join("examples", "batch_one")
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batch_one_path = os.path.join(os.path.dirname(__file__), "batch_one")
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if __name__ == "__main__":
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retag_backtests("batch_one", directory_path=batch_one_path)

‎examples/tutorial/notebooks/01_data_exploration.ipynb‎

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"id": "7",
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"metadata": {},
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"source": [
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"## Data downloading\n"
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"## Custom filenames\n",
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"\n",
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"By default, downloaded CSV files are named using the pattern\n",
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"`OHLCV_SYMBOL_MARKET_TIMEFRAME_START_END.csv`. You can override this with the\n",
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"`filename` parameter to use your own naming convention. The `.csv` extension is\n",
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"appended automatically if not present."
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]
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},
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{
@@ -123,6 +128,28 @@
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"id": "8",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example: download with a custom filename\n",
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"# result = download_v2(\n",
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"# symbol=\"BTC/EUR\",\n",
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"# market=MARKET,\n",
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"# time_frame=\"1d\",\n",
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"# data_type=\"ohlcv\",\n",
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"# start_date=backtest_window_date_range.start_date,\n",
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"# end_date=backtest_window_date_range.end_date,\n",
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"# save=True,\n",
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"# storage_path=str(data_storage_path),\n",
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"# filename=\"btc_daily_data\", # saves as btc_daily_data.csv\n",
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"# )\n",
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"# print(f\"Saved to: {result.path}\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9",
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"metadata": {},
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"outputs": [],
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"source": [
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"from investing_algorithm_framework import download_v2, TimeFrame, tqdm\n",
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"in_sample_data = {}\n",
@@ -143,7 +170,9 @@
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" start_date=backtest_window_date_range.start_date,\n",
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" end_date=backtest_window_date_range.end_date,\n",
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" save=True,\n",
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" storage_path=str(data_storage_path)\n",
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" storage_path=str(data_storage_path),\n",
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" # Optional: provide a custom filename instead of the auto-generated one\n",
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" # filename=f\"{symbol}_{time_frame}_in_sample\",\n",
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" )\n",
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" in_sample_data[symbol][time_frame] = {\n",
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" \"data\": result.data,\n",
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" start_date=backtest_window_date_range.start_date,\n",
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" end_date=backtest_window_date_range.end_date,\n",
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" save=True,\n",
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" storage_path=str(data_storage_path)\n",
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" storage_path=str(data_storage_path),\n",
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" # Optional: provide a custom filename instead of the auto-generated one\n",
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" # filename=f\"{symbol}_{time_frame}_out_sample\",\n",
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" )\n",
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" out_sample_data[symbol][time_frame] = {\n",
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" \"data\": result.data,\n",
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" first_date = result.data.index[0]\n",
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"\n",
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" if first_date > backtest_window_date_range.start_date:\n",
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" print(f\"Warning: Data for {symbol_pair} starts on {first_date} which is after the requested start date of {backtest_window_date_range.start_date}.\")\n"
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" print(f\"Warning: Data for {symbol_pair} starts on {first_date} which is after the requested start date of {backtest_window_date_range.start_date}.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9",
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"id": "10",
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"metadata": {},
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"source": [
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"## Check data completeness and fill missing timestamps"
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "10",
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"id": "11",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "11",
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"id": "12",
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"metadata": {},
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"source": [
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"## Analysis on the Backtest Windows"
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "12",
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"id": "13",
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"metadata": {},
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"outputs": [],
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"source": [

‎examples/tutorial/notebooks/09_report_and_llm_workflow.ipynb‎

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"cell_type": "markdown",
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"id": "3",
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"metadata": {},
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"source": [
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"## Step 1b — Tag Your Backtests\n",
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"\n",
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"Tags let you label and group strategies — for example by batch name, experiment,\n",
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"or configuration variant. Tags are **persisted** in a `tag.json` file inside\n",
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"each backtest directory, so they survive across subsequent loads.\n",
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"\n",
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"### How tags get assigned\n",
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"\n",
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"There are three ways a backtest gets a tag:\n",
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"\n",
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"**1. During the backtest run** — Set `tag` in the strategy metadata:\n",
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"```python\n",
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"strategy = TradingStrategy(\n",
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" algorithm_id=\"momentum_v3\",\n",
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" metadata={\"tag\": \"experiment_A\"},\n",
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" ...\n",
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")\n",
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"```\n",
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"The tag is automatically extracted and saved with the backtest.\n",
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"\n",
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"**2. After the fact with `retag_backtests()`** — Retag all backtests in a\n",
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"directory (or filter by strategy_id):\n",
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"```python\n",
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"from investing_algorithm_framework import retag_backtests\n",
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"\n",
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"# Tag everything in a directory\n",
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"retag_backtests(\"experiment_A\", directory_path=\"my_batch\")\n",
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"\n",
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"# Tag only a specific strategy\n",
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"retag_backtests(\"experiment_B\", directory_path=\"my_batch\", strategy_id=\"momentum_v3\")\n",
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"```\n",
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"\n",
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"**3. Multi-directory loading** — When you load from multiple directories,\n",
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"each directory name is used as the default tag (unless a persisted tag exists):\n",
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"```python\n",
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"report = BacktestReport.open(directory_path=[\"batch_A\", \"batch_B\"])\n",
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"# Strategies from batch_A get tag \"batch_A\", etc.\n",
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"```\n",
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"\n",
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"### What tags do in the dashboard\n",
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"\n",
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"- **Filter bar** — When 2+ tags exist, a chip-based filter bar appears at the top\n",
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"- **Tag badges** — Every strategy name shows its tag badge in all tables\n",
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"- **Collapsible sidebar groups** — Strategies are grouped by tag with collapsible headers\n",
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"- **MCP server** — The `list_strategies` and `get_strategy_details` tools include tag info"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4",
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"metadata": {},
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"outputs": [],
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"source": [
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"from investing_algorithm_framework import retag_backtests\n",
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"\n",
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"# Retag all backtests in a directory\n",
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"count = retag_backtests(\"experiment_A\", directory_path=batch_dir)\n",
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"print(f\"Retagged {count} backtests with tag 'experiment_A'\")\n",
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"\n",
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"# Retag a single strategy by its algorithm_id\n",
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"count = retag_backtests(\n",
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" \"experiment_B\",\n",
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" directory_path=batch_dir,\n",
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" strategy_id=\"momentum_v3\"\n",
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")\n",
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"print(f\"Retagged {count} backtests with tag 'experiment_B'\")\n",
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"\n",
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"# Reload to see the tags\n",
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"report = BacktestReport.open(directory_path=batch_dir)\n",
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"for bt in report.backtests:\n",
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" print(f\" • {bt.algorithm_id}: tag={bt.tag}\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5",
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"metadata": {},
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"source": [
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"### Multi-directory loading\n",
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"\n",
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"You can also load backtests from **multiple directories** at once by passing a list.\n",
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"Each directory name becomes the default tag for its strategies (unless they already\n",
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"have a persisted tag)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load from multiple directories — each dir name becomes the tag\n",
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"report = BacktestReport.open(directory_path=[\"batch_A\", \"batch_B\"])\n",
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"\n",
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"for bt in report.backtests:\n",
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" print(f\" • {bt.algorithm_id}: tag={bt.tag}\")\n",
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"\n",
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"# Open the dashboard — strategies will be grouped by tag in the sidebar\n",
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"report.show()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7",
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"metadata": {},
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"source": [
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"## Step 2 — Open the Interactive Dashboard\n",
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"\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4",
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"id": "8",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5",
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"id": "9",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "10",
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"metadata": {},
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"source": [
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"## Step 3 — Start the MCP Server (Connect Your LLM)\n",
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"### Start the server from your terminal\n",
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"\n",
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"```bash\n",
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"# Single directory\n",
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"iaf mcp -d your_batch_directory\n",
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"\n",
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"# Multiple directories — repeat -d for each\n",
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"iaf mcp -d batch_one -d batch_two -d batch_three\n",
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"```\n",
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"\n",
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"Or if you haven't installed the CLI:\n",
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"\n",
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"```bash\n",
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"python -m investing_algorithm_framework.cli.mcp_server -d your_batch_directory\n",
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"\n",
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"# Multiple directories\n",
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"python -m investing_algorithm_framework.cli.mcp_server -d batch_one -d batch_two\n",
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"```\n",
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"\n",
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"### Configure VS Code to use it\n",
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" \"servers\": {\n",
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" \"backtest-analysis\": {\n",
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" \"command\": \"iaf\",\n",
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" \"args\": [\"mcp\", \"-d\", \"your_batch_directory\"]\n",
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" \"args\": [\"mcp\", \"-d\", \"batch_one\", \"-d\", \"batch_two\"]\n",
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" }\n",
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" }\n",
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" }\n",
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},
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{
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"cell_type": "markdown",
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"id": "11",
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"metadata": {},
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"source": [
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"## Step 4 — The LLM Toolkit (23 MCP Tools)\n",
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},
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{
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"cell_type": "markdown",
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"id": "12",
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"metadata": {},
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"source": [
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"## Step 5 — Ask the LLM to Analyze Your Strategies\n",
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},
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{
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"cell_type": "markdown",
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"id": "13",
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"metadata": {},
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"source": [
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"## Step 6 — The Iterative Workflow\n",
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},
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{
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"cell_type": "markdown",
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"id": "14",
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"metadata": {},
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"source": [
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"## Step 7 — Notes as Self-Contained Analysis Documents\n",
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},
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{
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"cell_type": "markdown",
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"id": "15",
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"metadata": {},
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"source": [
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"## Step 8 — Example Conversation with the LLM\n",
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},
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{
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"cell_type": "markdown",
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"id": "16",
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"metadata": {},
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"source": [
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"## Step 9 — Apply Selections & Export\n",
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},
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{
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"cell_type": "markdown",
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"id": "17",
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"metadata": {},
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"source": [
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"## Step 10 — You Can Also Save / Reload Programmatically\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "14",
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"id": "18",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "19",
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"metadata": {},
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"source": [
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"## TL;DR — The Complete Workflow\n",
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"```bash\n",
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"# 3. Start the MCP server (in a separate terminal)\n",
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"iaf mcp -d my_batch\n",
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"\n",
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"# Or load multiple batch directories at once\n",
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"iaf mcp -d batch_one -d batch_two\n",
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"```\n",
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"\n",
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"```\n",

‎investing_algorithm_framework/app/reporting/templates/dashboard.css‎

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.challenger-btn.active { background:var(--accent); color:#fff; border-color:var(--accent); }
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.challenger-row { background:rgba(34,211,238,0.06) !important; }
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.challenger-row td { border-bottom:1px solid var(--accent) !important; }
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.challenger-col { background:rgba(34,211,238,0.06) !important; border-bottom:2px solid var(--accent) !important; }
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.sb-challenger { margin-left:auto; font-size:11px; color:var(--accent); }
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.sb-item .sb-cb { width:13px; height:13px; accent-color:var(--accent); cursor:pointer; flex-shrink:0; margin:0; }
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.sb-item .sb-chal-btn { background:none; border:1px solid var(--border); border-radius:3px; cursor:pointer; font-size:11px; color:var(--text-dim); padding:0 3px; margin-left:auto; line-height:1.2; transition:all 0.15s; flex-shrink:0; }

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