8f1bb488df
- IMPLEMENTATION_PLAN.md: new plan with Phases A-D (bug fixes, polish, new analytics, backend analytics) - RALPH_PROMPT.md: updated focus to chart improvements - progress.txt: reset with preserved architecture patterns - guardrails.md: trimmed to relevant rules, added chart-specific guardrails - ralph.ps1: updated banner text
241 lines
9.5 KiB
Markdown
241 lines
9.5 KiB
Markdown
# Ralph Wiggum Loop — Dashboard Visualization Improvements
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You are operating inside an automated loop improving Plotly charts in an NHS patient pathway analysis Dash application. Each iteration you receive fresh context — you have NO memory of previous iterations. Your only memory is the filesystem.
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**Current Focus**: Fix chart bugs, improve visual polish, add new analytics charts. See IMPLEMENTATION_PLAN.md for the full task list organized into Phases A–D.
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## First Actions Every Iteration
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Read these files in this order before doing anything else:
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1. `progress.txt` — What previous iterations accomplished, what's blocked, and what to do next.
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2. `IMPLEMENTATION_PLAN.md` — Task list with status markers, architecture overview, and completion criteria.
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3. `guardrails.md` — Known failure patterns to avoid. You MUST read and follow these.
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4. `CLAUDE.md` — Project architecture and backend code patterns.
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Then run `git log --oneline -5` to see recent commits.
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## Key Files for This Phase
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**When modifying chart functions**, always read first:
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- `src/visualization/plotly_generator.py` — PRIMARY file. All chart generation functions live here (~1782 lines).
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- `dash_app/callbacks/chart.py` — Patient Pathways tab dispatch and chart rendering helpers.
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- `dash_app/callbacks/trust_comparison.py` — Trust Comparison 6-chart callbacks.
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**When adding new analytics charts**, also read:
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- `src/data_processing/pathway_queries.py` — All SQLite query functions. New queries go here.
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- `dash_app/data/queries.py` — Thin wrappers. Add wrapper for each new query.
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- `dash_app/components/chart_card.py` — TAB_DEFINITIONS for Patient Pathways tabs.
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**When modifying UI components**, read:
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- `dash_app/components/trust_comparison.py` — TC landing + dashboard layout.
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- `dash_app/assets/nhs.css` — All CSS styles.
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## Narration
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Narrate your work as you go. Your output is the only visibility the operator has into what's happening. For every significant action, explain what you're doing and why:
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- **Reading files**: "Reading plotly_generator.py to locate the heatmap colorscale..."
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- **Creating code**: "Adding _base_layout() helper to DRY shared layout properties..."
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- **Debugging**: "Chart title color is #003087 instead of CHART_TITLE_COLOR..."
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- **Testing**: "Running python run_dash.py to verify the app starts..."
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- **Committing**: "Committing heatmap fixes."
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Do NOT just output a summary at the end. Narrate throughout.
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## Task Selection
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1. Read ALL tasks in IMPLEMENTATION_PLAN.md — understand the full picture
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2. Skip any marked `[x]` (complete) or `[B]` (blocked)
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3. Check progress.txt for guidance — the previous iteration may have recommendations
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4. **Choose a task** based on:
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- Dependencies (A.1 shared constants before A.2-A.4 which use them)
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- Phase ordering (Phase A before B, B before C, C before D)
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- Previous iteration's recommendations
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5. **Document your reasoning**: Before starting, explain WHY you chose this task
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6. Mark your chosen task `[~]` (in progress) in IMPLEMENTATION_PLAN.md
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If your chosen task is blocked:
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- Mark it `[B]` with a reason
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- Document the blocker in progress.txt
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- Move to a different ready task
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## Development
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Work on ONE task per iteration. Build incrementally and verify as you go.
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### Key Technologies
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- **Dash 4.0.0**: `from dash import Dash, html, dcc, Input, Output, State, ctx, ALL`
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- **Dash Mantine Components 2.5.1**: `import dash_mantine_components as dmc` — `MantineProvider` wraps layout
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- **Plotly**: `import plotly.graph_objects as go` — all chart figures
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- **SQLite**: `import sqlite3` — read-only access to `data/pathways.db`
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- **CSS**: All in `dash_app/assets/nhs.css` — auto-served by Dash
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### plotly_generator.py Patterns
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All chart functions follow the same pattern:
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```python
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def create_CHART_figure(data: list[dict], title: str = "", ...) -> go.Figure:
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"""Create CHART from prepared data."""
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if not data:
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return go.Figure()
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# Build traces from data
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fig = go.Figure(data=traces)
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# Apply layout
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layout = _base_layout(display_title)
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layout.update({...chart-specific overrides...})
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fig.update_layout(**layout)
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return fig
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```
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### Adding a New Chart Tab
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1. Add query function to `src/data_processing/pathway_queries.py` (accept `db_path` param)
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2. Add thin wrapper to `dash_app/data/queries.py` (resolve DB_PATH and delegate)
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3. Add figure function to `src/visualization/plotly_generator.py`
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4. Add tab to `TAB_DEFINITIONS` in `dash_app/components/chart_card.py`
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5. Add `_render_*()` helper in `dash_app/callbacks/chart.py`
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6. Add elif case in `update_chart()` callback
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### Database Access Pattern
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```python
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# In src/data_processing/pathway_queries.py
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def get_something(db_path: Path, filter_id: str, chart_type: str, ...) -> list[dict]:
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conn = sqlite3.connect(str(db_path))
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conn.row_factory = sqlite3.Row
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cursor = conn.cursor()
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cursor.execute("SELECT ... WHERE date_filter_id = ? AND chart_type = ?", [filter_id, chart_type])
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rows = [dict(row) for row in cursor.fetchall()]
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conn.close()
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return rows
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# In dash_app/data/queries.py (thin wrapper)
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from data_processing.pathway_queries import get_something as _get_something
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DB_PATH = Path(__file__).resolve().parents[2] / "data" / "pathways.db"
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def get_something(filter_id="all_6mo", chart_type="directory", ...):
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return _get_something(DB_PATH, filter_id, chart_type, ...)
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```
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### Verification Steps
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After writing code, ALWAYS verify:
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1. **Import check**: `python -c "from dash_app.app import app"` (or specific module)
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2. **App starts**: `python run_dash.py` — must start without errors
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3. **Visual check** (when modifying charts): describe what you expect to see at localhost:8050
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4. **For callbacks**: verify the callback chain fires correctly
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If any step fails, fix the issue before proceeding.
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## Validation Protocol
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Every task MUST pass validation before being marked complete:
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### Tier 1: Code Validation (MANDATORY)
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- Code compiles without Python syntax errors
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- Imports work without errors
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- `python run_dash.py` starts without exceptions
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### Tier 2: Visual Validation (for chart modification tasks)
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- Chart renders in the browser
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- Colors, labels, legend layout match expectations
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- No overflow or overlap issues
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### Tier 3: Functional Validation (for callback/toggle tasks)
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- Callbacks fire when inputs change
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- Metric toggles switch correctly
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- New tabs appear and render data
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### Validation Failure
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If any tier fails:
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- DO NOT mark the task complete
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- Document the failure in progress.txt
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- Fix the issue within this iteration if possible
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- If you cannot fix it, mark the task `[B]` with details
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## Quality Gates
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Before marking ANY task `[x]`, ALL of these must be true:
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1. Code is saved to the appropriate file(s)
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2. Tier 1 validation passed (imports + app starts)
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3. Tier 2/3 validation passed (as applicable)
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4. All changes committed to git with a descriptive message
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These are non-negotiable.
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## Update Progress
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After completing your work, append to progress.txt using this format:
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```
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## Iteration [N] — [YYYY-MM-DD]
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### Task: [which task you worked on]
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### Why this task:
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- [Brief explanation of why you chose this task over others]
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### Status: COMPLETE | BLOCKED | IN PROGRESS
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### What was done:
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- [Specific actions taken]
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### Validation results:
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- Tier 1 (Code): [import check, app starts]
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- Tier 2 (Visual): [chart renders, colors correct]
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- Tier 3 (Functional): [callbacks fire, toggles work]
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### Files changed:
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- [list of files created/modified]
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### Committed: [git hash] "[commit message]"
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### Patterns discovered:
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- [Any reusable learnings — Plotly quirks, layout gotchas, Dash patterns]
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### Next iteration should:
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- [Explicit guidance for what the next fresh instance should do first]
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- [Note any context that would be lost without writing it here]
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### Blocked items:
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- [Any tasks that are blocked and why]
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```
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If you discover a failure pattern, add it to `guardrails.md`.
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## Commit Changes
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1. Stage changed files
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2. Use a descriptive commit message referencing the task (e.g., "fix: heatmap colorscale + cell annotations (Task A.2)")
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3. Commit after your task is validated and complete
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4. If you updated progress.txt with a blocked status, commit that too
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## Completion Check
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If ALL tasks in IMPLEMENTATION_PLAN.md are marked `[x]`:
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1. Run `python run_dash.py` to verify app starts cleanly
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2. Verify all completion criteria at the bottom of IMPLEMENTATION_PLAN.md are satisfied
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3. Only then output the completion signal on its own line:
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```
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<promise>COMPLETE</promise>
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```
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DO NOT output this string under any other circumstances.
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DO NOT output it if any task is still `[ ]` or `[B]` or `[~]`.
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## Rules
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- Complete ONE task per iteration, then update progress and stop
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- ALWAYS read progress.txt, guardrails.md before starting work
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- **Read plotly_generator.py** when modifying ANY chart function (line numbers shift!)
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- **DO NOT modify pipeline/analysis logic** in src/ (pathway_pipeline, transforms, diagnosis_lookup, pathway_analyzer, refresh_pathways)
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- **DO add/modify** chart functions in `src/visualization/plotly_generator.py`
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- **DO add** new query functions in `src/data_processing/pathway_queries.py`
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- **New figure functions** go in `src/visualization/`, not in `dash_app/callbacks/`
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- **New query functions** go in `src/data_processing/pathway_queries.py` with thin wrappers in `dash_app/data/queries.py`
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- **dcc.Store for state** — no server-side globals
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- **Lazy tab rendering** — only compute the active tab's chart
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- Keep commits atomic and well-described
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- If stuck for 2+ attempts, document in progress.txt and move on
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- `python run_dash.py` must work after every task
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