ljluestc commented on issue #28148:
URL: https://github.com/apache/superset/issues/28148#issuecomment-2726190195
```
import pandas as pd
from flask import Flask, jsonify
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import create_engine
# Initialize Flask app
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///pivot_data.db' # Use
SQLite for simplicity
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db = SQLAlchemy(app)
# Define a model for the pivot table data
class PivotData(db.Model):
__tablename__ = 'pivot_data'
id = db.Column(db.Integer, primary_key=True)
series = db.Column(db.String(50)) # e.g., "Puzzle"
metric = db.Column(db.String(50)) # e.g., "Sales", "Profit"
value = db.Column(db.Float) # Numeric value
# Simulate your data (replace with your actual data source)
def create_sample_data():
data = {
'series': ['Puzzle', 'Puzzle', 'Action', 'Action'],
'metric': ['Sales', 'Profit', 'Sales', 'Profit'],
'value': [100, 20, 150, 30]
}
df = pd.DataFrame(data)
# Sort by series first, then value descending within series
df = df.sort_values(by=['series', 'value'], ascending=[True, False])
return df
# Populate the database
def init_db():
db.drop_all()
db.create_all()
df = create_sample_data()
for _, row in df.iterrows():
entry = PivotData(series=row['series'], metric=row['metric'],
value=row['value'])
db.session.add(entry)
db.session.commit()
# Flask route to serve data (for debugging)
@app.route('/data', methods=['GET'])
def get_data():
data = PivotData.query.all()
result = [{'series': d.series, 'metric': d.metric, 'value': d.value} for
d in data]
return jsonify(result)
if __name__ == '__main__':
with app.app_context():
init_db() # Initialize database with sorted data
app.run(debug=True, host='0.0.0.0', port=5000)
```
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