machi1990

#!/usr/bin/env python3
"""
Violin Plot Distribution Analysis for ARO-HCP Upgrades

Generates version activation time distribution visualization using violin plots
to show the full distribution of data.

Outliers removed using IQR (Interquartile Range) method - standard statistical approach.
"""

machi1990

#!/usr/bin/env python3
"""
Comprehensive ARO-HCP Upgrade Analysis Visualization Script

This script generates three key visualizations from ARO-HCP upgrade data:

1. STACKED PHASE DURATION GRAPH (upgrade_phases_stacked_by_week.png)
   - Shows breakdown of time spent in each upgrade phase by week
   - Phases: Creation→Backend, Backend Selection, Backend→CS Pickup,
            CS Pickup→Trigger, Hypershift Reaction

machi1990

#!/usr/bin/env python3
"""
Time from cluster creation to backend upgrade decision
Combines all findings into one complete view
"""

import json
import matplotlib.pyplot as plt
import numpy as np
from pathlib import Path

machi1990

#!/usr/bin/env python3
"""
Create separate cluster upgrade analysis graphs for each cluster
"""
import json
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from datetime import datetime

machi1990

const { typeDefs, resolvers, contextCreator, services } = buildGraphbackAPI(schema, {
  dataProviderCreator: createKnexDbProvider(dbConfig),
  plugins: []
});

const apolloServer = new ApolloServer({
  typeDefs,
  resolvers,
  context: contextCreator
})

machi1990

"""
@oneToOne key: 'user_id'
"""

machi1990

"""
@oneToOne(key: 'user_id')
"""