Add developer usage examples

README.md

@@ -106,6 +106,7 @@ A step-by-step guide for integrating the dataset into your own application:
 exercises-dataset/
 ├── data/
 │   └── exercises.json       # Full dataset — 1,324 exercise records (JSON array)
+├── examples/                # Small Node, Python, and SQLite integration examples
 ├── images/                  # 1,324 × 180×180 thumbnails  (© Gym visual)
 ├── videos/                  # 1,324 × 180×180 animation GIFs  (© Gym visual)
 ├── index.html               # Interactive exercise browser (client-side, no server needed)
@@ -117,6 +118,7 @@ exercises-dataset/
 ### Key Files
 
 - **`data/exercises.json`** — The primary data file. A JSON array of 1,324 exercise objects with all metadata. `image` / `gif_url` point to the local 180×180 assets, and each record carries an `attribution` field; `media_id` holds the original media reference id.
+- **`examples/`** — Small integration examples for loading the dataset from Node.js, Python, and SQLite.
 - **`images/`, `videos/`** — 180×180 thumbnails and animation GIFs (© [Gym visual](https://gymvisual.com/), used with permission).
 - **`index.html`** — Standalone exercise browser. Open directly in any modern browser.
 - **`setup.html`** — Developer guide for DB setup, API integration, and LLM-assisted backend generation.

examples/node-load-dataset.mjs

@@ -0,0 +1,27 @@
+import fs from 'node:fs';
+import path from 'node:path';
+import { fileURLToPath } from 'node:url';
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = path.dirname(__filename);
+const dataPath = path.resolve(__dirname, '..', 'data', 'exercises.json');
+
+const exercises = JSON.parse(fs.readFileSync(dataPath, 'utf8'));
+
+const byBodyPart = exercises.reduce((counts, exercise) => {
+  counts[exercise.body_part] = (counts[exercise.body_part] ?? 0) + 1;
+  return counts;
+}, {});
+
+const bodyweight = exercises.filter((exercise) => exercise.equipment === 'body weight');
+
+console.log(`Total exercises: ${exercises.length}`);
+console.log(`Bodyweight exercises: ${bodyweight.length}`);
+console.log('Exercises by body part:');
+
+for (const [bodyPart, count] of Object.entries(byBodyPart).sort((a, b) => b[1] - a[1])) {
+  console.log(`- ${bodyPart}: ${count}`);
+}
+
+console.log('\nFirst exercise media attribution:');
+console.log(exercises[0].attribution);

examples/python-load-dataset.py

@@ -0,0 +1,27 @@
+import json
+from collections import Counter
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[1]
+DATA_PATH = ROOT / "data" / "exercises.json"
+
+
+with DATA_PATH.open(encoding="utf-8") as file:
+    exercises = json.load(file)
+
+by_body_part = Counter(exercise["body_part"] for exercise in exercises)
+bodyweight = [
+    exercise for exercise in exercises
+    if exercise["equipment"] == "body weight"
+]
+
+print(f"Total exercises: {len(exercises)}")
+print(f"Bodyweight exercises: {len(bodyweight)}")
+print("Exercises by body part:")
+
+for body_part, count in by_body_part.most_common():
+    print(f"- {body_part}: {count}")
+
+print("\nFirst exercise media attribution:")
+print(exercises[0]["attribution"])

examples/sqlite-import.md

@@ -0,0 +1,51 @@
+# SQLite import example
+
+The dataset can be imported into SQLite by storing multilingual instructions and secondary muscles as JSON text columns.
+
+## Minimal table
+
+```sql
+CREATE TABLE exercises (
+  id TEXT PRIMARY KEY,
+  name TEXT NOT NULL,
+  category TEXT,
+  body_part TEXT,
+  equipment TEXT,
+  instructions TEXT,
+  instruction_steps TEXT,
+  muscle_group TEXT,
+  secondary_muscles TEXT,
+  target TEXT,
+  image TEXT,
+  gif_url TEXT,
+  media_id TEXT,
+  created_at TEXT,
+  attribution TEXT
+);
+```
+
+## Generate INSERT statements
+
+Open `setup.html`, choose the SQLite tab, and click "Generate INSERT SQL". The generated file contains all 1,324 records and can be imported with:
+
+```bash
+sqlite3 exercises.db < exercises_insert_sqlite.sql
+```
+
+## Query examples
+
+```sql
+SELECT COUNT(*) FROM exercises;
+
+SELECT name, target, equipment
+FROM exercises
+WHERE equipment = 'body weight'
+ORDER BY name
+LIMIT 20;
+
+SELECT name, json_extract(instructions, '$.en') AS english_instructions
+FROM exercises
+WHERE id = '0001';
+```
+
+The media paths in `image` and `gif_url` point to files in this repository. Keep the `attribution` value with any exported records that include media references.