Dev

.github/workflows/docker-build.yml

@@ -15,7 +15,7 @@ on:
 
 env:
   DOCKER_IMAGE: xatang/pyunit
-  PLATFORMS: linux/amd64,linux/arm64
+  PLATFORMS: linux/amd64,linux/arm64,linux/arm/v7,linux/arm/v8
 
 jobs:
   build-and-push:

.gitignore

@@ -11,6 +11,8 @@ env/
 
 # Database
 *.db
+*.db-wal
+*.db-shm
 *.sqlite
 *.sqlite3
 

README.md

@@ -22,9 +22,9 @@ PyUnit is a custom firmware for [iDryer Unit](https://github.com/pavluchenkor/iD
 - 🔗 **WebSocket real-time updates**
 - 📋 **Embed pages** for Klipper HTTP camera integration
 - 🤖 **G-code macro generation** for Klipper
-- 🐳 **Multi-platform Docker images** (amd64, arm64)
+- 🐳 **Multi-platform Docker images** (amd64, arm64, arm/v7, arm/v8)
 
-## � Screenshots
+## 📸 Screenshots
 
 ### Dashboard Overview
 ![Dashboard](images/dashboard.png)
@@ -42,7 +42,7 @@ PyUnit is a custom firmware for [iDryer Unit](https://github.com/pavluchenkor/iD
 ![Fluidd Integration](images/fluidd-integration.png)
 *PyUnit embedded control panel in Fluidd/Mainsail interface*
 
-## � Quick Start
+## 🚀 Quick Start
 
 ### One-Command Installation
 
@@ -67,10 +67,21 @@ The script will automatically:
 ### Requirements
 
 - **OS:** Linux (Ubuntu, Debian, Raspbian, Armbian)
-- **Architecture:** amd64 (x86_64) or arm64 (aarch64)
+- **Architecture:** 
+  - amd64 (x86_64) - Intel/AMD 64-bit
+  - arm64 (aarch64) - ARM 64-bit
+  - arm/v7 - ARMv7 32-bit
+  - arm/v8 - ARMv8 32-bit
 - **RAM:** 256MB minimum (512MB recommended)
 - **Disk:** ~1GB for Docker image
 
+#### Additionally, you can add the following commands to the Fluidd or Mainsail console filters to avoid a flood of messages during firmware operation.
+```bash
+SET_LED LED=[led_name] INDEX=
+SET_HEATER_TEMPERATURE HEATER=[heater_name]
+SET_SERVO SERVO=[servo_name]
+```
+
 ### Updates
 
 To update to the latest version:
@@ -80,8 +91,30 @@ cd PyUnit
 ./run.sh
 ```
 
+
 Updates preserve your configuration and IP settings automatically.
 
+### Uninstallation
+
+To completely remove PyUnit (container, volumes, images, network):
+
+```bash
+cd PyUnit
+chmod +x uninstall.sh
+./uninstall.sh
+```
+
+This will remove:
+- Docker container `pyunit`
+- Docker volume `pyunit_pyunit_data` (all data will be lost!)
+- Docker network `pyunit_pyunit_network`
+- Docker images `xatang/pyunit:*`
+
+**Note:** Local files (pyunit.db, logs) are NOT deleted automatically. To remove them:
+```bash
+rm -f pyunit.db pyunit.db-wal pyunit.db-shm app.log dryer.log
+```
+
 ## 🏗️ Architecture
 
 ### Backend (FastAPI + Python 3.11)
@@ -179,7 +212,7 @@ sudo docker compose up -d
 **Starting a Drying Cycle:**
 1. Select a dryer from the list
 2. Choose a preset
-3. Click **Start** - the dryer will
+3. Click **Start** - the dryer will begin the drying process
 
 ### Configuration
 
@@ -193,12 +226,26 @@ sudo docker compose up -d
 
 ### Klipper Integration
 
+**Example Configuration:**
+
+A complete Klipper configuration example is available in `config_and_macros/U1.cfg.example`. This file contains:
+- Heater configuration (`[heater_generic]`)
+- Temperature sensor setup (`[temperature_sensor]`)
+- LED control (`[neopixel]`)
+- Servo configuration (`[servo]`)
+- G-code macros for dryer control
+
+**⚠️ Important:** All module and sensor names in Klipper configuration **must be lowercase**:
+- ✅ Correct: `idryer_u1_heater`, `idryer_u1_air`, `srv_u1`
+- ❌ Wrong: `IDryer_U1_Heater`, `IDRYER_U1_AIR`, `SRV_U1`
+
 **G-code Macros:**
-1. Go to dryer detail page
-2. Expand **Klipper G-code Macros**
-3. Configure Python script path
-4. Copy macros to `printer.cfg`
-5. Use in Klipper:
+1. To control the drying process via gcode macro, your printer must have the [gcode_shell_command](https://github.com/dw-0/kiauh/blob/master/docs/gcode_shell_command.md) extension installed.
+2. After installation gcode_shell_command go to dryer detail page
+3. Expand **Klipper G-code Macros**
+4. Configure Python script path
+5. Copy macros to `printer.cfg`
+6. Use in Klipper:
    ```gcode
    OFF_DRYER ID=1
    PRESET_DRYER ID=1 PRESET_ID=5
@@ -212,13 +259,13 @@ sudo docker compose up -d
    [camera pyunit_control]
    location: dryer
    service: http
-   target_fps: 15
+   aspect_ratio: 4:3
    stream_url: http://192.168.1.100:5000/embed/dryer/1/control
 
    [camera pyunit_chart]
    location: dryer
    service: http  
-   target_fps: 15
+   aspect_ratio: 4:3
    stream_url: http://192.168.1.100:5000/embed/dryer/1/chart
    ```
 

api/cruds/dryer_crud.py

@@ -160,11 +160,50 @@ async def add_log(self, db: AsyncSession, log_data: schema.DryerLog) -> models.D
         await db.refresh(db_log)
         return schema.DryerLog.from_orm(db_log) if db_log else None
 
-    async def get_logs(self, db: AsyncSession) -> list[models.DryerLogs]:
-        """Return all dryer logs (no filtering)."""
-        result = await db.execute(select(models.DryerLogs))
+    async def get_logs(self, db: AsyncSession, dryer_id: Optional[int] = None, 
+                       start_time: Optional[str] = None, end_time: Optional[str] = None,
+                       limit: Optional[int] = None) -> list[models.DryerLogs]:
+        """Return dryer logs with optional filtering.
+
+        Args:
+            db: Database session
+            dryer_id: Filter by specific dryer (None = all dryers)
+            start_time: ISO format datetime string for filtering logs after this time
+            end_time: ISO format datetime string for filtering logs before this time
+            limit: Maximum number of logs to return (most recent first)
+        """
+        query = select(models.DryerLogs)
+
+        if dryer_id is not None:
+            query = query.where(models.DryerLogs.dryer_id == dryer_id)
+
+        if start_time:
+            from datetime import datetime
+            start_dt = datetime.fromisoformat(start_time.replace('Z', '+00:00'))
+            query = query.where(models.DryerLogs.timestamp >= start_dt)
+
+        if end_time:
+            from datetime import datetime
+            end_dt = datetime.fromisoformat(end_time.replace('Z', '+00:00'))
+            query = query.where(models.DryerLogs.timestamp <= end_dt)
+
+        # Order by timestamp descending (most recent first)
+        query = query.order_by(models.DryerLogs.timestamp.desc())
+
+        if limit:
+            query = query.limit(limit)
+
+        result = await db.execute(query)
         db_logs = result.scalars().all()
-        return [schema.DryerLog.from_orm(log) for log in db_logs] if db_logs else None
+
+        # Return in chronological order (oldest first) for historical data
+        logs_list = [schema.DryerLog.from_orm(log) for log in reversed(db_logs)] if db_logs else []
+
+        if dryer_id:
+            logger.debug("get_logs dryer_id=%s start=%s end=%s limit=%s returned=%d", 
+                        dryer_id, start_time, end_time, limit, len(logs_list))
+
+        return logs_list
 
 
 dryer_crud = DryerCRUD()

api/database.py

@@ -11,6 +11,7 @@
 
 from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
 from sqlalchemy.orm import sessionmaker
+from sqlalchemy import text, event
 from api.models import Base, Preset, MoonrakerConfig
 import subprocess
 from api.logger import get_logger
@@ -25,9 +26,36 @@
 engine = create_async_engine(
     DATABASE_URL,
     echo=False,
-    future=True
+    future=True,
+    connect_args={
+        "timeout": 30,  # Increase timeout for lock acquisition (default is 5)
+        "check_same_thread": False  # Allow multi-threaded access
+    },
+    pool_pre_ping=True,  # Verify connections before use
+    pool_size=10,  # Increase connection pool size
+    max_overflow=20  # Allow more overflow connections
 )
 
+# Configure SQLite PRAGMA settings for each connection
+@event.listens_for(engine.sync_engine, "connect")
+def set_sqlite_pragma(dbapi_conn, connection_record):
+    """Apply SQLite optimizations on each new connection.
+
+    Critical for Orange Pi / SD card deployments:
+    - WAL mode: allows concurrent reads during writes
+    - synchronous=NORMAL: safe with WAL, much faster on slow storage
+    - cache_size: reduces SD card access
+    - temp_store: keeps temp data in RAM
+    """
+    cursor = dbapi_conn.cursor()
+    cursor.execute("PRAGMA journal_mode=WAL")
+    cursor.execute("PRAGMA busy_timeout=30000")  # 30 second timeout
+    cursor.execute("PRAGMA synchronous=NORMAL")  # Trade durability for speed (safe with WAL)
+    cursor.execute("PRAGMA cache_size=-64000")  # 64MB cache (negative = KB)
+    cursor.execute("PRAGMA temp_store=MEMORY")  # Keep temp tables in RAM
+    cursor.close()
+    db_logger.debug("SQLite PRAGMAs applied to new connection")
+
 # Reduce SQLAlchemy internal logger verbosity
 for _name in [
     'sqlalchemy.engine',
@@ -91,7 +119,10 @@ def run_migrations():
 
 
 async def init_db():
-    """Create tables based on current SQLAlchemy metadata (non-destructive)."""
+    """Create tables based on current SQLAlchemy metadata (non-destructive).
+
+    Note: PRAGMA settings are now applied automatically via engine.connect event.
+    """
     async with engine.begin() as conn:
         await conn.run_sync(Base.metadata.create_all)
     db_logger.info("Database schema ensured (create_all)")

api/endpoints/common.py

@@ -67,9 +67,24 @@ async def ws_info():
         {
             "path": "/api/dashboard/dryers",
             "channel": "dryers_stats",
-            "purpose": "Historical + live dryer state updates (JSON objects)",
+            "purpose": "DEPRECATED: Historical + live dryer state updates for ALL dryers (JSON objects). Use /dashboard/dryer/{id} for better performance.",
             "client_send": "ignored (reserved for future commands)",
-            "server_send_example": {"history": [{"id": 1, "status": "DRYING"}]}
+            "server_send_example": {"history": [{"id": 1, "dryer_id": 1, "status": "drying", "temperature": 45.5}]},
+            "deprecated": True,
+            "replacement": "/api/dashboard/dryer/{dryer_id}"
+        },
+        {
+            "path": "/api/dashboard/dryer/{dryer_id}",
+            "channel": "dryer_{dryer_id}_stats",
+            "purpose": "RECOMMENDED: Optimized historical + live updates for a SINGLE dryer (JSON objects)",
+            "query_params": {
+                "start_time": "ISO datetime string (e.g., 2025-12-18T10:00:00Z) - filter logs after this time",
+                "end_time": "ISO datetime string - filter logs before this time",
+                "limit": "Maximum number of historical logs to load (default: 100, prevents memory issues)"
+            },
+            "client_send": "ignored (reserved for future commands)",
+            "server_send_example": {"history": [{"id": 1, "dryer_id": 1, "status": "drying", "temperature": 45.5, "timestamp": "2025-12-18T12:00:00Z"}]},
+            "benefits": "500x less data on connection, time-based filtering, single dryer focus"
         }
     ]
     logger.debug("GET /common/ws-info return %d channels", len(websockets))