Add indicators fetcher, rich dashboard renderer, and remove trade executor/status
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DiTus
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WIKI/dashboard_configuration.md
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WIKI/dashboard_configuration.md
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# Dashboard Configuration Guide
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This guide explains how to configure which tables are displayed on the live terminal dashboard.
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## Overview
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The dashboard is rendered by the `DashboardRenderer` class in `dashboard.py`. It currently supports two tables:
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| Table Key | Title | Description |
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|-----------|-------|-------------|
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| `market` | Market Dashboard | Live prices, best bid/ask, gap, and direction for watched coins |
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| `strategies` | Strategies | Signal, signal price, last change, timeframe, and size for each enabled strategy |
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Each table can be independently enabled or disabled. When only one table is visible, it takes the full terminal width. When both are visible, they split side-by-side.
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## Configuration
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### Default Visibility
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The default table visibility is set when `DashboardRenderer` is instantiated in `main_app.py` (`MainApp.__init__`):
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```python
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self.renderer = DashboardRenderer(table_visibility={
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"market": True,
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"strategies": False,
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})
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```
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By default, the **market table is enabled** and the **strategies table is disabled**.
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### Changing Default Visibility
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To change which tables are shown by default, edit the `table_visibility` dict in `main_app.py` (`MainApp.__init__`, line 349):
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```python
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self.renderer = DashboardRenderer(table_visibility={
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"market": True,
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"strategies": True, # enable strategies table
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})
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```
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### Runtime Toggling
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Tables can be toggled at runtime through the `MainApp.toggle_table()` method, which delegates to `DashboardRenderer.toggle_table()`:
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```python
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# Flip the strategies table on/off
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app.toggle_table("strategies")
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# Explicitly enable
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app.toggle_table("strategies", enabled=True)
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# Explicitly disable
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app.toggle_table("strategies", enabled=False)
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```
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The same methods are available directly on the renderer:
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```python
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renderer = DashboardRenderer()
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renderer.toggle_table("market") # flip
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renderer.toggle_table("strategies", False) # disable
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```
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## How It Works
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### DashboardRenderer (`dashboard.py`)
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- `__init__(console=None, table_visibility=None)` — accepts an optional `table_visibility` dict. If not provided, defaults to `{"market": True, "strategies": False}`.
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- `toggle_table(table_name, enabled=None)` — flips the visibility state when `enabled` is `None`, or sets it to the given boolean. Raises `ValueError` for unknown table names.
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- `build_layout(...)` — conditionally builds only the tables that are enabled, then arranges them:
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- **One table:** `Layout(table)` — full width
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- **Two tables:** `Layout.split_row(Layout(t1), Layout(t2))` — side-by-side
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- **Zero tables:** empty `Layout`
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### MainApp (`main_app.py`)
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- `MainApp.__init__` creates the `DashboardRenderer` with the `table_visibility` config.
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- `MainApp.toggle_table(table_name, enabled=None)` delegates to the renderer for runtime toggling.
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- `MainApp.display_dashboard()` calls `renderer.build_layout()` which respects the current visibility settings.
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## File Reference
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| File | Line | Description |
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|------|------|-------------|
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| `dashboard.py` | 22 | `DashboardRenderer.__init__` — accepts `table_visibility` parameter |
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| `dashboard.py` | 32 | `toggle_table()` method — flips or sets table visibility |
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| `dashboard.py` | 172 | `build_layout()` — conditionally includes tables based on visibility |
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| `main_app.py` | 349 | `MainApp.__init__` — sets default `table_visibility` |
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| `main_app.py` | 385 | `MainApp.toggle_table()` — runtime toggle method |
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WIKI/indicators.md
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WIKI/indicators.md
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# Indicators Guide
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This guide explains how to configure and use the Indicators table on the live terminal dashboard.
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## Overview
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The Indicators table displays computed financial indicators (e.g., WTI/BRENT ratio, live prices, moving averages, RSI) with their current value, 1-hour and 1-day percentage changes, and deviation from a long-term average.
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The system is **config-driven** — new indicators are added by editing `_data/indicators.json`. No code changes are required for standard indicator types.
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## Dashboard Table
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The Indicators table is displayed below the Market table in the dashboard. It shows:
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| Column | Description |
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|--------|-------------|
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| `#` | Indicator number |
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| `Indicator` | Display name from config |
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| `Value` | Current indicator value |
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| `1h Change` | Percentage change over the last 1 hour |
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| `1D Change` | Percentage change over the last 1 day |
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| `Deviation` | Deviation from the long-term average |
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Changes are color-coded: **green** for positive, **red** for negative, **yellow** for neutral.
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## Configuration
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### Default Visibility
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The Indicators table is enabled by default. The visibility is set in `main_app.py` (`MainApp.__init__`):
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```python
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self.renderer = DashboardRenderer(table_visibility={
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"market": True,
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"strategies": False,
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"indicators": True,
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})
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```
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### Runtime Toggling
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Toggle the Indicators table at runtime:
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```python
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app.toggle_table("indicators") # flip on/off
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app.toggle_table("indicators", enabled=True) # explicitly enable
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app.toggle_table("indicators", enabled=False) # explicitly disable
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```
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## Indicator Types
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The following indicator types are supported in `_data/indicators.json`:
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### `ratio` — A/B Ratio
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Computes `numerator / denominator`.
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```json
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"wti_brent_ratio": {
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"display_name": "WTI/BRENT",
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"type": "ratio",
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"numerator": "xyz:CL",
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"denominator": "xyz:BRENTOIL",
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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- **Value**: `live(numerator) / live(denominator)` from latest 1m candle closes
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- **1h Change**: compares to ratio from 1h candle close prices
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- **1D Change**: compares to ratio from 1d candle close prices
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- **Deviation**: `(current - long_avg) / long_avg * 100`, where `long_avg` is the mean of daily ratios over all available history
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### `price` — Single Price
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```json
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"wti_price": {
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"display_name": "WTI",
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"type": "price",
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"coin": "xyz:CL",
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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- **Value**: latest close price from `{coin}_1m` table
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- **1h/1D Change**: compares to close from 1h/1d candle tables
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- **Deviation**: `(current - long_avg) / long_avg * 100`, where `long_avg` is the mean of daily closes
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### `spread` — Price Difference
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Computes `numerator - denominator`.
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```json
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"wti_brent_spread": {
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"display_name": "WTI-BRENT Spread",
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"type": "spread",
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"numerator": "xyz:CL",
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"denominator": "xyz:BRENTOIL",
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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### `diff_pct` — Percentage Difference
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Computes `(numerator - denominator) / denominator * 100`.
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```json
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"wti_brent_diff": {
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"display_name": "WTI-BRENT Diff%",
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"type": "diff_pct",
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"numerator": "xyz:CL",
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"denominator": "xyz:BRENTOIL",
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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### `ma` — Moving Average
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```json
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"wti_ma_20": {
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"display_name": "WTI MA(20)",
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"type": "ma",
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"coin": "xyz:CL",
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"timeframe": "1h",
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"period": 20,
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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- **Value**: latest SMA value on the specified timeframe
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- **1h Change**: compares to MA value from 1h candle table
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- **1D Change**: compares to MA value from 1d candle table
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- **Deviation**: `(current_price - MA) / MA * 100` (how far the live price is from the MA)
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### `rsi` — Relative Strength Index
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```json
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"wti_rsi_14": {
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"display_name": "WTI RSI(14)",
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"type": "rsi",
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"coin": "xyz:CL",
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"timeframe": "1h",
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"period": 14,
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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- **Value**: latest RSI value (0-100) on the specified timeframe
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- **1h/1D Change**: absolute change in RSI points
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- **Deviation**: `RSI - 50` (deviation from neutral)
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### `custom` — Custom Function
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Calls a user-defined Python function.
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```json
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"custom_indicator": {
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"display_name": "My Custom Indicator",
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"type": "custom",
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"module": "indicators.custom_indicators",
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"function": "my_custom_calc",
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"args": {"param1": "value1"},
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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The custom function must accept `db_path` as the first argument, plus any `args` from the config, and return a dict:
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```python
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def my_custom_calc(db_path, **kwargs):
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return {
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"value": 0.96611,
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"reference": 0.96044,
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"changes": {"1h": 0.12, "1d": -0.45},
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"deviation": 0.59
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}
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}
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```
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## Data Sources
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All indicator calculations read from the SQLite database `_data/market_data.db`:
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- **Live value**: latest close price from `{coin}_1m` candle table (updated in real-time by `live_candle_fetcher.py`)
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- **1h change**: close price from `{coin}_1h` candle table (second-to-last completed 1h candle)
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- **1D change**: close price from `{coin}_1d` candle table (second-to-last completed 1d candle)
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- **Reference value**: mean of daily values over all available historical data
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## Process Architecture
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```
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indicators_fetcher.py (subprocess, runs every 30s)
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+---> indicators.py (IndicatorCalculator)
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| |
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| +---> _data/market_data.db (SQLite candle data)
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| +---> _data/indicators.json (config)
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+---> _logs/indicators_status.json (output)
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+---> main_app.py (MainApp.read_indicators_status)
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+---> dashboard.py (DashboardRenderer.build_indicators_table)
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```
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## File Reference
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| File | Description |
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|------|-------------|
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| `_data/indicators.json` | Indicator definitions (config) |
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| `indicators.py` | `IndicatorCalculator` class — computation logic |
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| `indicators_fetcher.py` | Standalone script — runs in a loop, computes indicators, writes JSON |
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| `dashboard.py` | `DashboardRenderer.build_indicators_table()` — renders the table |
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| `main_app.py` | `run_indicators_fetcher()` — process target; `MainApp.read_indicators_status()` — reads JSON |
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| `_logs/indicators_status.json` | Output file with computed indicator values |
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## Adding a New Indicator
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1. Edit `_data/indicators.json` and add a new entry:
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```json
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"my_new_indicator": {
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"display_name": "My Indicator",
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"type": "price",
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"coin": "BTC",
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"changes": ["1h", "1d"],
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"show_deviation": true
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}
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```
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2. Restart the application (`python main_app.py`). The Indicators Fetcher will automatically pick up the new config on its next run.
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No code changes are needed for standard indicator types (`ratio`, `price`, `spread`, `diff_pct`, `ma`, `rsi`). For custom calculations, use the `custom` type.
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