thechandanbhagat/claude-skills/json

# Pretty print
cat data.json | jq '.'
 
# Select field
cat data.json | jq '.users[0].name'
 
# Filter arrays
cat data.json | jq '.users[] | select(.age > 18)'
 
# Map transformation
cat data.json | jq '.users[] | {name, email}'
 
# Count elements
cat data.json | jq '.users | length'

import json
import jsonschema
schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "number", "minimum": 0}
    },
    "required": ["name", "age"]
}
data = {"name": "John", "age": 30}
jsonschema.validate(instance=data, schema=schema)

# Rename keys
jq '.users[] | {fullName: .name, emailAddress: .email}'
 
# Flatten nested structure
jq '[.users[] | {name, city: .address.city}]'
 
# Group by
jq 'group_by(.category) | map({category: .[0].category, items: .})'
 
# Merge objects
jq '. + {newField: "value"}'

jq -r '.[] | [.name, .email, .age] | @csv' data.json > output.csv

python -c "import json, yaml; print(yaml.dump(json.load(open('data.json'))))"