def generate_vegalite_channel_wrappers(schemafile, version, imports=None):
# TODO: generate __all__ for top of file
with open(schemafile, encoding='utf8') as f:
schema = json.load(f)
if imports is None:
imports = ["import six",
"from . import core",
"import pandas as pd",
"from altair.utils.schemapi import Undefined",
"from altair.utils import parse_shorthand"]
contents = [HEADER]
contents.extend(imports)
contents.append('')
contents.append(CHANNEL_MIXINS)
if version == 'v1':
encoding_def = 'Encoding'
elif version == 'v2':
encoding_def = 'EncodingWithFacet'
else:
encoding_def = 'FacetedEncoding'
encoding = SchemaInfo(schema['definitions'][encoding_def],
rootschema=schema)
for prop, propschema in encoding.properties.items():
if propschema.is_reference():
definitions = [propschema.ref]
elif propschema.is_anyOf():
definitions = [s.ref for s in propschema.anyOf if s.is_reference()]
else:
raise ValueError("either $ref or anyOf expected")
for definition in definitions:
defschema = {'$ref': definition}
basename = definition.split('/')[-1]
classname = prop.title()
if 'Value' in basename:
Generator = ValueSchemaGenerator
classname += 'Value'
nodefault = ['value']
else:
Generator = FieldSchemaGenerator
nodefault = []
defschema = copy.deepcopy(resolve_references(defschema, schema))
# For Encoding field definitions, we patch the schema by adding the
# shorthand property.
defschema['properties']['shorthand'] = {'type': 'string',
'description': 'shorthand for field, aggregate, and type'}
defschema['required'] = ['shorthand']
gen = Generator(classname=classname, basename=basename,
schema=defschema, rootschema=schema,
nodefault=nodefault)
contents.append(gen.schema_class())
return '\n'.join(contents)
def recursive_dict_update(schema, root, def_dict):
if "$ref" in schema:
next_schema = resolve_references(schema, root)
if "properties" in next_schema:
definition = schema["$ref"]
properties = next_schema["properties"]
for k in def_dict.keys():
if k in properties:
def_dict[k] = definition
else:
recursive_dict_update(next_schema, root, def_dict)
elif "anyOf" in schema:
for sub_schema in schema["anyOf"]:
recursive_dict_update(sub_schema, root, def_dict)
def generate_vegalite_channel_wrappers(schemafile, version, imports=None):
# TODO: generate __all__ for top of file
with open(schemafile, encoding="utf8") as f:
schema = json.load(f)
if imports is None:
imports = [
"from . import core",
"import pandas as pd",
"from altair.utils.schemapi import Undefined",
"from altair.utils import parse_shorthand",
]
contents = [HEADER]
contents.extend(imports)
contents.append("")
contents.append(CHANNEL_MIXINS)
if version == "v2":
encoding_def = "EncodingWithFacet"
else:
encoding_def = "FacetedEncoding"
encoding = SchemaInfo(schema["definitions"][encoding_def],
rootschema=schema)
for prop, propschema in encoding.properties.items():
if propschema.is_reference():
definitions = [propschema.ref]
elif propschema.is_anyOf():
definitions = [s.ref for s in propschema.anyOf if s.is_reference()]
else:
raise ValueError("either $ref or anyOf expected")
for definition in definitions:
defschema = {"$ref": definition}
basename = definition.split("/")[-1]
classname = prop[0].upper() + prop[1:]
if "Value" in basename:
Generator = ValueSchemaGenerator
classname += "Value"
nodefault = ["value"]
else:
Generator = FieldSchemaGenerator
nodefault = []
defschema = copy.deepcopy(resolve_references(
defschema, schema))
# For Encoding field definitions, we patch the schema by adding the
# shorthand property.
defschema["properties"]["shorthand"] = {
"type": "string",
"description": "shorthand for field, aggregate, and type",
}
defschema["required"] = ["shorthand"]
gen = Generator(
classname=classname,
basename=basename,
schema=defschema,
rootschema=schema,
encodingname=prop,
nodefault=nodefault,
)
contents.append(gen.schema_class())
return "\n".join(contents)