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Editing: schema.py
"""schema is a library for validating Python data structures, such as those obtained from config-files, forms, external services or command-line parsing, converted from JSON/YAML (or something else) to Python data-types.""" import inspect import re try: from contextlib import ExitStack except ImportError: from contextlib2 import ExitStack __version__ = "0.7.5" __all__ = [ "Schema", "And", "Or", "Regex", "Optional", "Use", "Forbidden", "Const", "Literal", "SchemaError", "SchemaWrongKeyError", "SchemaMissingKeyError", "SchemaForbiddenKeyError", "SchemaUnexpectedTypeError", "SchemaOnlyOneAllowedError", ] class SchemaError(Exception): """Error during Schema validation.""" def __init__(self, autos, errors=None): self.autos = autos if type(autos) is list else [autos] self.errors = errors if type(errors) is list else [errors] Exception.__init__(self, self.code) @property def code(self): """ Removes duplicates values in auto and error list. parameters. """ def uniq(seq): """ Utility function that removes duplicate. """ seen = set() seen_add = seen.add # This way removes duplicates while preserving the order. return [x for x in seq if x not in seen and not seen_add(x)] data_set = uniq(i for i in self.autos if i is not None) error_list = uniq(i for i in self.errors if i is not None) if error_list: return "\n".join(error_list) return "\n".join(data_set) class SchemaWrongKeyError(SchemaError): """Error Should be raised when an unexpected key is detected within the data set being.""" pass class SchemaMissingKeyError(SchemaError): """Error should be raised when a mandatory key is not found within the data set being validated""" pass class SchemaOnlyOneAllowedError(SchemaError): """Error should be raised when an only_one Or key has multiple matching candidates""" pass class SchemaForbiddenKeyError(SchemaError): """Error should be raised when a forbidden key is found within the data set being validated, and its value matches the value that was specified""" pass class SchemaUnexpectedTypeError(SchemaError): """Error should be raised when a type mismatch is detected within the data set being validated.""" pass class And(object): """ Utility function to combine validation directives in AND Boolean fashion. """ def __init__(self, *args, **kw): self._args = args if not set(kw).issubset({"error", "schema", "ignore_extra_keys"}): diff = {"error", "schema", "ignore_extra_keys"}.difference(kw) raise TypeError("Unknown keyword arguments %r" % list(diff)) self._error = kw.get("error") self._ignore_extra_keys = kw.get("ignore_extra_keys", False) # You can pass your inherited Schema class. self._schema = kw.get("schema", Schema) def __repr__(self): return "%s(%s)" % (self.__class__.__name__, ", ".join(repr(a) for a in self._args)) @property def args(self): """The provided parameters""" return self._args def validate(self, data, **kwargs): """ Validate data using defined sub schema/expressions ensuring all values are valid. :param data: to be validated with sub defined schemas. :return: returns validated data """ for s in [self._schema(s, error=self._error, ignore_extra_keys=self._ignore_extra_keys) for s in self._args]: data = s.validate(data, **kwargs) return data class Or(And): """Utility function to combine validation directives in a OR Boolean fashion.""" def __init__(self, *args, **kwargs): self.only_one = kwargs.pop("only_one", False) self.match_count = 0 super(Or, self).__init__(*args, **kwargs) def reset(self): failed = self.match_count > 1 and self.only_one self.match_count = 0 if failed: raise SchemaOnlyOneAllowedError(["There are multiple keys present " + "from the %r condition" % self]) def validate(self, data, **kwargs): """ Validate data using sub defined schema/expressions ensuring at least one value is valid. :param data: data to be validated by provided schema. :return: return validated data if not validation """ autos, errors = [], [] for s in [self._schema(s, error=self._error, ignore_extra_keys=self._ignore_extra_keys) for s in self._args]: try: validation = s.validate(data, **kwargs) self.match_count += 1 if self.match_count > 1 and self.only_one: break return validation except SchemaError as _x: autos += _x.autos errors += _x.errors raise SchemaError( ["%r did not validate %r" % (self, data)] + autos, [self._error.format(data) if self._error else None] + errors, ) class Regex(object): """ Enables schema.py to validate string using regular expressions. """ # Map all flags bits to a more readable description NAMES = [ "re.ASCII", "re.DEBUG", "re.VERBOSE", "re.UNICODE", "re.DOTALL", "re.MULTILINE", "re.LOCALE", "re.IGNORECASE", "re.TEMPLATE", ] def __init__(self, pattern_str, flags=0, error=None): self._pattern_str = pattern_str flags_list = [ Regex.NAMES[i] for i, f in enumerate("{0:09b}".format(int(flags))) if f != "0" ] # Name for each bit if flags_list: self._flags_names = ", flags=" + "|".join(flags_list) else: self._flags_names = "" self._pattern = re.compile(pattern_str, flags=flags) self._error = error def __repr__(self): return "%s(%r%s)" % (self.__class__.__name__, self._pattern_str, self._flags_names) @property def pattern_str(self): """The pattern for the represented regular expression""" return self._pattern_str def validate(self, data, **kwargs): """ Validated data using defined regex. :param data: data to be validated :return: return validated data. """ e = self._error try: if self._pattern.search(data): return data else: raise SchemaError("%r does not match %r" % (self, data), e.format(data) if e else None) except TypeError: raise SchemaError("%r is not string nor buffer" % data, e) class Use(object): """ For more general use cases, you can use the Use class to transform the data while it is being validate. """ def __init__(self, callable_, error=None): if not callable(callable_): raise TypeError("Expected a callable, not %r" % callable_) self._callable = callable_ self._error = error def __repr__(self): return "%s(%r)" % (self.__class__.__name__, self._callable) def validate(self, data, **kwargs): try: return self._callable(data) except SchemaError as x: raise SchemaError([None] + x.autos, [self._error.format(data) if self._error else None] + x.errors) except BaseException as x: f = _callable_str(self._callable) raise SchemaError("%s(%r) raised %r" % (f, data, x), self._error.format(data) if self._error else None) COMPARABLE, CALLABLE, VALIDATOR, TYPE, DICT, ITERABLE = range(6) def _priority(s): """Return priority for a given object.""" if type(s) in (list, tuple, set, frozenset): return ITERABLE if type(s) is dict: return DICT if issubclass(type(s), type): return TYPE if isinstance(s, Literal): return COMPARABLE if hasattr(s, "validate"): return VALIDATOR if callable(s): return CALLABLE else: return COMPARABLE def _invoke_with_optional_kwargs(f, **kwargs): s = inspect.signature(f) if len(s.parameters) == 0: return f() return f(**kwargs) class Schema(object): """ Entry point of the library, use this class to instantiate validation schema for the data that will be validated. """ def __init__(self, schema, error=None, ignore_extra_keys=False, name=None, description=None, as_reference=False): self._schema = schema self._error = error self._ignore_extra_keys = ignore_extra_keys self._name = name self._description = description # Ask json_schema to create a definition for this schema and use it as part of another self.as_reference = as_reference if as_reference and name is None: raise ValueError("Schema used as reference should have a name") def __repr__(self): return "%s(%r)" % (self.__class__.__name__, self._schema) @property def schema(self): return self._schema @property def description(self): return self._description @property def name(self): return self._name @property def ignore_extra_keys(self): return self._ignore_extra_keys @staticmethod def _dict_key_priority(s): """Return priority for a given key object.""" if isinstance(s, Hook): return _priority(s._schema) - 0.5 if isinstance(s, Optional): return _priority(s._schema) + 0.5 return _priority(s) @staticmethod def _is_optional_type(s): """Return True if the given key is optional (does not have to be found)""" return any(isinstance(s, optional_type) for optional_type in [Optional, Hook]) def is_valid(self, data, **kwargs): """Return whether the given data has passed all the validations that were specified in the given schema. """ try: self.validate(data, **kwargs) except SchemaError: return False else: return True def _prepend_schema_name(self, message): """ If a custom schema name has been defined, prepends it to the error message that gets raised when a schema error occurs. """ if self._name: message = "{0!r} {1!s}".format(self._name, message) return message def validate(self, data, **kwargs): Schema = self.__class__ s = self._schema e = self._error i = self._ignore_extra_keys if isinstance(s, Literal): s = s.schema flavor = _priority(s) if flavor == ITERABLE: data = Schema(type(s), error=e).validate(data, **kwargs) o = Or(*s, error=e, schema=Schema, ignore_extra_keys=i) return type(data)(o.validate(d, **kwargs) for d in data) if flavor == DICT: exitstack = ExitStack() data = Schema(dict, error=e).validate(data, **kwargs) new = type(data)() # new - is a dict of the validated values coverage = set() # matched schema keys # for each key and value find a schema entry matching them, if any sorted_skeys = sorted(s, key=self._dict_key_priority) for skey in sorted_skeys: if hasattr(skey, "reset"): exitstack.callback(skey.reset) with exitstack: # Evaluate dictionaries last data_items = sorted(data.items(), key=lambda value: isinstance(value[1], dict)) for key, value in data_items: for skey in sorted_skeys: svalue = s[skey] try: nkey = Schema(skey, error=e).validate(key, **kwargs) except SchemaError: pass else: if isinstance(skey, Hook): # As the content of the value makes little sense for # keys with a hook, we reverse its meaning: # we will only call the handler if the value does match # In the case of the forbidden key hook, # we will raise the SchemaErrorForbiddenKey exception # on match, allowing for excluding a key only if its # value has a certain type, and allowing Forbidden to # work well in combination with Optional. try: nvalue = Schema(svalue, error=e).validate(value, **kwargs) except SchemaError: continue skey.handler(nkey, data, e) else: try: nvalue = Schema(svalue, error=e, ignore_extra_keys=i).validate(value, **kwargs) except SchemaError as x: k = "Key '%s' error:" % nkey message = self._prepend_schema_name(k) raise SchemaError([message] + x.autos, [e.format(data) if e else None] + x.errors) else: new[nkey] = nvalue coverage.add(skey) break required = set(k for k in s if not self._is_optional_type(k)) if not required.issubset(coverage): missing_keys = required - coverage s_missing_keys = ", ".join(repr(k) for k in sorted(missing_keys, key=repr)) message = "Missing key%s: %s" % (_plural_s(missing_keys), s_missing_keys) message = self._prepend_schema_name(message) raise SchemaMissingKeyError(message, e.format(data) if e else None) if not self._ignore_extra_keys and (len(new) != len(data)): wrong_keys = set(data.keys()) - set(new.keys()) s_wrong_keys = ", ".join(repr(k) for k in sorted(wrong_keys, key=repr)) message = "Wrong key%s %s in %r" % (_plural_s(wrong_keys), s_wrong_keys, data) message = self._prepend_schema_name(message) raise SchemaWrongKeyError(message, e.format(data) if e else None) # Apply default-having optionals that haven't been used: defaults = set(k for k in s if isinstance(k, Optional) and hasattr(k, "default")) - coverage for default in defaults: new[default.key] = _invoke_with_optional_kwargs(default.default, **kwargs) if callable(default.default) else default.default return new if flavor == TYPE: if isinstance(data, s) and not (isinstance(data, bool) and s == int): return data else: message = "%r should be instance of %r" % (data, s.__name__) message = self._prepend_schema_name(message) raise SchemaUnexpectedTypeError(message, e.format(data) if e else None) if flavor == VALIDATOR: try: return s.validate(data, **kwargs) except SchemaError as x: raise SchemaError([None] + x.autos, [e.format(data) if e else None] + x.errors) except BaseException as x: message = "%r.validate(%r) raised %r" % (s, data, x) message = self._prepend_schema_name(message) raise SchemaError(message, e.format(data) if e else None) if flavor == CALLABLE: f = _callable_str(s) try: if s(data): return data except SchemaError as x: raise SchemaError([None] + x.autos, [e.format(data) if e else None] + x.errors) except BaseException as x: message = "%s(%r) raised %r" % (f, data, x) message = self._prepend_schema_name(message) raise SchemaError(message, e.format(data) if e else None) message = "%s(%r) should evaluate to True" % (f, data) message = self._prepend_schema_name(message) raise SchemaError(message, e.format(data) if e else None) if s == data: return data else: message = "%r does not match %r" % (s, data) message = self._prepend_schema_name(message) raise SchemaError(message, e.format(data) if e else None) def json_schema(self, schema_id, use_refs=False, **kwargs): """Generate a draft-07 JSON schema dict representing the Schema. This method must be called with a schema_id. :param schema_id: The value of the $id on the main schema :param use_refs: Enable reusing object references in the resulting JSON schema. Schemas with references are harder to read by humans, but are a lot smaller when there is a lot of reuse """ seen = dict() # For use_refs definitions_by_name = {} def _json_schema(schema, is_main_schema=True, description=None, allow_reference=True): Schema = self.__class__ def _create_or_use_ref(return_dict): """If not already seen, return the provided part of the schema unchanged. If already seen, give an id to the already seen dict and return a reference to the previous part of the schema instead. """ if not use_refs or is_main_schema: return return_schema hashed = hash(repr(sorted(return_dict.items()))) if hashed not in seen: seen[hashed] = return_dict return return_dict else: id_str = "#" + str(hashed) seen[hashed]["$id"] = id_str return {"$ref": id_str} def _get_type_name(python_type): """Return the JSON schema name for a Python type""" if python_type == str: return "string" elif python_type == int: return "integer" elif python_type == float: return "number" elif python_type == bool: return "boolean" elif python_type == list: return "array" elif python_type == dict: return "object" return "string" def _to_json_type(value): """Attempt to convert a constant value (for "const" and "default") to a JSON serializable value""" if value is None or type(value) in (str, int, float, bool, list, dict): return value if type(value) in (tuple, set, frozenset): return list(value) if isinstance(value, Literal): return value.schema return str(value) def _to_schema(s, ignore_extra_keys): if not isinstance(s, Schema): return Schema(s, ignore_extra_keys=ignore_extra_keys) return s s = schema.schema i = schema.ignore_extra_keys flavor = _priority(s) return_schema = {} return_description = description or schema.description if return_description: return_schema["description"] = return_description # Check if we have to create a common definition and use as reference if allow_reference and schema.as_reference: # Generate sub schema if not already done if schema.name not in definitions_by_name: definitions_by_name[schema.name] = {} # Avoid infinite loop definitions_by_name[schema.name] = _json_schema(schema, is_main_schema=False, allow_reference=False) return_schema["$ref"] = "#/definitions/" + schema.name else: if flavor == TYPE: # Handle type return_schema["type"] = _get_type_name(s) elif flavor == ITERABLE: # Handle arrays or dict schema return_schema["type"] = "array" if len(s) == 1: return_schema["items"] = _json_schema(_to_schema(s[0], i), is_main_schema=False) elif len(s) > 1: return_schema["items"] = _json_schema(Schema(Or(*s)), is_main_schema=False) elif isinstance(s, Or): # Handle Or values # Check if we can use an enum if all(priority == COMPARABLE for priority in [_priority(value) for value in s.args]): or_values = [str(s) if isinstance(s, Literal) else s for s in s.args] # All values are simple, can use enum or const if len(or_values) == 1: return_schema["const"] = _to_json_type(or_values[0]) return return_schema return_schema["enum"] = or_values else: # No enum, let's go with recursive calls any_of_values = [] for or_key in s.args: new_value = _json_schema(_to_schema(or_key, i), is_main_schema=False) if new_value != {} and new_value not in any_of_values: any_of_values.append(new_value) if len(any_of_values) == 1: # Only one representable condition remains, do not put under anyOf return_schema.update(any_of_values[0]) else: return_schema["anyOf"] = any_of_values elif isinstance(s, And): # Handle And values all_of_values = [] for and_key in s.args: new_value = _json_schema(_to_schema(and_key, i), is_main_schema=False) if new_value != {} and new_value not in all_of_values: all_of_values.append(new_value) if len(all_of_values) == 1: # Only one representable condition remains, do not put under allOf return_schema.update(all_of_values[0]) else: return_schema["allOf"] = all_of_values elif flavor == COMPARABLE: return_schema["const"] = _to_json_type(s) elif flavor == VALIDATOR and type(s) == Regex: return_schema["type"] = "string" return_schema["pattern"] = s.pattern_str else: if flavor != DICT: # If not handled, do not check return return_schema # Schema is a dict required_keys = [] expanded_schema = {} additional_properties = i for key in s: if isinstance(key, Hook): continue def _key_allows_additional_properties(key): """Check if a key is broad enough to allow additional properties""" if isinstance(key, Optional): return _key_allows_additional_properties(key.schema) return key == str or key == object def _get_key_description(key): """Get the description associated to a key (as specified in a Literal object). Return None if not a Literal""" if isinstance(key, Optional): return _get_key_description(key.schema) if isinstance(key, Literal): return key.description return None def _get_key_name(key): """Get the name of a key (as specified in a Literal object). Return the key unchanged if not a Literal""" if isinstance(key, Optional): return _get_key_name(key.schema) if isinstance(key, Literal): return key.schema return key additional_properties = additional_properties or _key_allows_additional_properties(key) sub_schema = _to_schema(s[key], ignore_extra_keys=i) key_name = _get_key_name(key) if isinstance(key_name, str): if not isinstance(key, Optional): required_keys.append(key_name) expanded_schema[key_name] = _json_schema( sub_schema, is_main_schema=False, description=_get_key_description(key) ) if isinstance(key, Optional) and hasattr(key, "default"): expanded_schema[key_name]["default"] = _to_json_type(_invoke_with_optional_kwargs(key.default, **kwargs) if callable(key.default) else key.default) elif isinstance(key_name, Or): # JSON schema does not support having a key named one name or another, so we just add both options # This is less strict because we cannot enforce that one or the other is required for or_key in key_name.args: expanded_schema[_get_key_name(or_key)] = _json_schema( sub_schema, is_main_schema=False, description=_get_key_description(or_key) ) return_schema.update( { "type": "object", "properties": expanded_schema, "required": required_keys, "additionalProperties": additional_properties, } ) if is_main_schema: return_schema.update({"$id": schema_id, "$schema": "http://json-schema.org/draft-07/schema#"}) if self._name: return_schema["title"] = self._name if definitions_by_name: return_schema["definitions"] = {} for definition_name, definition in definitions_by_name.items(): return_schema["definitions"][definition_name] = definition return _create_or_use_ref(return_schema) return _json_schema(self, True) class Optional(Schema): """Marker for an optional part of the validation Schema.""" _MARKER = object() def __init__(self, *args, **kwargs): default = kwargs.pop("default", self._MARKER) super(Optional, self).__init__(*args, **kwargs) if default is not self._MARKER: # See if I can come up with a static key to use for myself: if _priority(self._schema) != COMPARABLE: raise TypeError( "Optional keys with defaults must have simple, " "predictable values, like literal strings or ints. " '"%r" is too complex.' % (self._schema,) ) self.default = default self.key = str(self._schema) def __hash__(self): return hash(self._schema) def __eq__(self, other): return ( self.__class__ is other.__class__ and getattr(self, "default", self._MARKER) == getattr(other, "default", self._MARKER) and self._schema == other._schema ) def reset(self): if hasattr(self._schema, "reset"): self._schema.reset() class Hook(Schema): def __init__(self, *args, **kwargs): self.handler = kwargs.pop("handler", lambda *args: None) super(Hook, self).__init__(*args, **kwargs) self.key = self._schema class Forbidden(Hook): def __init__(self, *args, **kwargs): kwargs["handler"] = self._default_function super(Forbidden, self).__init__(*args, **kwargs) @staticmethod def _default_function(nkey, data, error): raise SchemaForbiddenKeyError("Forbidden key encountered: %r in %r" % (nkey, data), error) class Literal(object): def __init__(self, value, description=None): self._schema = value self._description = description def __str__(self): return self._schema def __repr__(self): return 'Literal("' + self.schema + '", description="' + (self.description or "") + '")' @property def description(self): return self._description @property def schema(self): return self._schema class Const(Schema): def validate(self, data, **kwargs): super(Const, self).validate(data, **kwargs) return data def _callable_str(callable_): if hasattr(callable_, "__name__"): return callable_.__name__ return str(callable_) def _plural_s(sized): return "s" if len(sized) > 1 else ""
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