Genson

https://github.com/wolverdude/genson
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### Install GenSON using pip

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This command installs the GenSON library using pip, the Python package installer. Ensure you have Python and pip installed on your system.

```bash
pip install genson
```

--------------------------------

### GenSON CLI Usage Example

Source: https://github.com/wolverdude/genson/blob/master/README.rst

An example of the GenSON CLI usage, showing the command structure for generating a unified JSON Schema from multiple JSON objects or schemas. It details positional and optional arguments for file input, delimiters, encoding, indentation, and schema URIs.

```bash
usage: genson [-h] [--version] [-d DELIM] [-e ENCODING] [-i SPACES]
              [-s SCHEMA] [-$ SCHEMA_URI]
    ...

Generate one, unified JSON Schema from one or more JSON objects and/or JSON
Schemas. Compatible with JSON-Schema Draft 4 and above.

positional arguments:
  object                Files containing JSON objects (defaults to stdin if no
                        arguments are passed).

optional arguments:
  -h, --help            Show this help message and exit.
  --version             Show version number and exit.
  -d DELIM, --delimiter DELIM
                        Set a delimiter. Use this option if the input files
                        contain multiple JSON objects/schemas. You can pass
                        any string. A few cases ('newline', 'tab', 'space')
                        will get converted to a whitespace character. If this
                        option is omitted, the parser will try to auto-detect
                        boundaries.
  -e ENCODING, --encoding ENCODING
                        Use ENCODING instead of the default system encoding
                        when reading files. ENCODING must be a valid codec
                        name or alias.
  -i SPACES, --indent SPACES
                        Pretty-print the output, indenting SPACES spaces.
  -s SCHEMA, --schema SCHEMA
                        File containing a JSON Schema (can be specified
                        multiple times to merge schemas).
  -$ SCHEMA_URI, --schema-uri SCHEMA_URI
                        The value of the '$schema' keyword (defaults to
                        'http://json-schema.org/schema#' or can be specified
                        in a schema with the -s option). If 'NULL' is passed,
                        the "$schema" keyword will not be included in the
                        result.
```

--------------------------------

### Python - MinNumberSchemaBuilder Usage Example

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Demonstrates the usage of the custom MinNumberSchemaBuilder by adding objects and generating a schema. It shows how the 'minimum' keyword is correctly included in the output schema.

```python
>>> builder = MinNumberSchemaBuilder()
>>> builder.add_object(5)
>>> builder.add_object(7)
>>> builder.to_schema()
{'$schema': 'http://json-schema.org/schema#', 'type': 'integer', 'minimum': 5}
>>> builder.add_object(-2)
>>> builder.to_schema()
{'$schema': 'http://json-schema.org/schema#', 'type': 'integer', 'minimum': -2}
```

--------------------------------

### Generate JSON Schema from File with Genson CLI

Source: https://context7.com/wolverdude/genson/llms.txt

Provides examples of using the Genson command-line interface to generate JSON schemas. The basic usage involves specifying a JSON file as input. Options are available for pretty-printing the output with indentation, handling multiple JSON objects separated by delimiters (like newlines), merging schemas from multiple files, and starting the generation process with an existing schema file.

```bash
# Generate schema from JSON file
echo '{"name": "Alice", "age": 30}' > person.json
genson person.json

# Output:
# {
#   "$schema": "http://json-schema.org/schema#",
#   "type": "object",
#   "properties": {
#     "name": {"type": "string"},
#     "age": {"type": "integer"}
#   },
#   "required": ["name", "age"]
# }

# Pretty-print with indentation
genson person.json -i 2

# Multiple JSON objects with delimiter
cat <<EOF > data.json
{"id": 1, "active": true}
{"id": 2, "active": false}
EOF
genson data.json -d newline

# Merge multiple files
genson file1.json file2.json file3.json -i 2

# Start with existing schema and add objects
genson -s existing-schema.json new-data.json

```

--------------------------------

### Run Tests with Tox (Bash)

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This command executes the test suite using Tox, which is a tool for automating Python testing. Tox will run tests against all supported Python versions installed on the machine and report coverage.

```bash
$ tox
```

--------------------------------

### Compare Schema Equality with Genson SchemaBuilder

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This Python example illustrates how to compare two SchemaBuilder objects for equality. It shows how schemas are merged when added to each other and how equality is determined based on their content.

```python
from genson import SchemaBuilder

b1 = SchemaBuilder()
b1.add_schema({"type": "object", "properties": {
  "hi": {"type": "string"}}})
b2 = SchemaBuilder()
b2.add_schema({"type": "object", "properties": {
  "hi": {"type": "integer"}}})
b1 == b2

b1.add_schema(b2)
b2.add_schema(b1)
b1 == b2
b1.to_schema()
```

--------------------------------

### GenSON Python API: SchemaBuilder Initialization and Object Addition

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Demonstrates how to initialize a SchemaBuilder object from the GenSON library and add JSON objects to it. The builder infers the schema based on the provided objects. This is the basic setup for schema generation in Python.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()

# Add some objects to infer their schema.
builder.add_object({"hi": "there"})
builder.add_object({"hi": 5})
```

--------------------------------

### Using patternProperties with GenSON in Python

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Demonstrates how to utilize the `patternProperties` keyword in GenSON for object schemas. This feature requires `patternProperties` to be defined in a seed schema. The example shows adding a schema with a regex pattern and then adding objects that conform to this pattern.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()
builder.add_schema({'type': 'object', 'patternProperties': {r'^\d+$': None}})
builder.add_object({'1': 1, '2': 2, '3': 3})
print(builder.to_schema())
```

--------------------------------

### Generate Array Tuple Validation Schema with Genson using Seed

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This Python example shows how to influence Genson's schema generation for arrays by providing a seed schema. By seeding with an empty array for `items`, Genson generates a schema for tuple validation, where each position has a specific type.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()
seed_schema = {'type': 'array', 'items': []}
builder.add_schema(seed_schema)
builder.add_object(['one', 1])
builder.to_schema()
```

--------------------------------

### Custom Number Schema Strategy in Genson Python

Source: https://context7.com/wolverdude/genson/llms.txt

Details how to implement a custom schema strategy in Genson, specifically for tracking the minimum value of numbers. This involves subclassing `genson.schema.strategies.Number`, overriding methods like `add_schema` and `add_object` to incorporate custom logic, and defining `EXTRA_STRATEGIES` in a custom SchemaBuilder. The example shows a builder that generates schemas with a 'minimum' keyword.

```python
from genson import SchemaBuilder
from genson.schema.strategies import Number

# Define custom strategy tracking minimum value
class MinNumber(Number):
    KEYWORDS = (*Number.KEYWORDS, 'minimum')

    def __init__(self, node_class):
        super().__init__(node_class)
        self.min = None

    def add_schema(self, schema):
        super().add_schema(schema)
        if self.min is None:
            self.min = schema.get('minimum')
        elif 'minimum' in schema:
            self.min = min(self.min, schema['minimum'])

    def add_object(self, obj):
        super().add_object(obj)
        self.min = obj if self.min is None else min(self.min, obj)

    def to_schema(self):
        schema = super().to_schema()
        if self.min is not None:
            schema['minimum'] = self.min
        return schema

# Create custom builder class
class MinNumberSchemaBuilder(SchemaBuilder):
    EXTRA_STRATEGIES = (MinNumber,)

# Use custom builder
builder = MinNumberSchemaBuilder()
builder.add_object(5)
builder.add_object(10)
builder.add_object(3)
schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'integer',
#   'minimum': 3
# }

# Minimum updates with new values
builder.add_object(1)
schema = builder.to_schema()
print(schema['minimum'])
# Output: 1
```

--------------------------------

### GenSON CLI Help

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Displays the help message for the GenSON command-line interface. This shows available options for generating JSON schemas from objects and schemas.

```bash
genson --help
```

--------------------------------

### Build and Export JSON Schema with Genson

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This Python snippet demonstrates how to use the SchemaBuilder to create a JSON schema from an object and then export it as a formatted JSON string. It shows the initial schema and the final exported schema after processing.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()
builder.add_object({
    "type": "object",
    "properties": {
        "hi": {"type": "boolean"}
    }
})

# Export the schema as a JSON string.
print(builder.to_json(indent=2))
```

--------------------------------

### Build JSON Schema with MinNumberSchemaBuilder (Python)

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Demonstrates how to use MinNumberSchemaBuilder and ExclusiveMinNumberSchemaBuilder to construct JSON schemas. The ExclusiveMinNumberSchemaBuilder has stricter validation and will raise an error if None is added.

```python
>>> builder = MinNumberSchemaBuilder()
>>> picky_builder = ExclusiveMinNumberSchemaBuilder()
>>> picky_builder.add_object(5)
>>> picky_builder.to_schema()
{'$schema': 'http://json-schema.org/schema#', 'type': 'integer', 'minimum': 5}
>>> builder.add_object(None) # this is fine
>>> picky_builder.add_object(None) # this fails
genson.schema.node.SchemaGenerationError: Could not find matching schema type for object: None
```

--------------------------------

### GenSON Python API: Merging Schemas

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Illustrates how to merge an existing JSON schema into the SchemaBuilder. This allows GenSON to create a unified schema from multiple sources, including pre-defined schemas.

```python
# Merge in another schema.
builder.add_schema({

```

--------------------------------

### Generate JSON Schema from Python Objects

Source: https://context7.com/wolverdude/genson/llms.txt

Demonstrates basic JSON Schema generation by adding multiple Python dictionaries to a SchemaBuilder and then converting it to a JSON Schema. This is useful for inferring a schema from existing data.

```python
from genson import SchemaBuilder

# Create a builder and add objects
builder = SchemaBuilder()
builder.add_object({"name": "Alice", "age": 30})
builder.add_object({"name": "Bob", "age": 25})

# Generate schema
schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'properties': {
#     'name': {'type': 'string'},
#     'age': {'type': 'integer'}
#   },
#   'required': ['name', 'age']
# }
```

--------------------------------

### Evolve Schema Types for Evolving Data

Source: https://context7.com/wolverdude/genson/llms.txt

Shows how GenSON handles properties with different data types across multiple objects by creating a schema that accommodates all observed types. This is crucial when data schemas are not strictly enforced.

```python
from genson import SchemaBuilder

# Add objects with different types for same property
builder = SchemaBuilder()
builder.add_object({"value": 42})
builder.add_object({"value": "hello"})
builder.add_object({"value": True})

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'properties': {
#     'value': {'type': ['boolean', 'integer', 'string']}
#   },
#   'required': ['value']
# }
```

--------------------------------

### Merge Multiple JSON Schemas

Source: https://context7.com/wolverdude/genson/llms.txt

Illustrates how to combine existing JSON Schemas into a single, comprehensive schema using GenSON's SchemaBuilder. It demonstrates merging schemas with differing required properties, resulting in a schema that satisfies all inputs.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()

# Add first schema
builder.add_schema({
    "type": "object",
    "properties": {
        "id": {"type": "integer"},
        "name": {"type": "string"}
    },
    "required": ["id"]
})

# Add second schema
builder.add_schema({
    "type": "object",
    "properties": {
        "id": {"type": "integer"},
        "email": {"type": "string"}
    },
    "required": ["id", "email"]
})

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'properties': {
#     'id': {'type': 'integer'},
#     'name': {'type': 'string'},
#     'email': {'type': 'string'}
#   },
#   'required': ['id']  # Only 'id' is required in both
# }
```

--------------------------------

### Read JSON Schema from Stdin with GenSON

Source: https://context7.com/wolverdude/genson/llms.txt

This command reads JSON data from standard input and generates a JSON Schema using GenSON. It's useful for piping data directly into the schema generation process.

```bash
echo '{"test": 123}' | genson
```

--------------------------------

### Generate JSON Schema with Custom URI using GenSON

Source: https://context7.com/wolverdude/genson/llms.txt

This command generates a JSON Schema from a file named 'data.json' and sets a custom schema URI. The URI is specified after the filename.

```bash
genson data.json -$ "http://json-schema.org/draft-07/schema#"
```

--------------------------------

### Python - Custom MinNumber Schema Strategy

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Extends the Number schema strategy to track and include the minimum number encountered in the generated schema. It overrides add_schema, add_object, and to_schema methods, and defines the KEYWORDS class constant.

```python
from genson import SchemaBuilder
from genson.schema.strategies import Number

class MinNumber(Number):
    # add 'minimum' to list of keywords
    KEYWORDS = (*Number.KEYWORDS, 'minimum')

    # create a new instance variable
    def __init__(self, node_class):
        super().__init__(node_class)
        self.min = None

    # capture 'minimum's from schemas
    def add_schema(self, schema):
        super().add_schema(schema)
        if self.min is None:
            self.min = schema.get('minimum')
        elif 'minimum' in schema:
            self.min = min(self.min, schema['minimum'])

    # adjust minimum based on the data
    def add_object(self, obj):
        super().add_object(obj)
        self.min = obj if self.min is None else min(self.min, obj)

    # include 'minimum' in the output
    def to_schema(self):
        schema = super().to_schema()
        schema['minimum'] = self.min
        return schema
```

--------------------------------

### Generate Array Schema (Tuple Mode)

Source: https://context7.com/wolverdude/genson/llms.txt

Demonstrates generating an array schema in tuple mode, where each element in the array has its own distinct schema. This is achieved by seeding the builder with an empty array schema.

```python
from genson import SchemaBuilder

# Use seed schema for tuple mode - each position has different schema
builder = SchemaBuilder()
builder.add_schema({'type': 'array', 'items': []})
builder.add_object(['Alice', 30, True])
builder.add_object(['Bob', 25, False])

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'array',
#   'items': [
#     {'type': 'string'},
#     {'type': 'integer'},
#     {'type': 'boolean'}
#   ]
# }
```

--------------------------------

### Compare and Merge JSON Schemas with Genson Python

Source: https://context7.com/wolverdude/genson/llms.txt

Illustrates how to compare SchemaBuilder instances for equality and merge schemas. Builders with identical structures are considered equal. The `add_schema` method allows merging another builder's schema into the current one, combining properties and updating required fields. This is useful for building a schema from distributed data sources.

```python
from genson import SchemaBuilder

# Create two builders
builder1 = SchemaBuilder()
builder1.add_object({"name": "Alice", "age": 30})

builder2 = SchemaBuilder()
builder2.add_object({"name": "Bob", "age": 25})

# Builders with same structure are equal
print(builder1 == builder2)
# Output: True

# Merge one builder into another
builder3 = SchemaBuilder()
builder3.add_object({"name": "Charlie", "active": True})

builder1.add_schema(builder3)
schema = builder1.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'properties': {
#     'name': {'type': 'string'},
#     'age': {'type': 'integer'},
#     'active': {'type': 'boolean'}
#   },
#   'required': ['name']  # Only 'name' is in all objects
# }
```

--------------------------------

### GenSON Python API: Exporting Schema

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Shows how to export the generated JSON schema from a SchemaBuilder object as a Python dictionary. This method serializes the inferred schema structure.

```python
# Export the schema as a Python dict.
builder.to_schema()
{"$schema": "http://json-schema.org/schema#",
 "type": "object",
 "properties": {
    "hi": {"type": ["integer", "string"]}},
    "required": ["hi"]}
```

--------------------------------

### Python - SchemaBuilder with Extra Strategies

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Extends the base SchemaBuilder to include custom strategies without replacing existing ones. The EXTRA_STRATEGIES class constant is used to add new strategies, which have higher priority than default strategies.

```python
# new SchemaBuilder class that uses the MinNumber strategy in addition
# to the existing strategies. Both MinNumber and Number are active, but
# MinNumber has priority, so it effectively replaces Number.
class MinNumberSchemaBuilder(SchemaBuilder):
    """ all number nodes include minimum """
    EXTRA_STRATEGIES = (MinNumber,)
```

--------------------------------

### Generate Schema with Pattern Properties

Source: https://context7.com/wolverdude/genson/llms.txt

Explains how to generate JSON Schema that includes 'patternProperties' for keys matching a regular expression. This is useful for objects with dynamically named keys, like those containing numeric strings.

```python
from genson import SchemaBuilder
import re

# Use seed schema to enable patternProperties
builder = SchemaBuilder()
builder.add_schema({
    'type': 'object',
    'patternProperties': {r'^\d+$': None}
})

# Add objects with numeric string keys
builder.add_object({'1': 100, '2': 200, '3': 300})
builder.add_object({'10': 1000, '20': 2000})

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'patternProperties': {
#     '^\d+$': {'type': 'integer'}
#   }
# }
```

--------------------------------

### Generate JSON Schema from Multi-Object File with Custom Delimiter

Source: https://context7.com/wolverdude/genson/llms.txt

This command generates a JSON Schema from a file containing multiple JSON objects separated by a custom delimiter ('---'). The '-i 2' option likely specifies the indentation level for the output schema.

```bash
genson multi-object-file.json -d "---" -i 2
```

--------------------------------

### Generate Array Schema (List Mode)

Source: https://context7.com/wolverdude/genson/llms.txt

Shows how GenSON generates a schema for arrays where all elements are expected to conform to a single schema. This is the default behavior when adding array objects.

```python
from genson import SchemaBuilder

# Default list mode - all items share one schema
builder = SchemaBuilder()
builder.add_object([1, 2, 3, 4, 5])
builder.add_object([10, 20, 30])

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'array',
#   'items': {'type': 'integer'}
# }

# Mixed types in array
builder2 = SchemaBuilder()
builder2.add_object([1, "two", 3.0, True])
schema2 = builder2.to_schema()
print(schema2)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'array',
#   'items': {'type': ['boolean', 'integer', 'number', 'string']}
# }
```

--------------------------------

### Python - SchemaBuilder with Exclusive Strategies

Source: https://github.com/wolverdude/genson/blob/master/README.rst

Extends the base SchemaBuilder to completely replace the default strategies with a custom set. The STRATEGIES class constant is used for this purpose, making the builder handle only the specified strategies.

```python
# this class *ONLY* has the MinNumber strategy. Any object that is not
# a number will cause an error.
class ExclusiveMinNumberSchemaBuilder(SchemaBuilder):
    """ all number nodes include minimum, and only handles number """
    STRATEGIES = (MinNumber,)
```

--------------------------------

### Generate JSON Schema without Schema URI Keyword using GenSON

Source: https://context7.com/wolverdude/genson/llms.txt

This command generates a JSON Schema from 'data.json' but explicitly sets the schema URI keyword to NULL, effectively omitting it from the generated schema.

```bash
genson data.json -$ NULL
```

--------------------------------

### Generate Array List Validation Schema with Genson

Source: https://github.com/wolverdude/genson/blob/master/README.rst

This Python code demonstrates the default behavior of Genson when adding an array object, which is to generate a schema for list validation. The `items` keyword specifies a union of types for all elements in the array.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()
builder.add_object(['one', 1])
builder.to_schema()
```

--------------------------------

### Generate Nested Object JSON Schema with Genson Python

Source: https://context7.com/wolverdude/genson/llms.txt

Demonstrates how to use Genson's SchemaBuilder to generate a JSON schema from a nested Python dictionary. The builder processes the object and outputs a schema reflecting its structure, types, and required fields. This is useful for validating JSON data with complex, nested structures.

```python
from genson import SchemaBuilder

builder = SchemaBuilder()
builder.add_object({
    "user": {
        "profile": {
            "name": "Alice",
            "age": 30
        },
        "posts": [
            {"title": "Hello", "views": 100},
            {"title": "World", "views": 200}
        ]
    }
})

schema = builder.to_schema()
print(schema)
# Output:
# {
#   '$schema': 'http://json-schema.org/schema#',
#   'type': 'object',
#   'properties': {
#     'user': {
#       'type': 'object',
#       'properties': {
#         'profile': {
#           'type': 'object',
#           'properties': {
#             'name': {'type': 'string'},
#             'age': {'type': 'integer'}
#           },
#           'required': ['name', 'age']
#         },
#         'posts': {
#           'type': 'array',
#           'items': {
#             'type': 'object',
#             'properties': {
#               'title': {'type': 'string'},
#               'views': {'type': 'integer'}
#             },
#             'required': ['title', 'views']
#           }
#         }
#       },
#       'required': ['profile', 'posts']
#     }
#   },
#   'required': ['user']
# }
```

--------------------------------

### Control JSON Schema URI with Genson Python

Source: https://context7.com/wolverdude/genson/llms.txt

Shows how to control the '$schema' URI in generated JSON schemas using Genson. You can use the default URI, specify a custom one (e.g., for Draft 7), or omit it entirely by setting `schema_uri` to `None` during SchemaBuilder initialization. This allows compatibility with different JSON schema validators.

```python
from genson import SchemaBuilder

# Default schema URI
builder = SchemaBuilder()
builder.add_object({"id": 1})
json_output = builder.to_json(indent=2)
print(json_output)
# Output:
# {
#   "$schema": "http://json-schema.org/schema#",
#   "type": "object",
#   "properties": {
#     "id": {
#       "type": "integer"
#     }
#   },
#   "required": [
#     "id"
#   ]
# }

# Custom schema URI
builder2 = SchemaBuilder(schema_uri='http://json-schema.org/draft-07/schema#')
builder2.add_object({"id": 1})
schema2 = builder2.to_schema()
print(schema2['$schema'])
# Output: 'http://json-schema.org/draft-07/schema#'

# No schema URI
builder3 = SchemaBuilder(schema_uri=None)
builder3.add_object({"id": 1})
schema3 = builder3.to_schema()
print('$schema' in schema3)
# Output: False
```
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