FM / site-packages

/opt/cloudlinux/venv/lib/python3.11/site-packages/

/opt/cloudlinux/venv/lib/python3.11/site-packages

Name	Size	Mode	Actions
aiohttp/	-	0755	rm
aiohttp-3.9.2.dist-info/	-	0755	rm
aiohttp_jinja2/	-	0755	rm
aiohttp_jinja2-1.5.dist-info/	-	0755	rm
aiohttp_security/	-	0755	rm
aiohttp_security-0.4.0.dist-info/	-	0755	rm
aiohttp_session/	-	0755	rm
aiohttp_session-2.9.0.dist-info/	-	0755	rm
aiosignal/	-	0755	rm
aiosignal-1.3.1.dist-info/	-	0755	rm
alembic/	-	0755	rm
alembic-1.11.1.dist-info/	-	0755	rm
astroid/	-	0755	rm
astroid-2.15.6.dist-info/	-	0755	rm
attr/	-	0755	rm
attrs/	-	0755	rm
attrs-23.1.0.dist-info/	-	0755	rm
backports/	-	0755	rm
certifi/	-	0755	rm
certifi-2023.7.22.dist-info/	-	0755	rm
cffi/	-	0755	rm
cffi-1.15.1.dist-info/	-	0755	rm
chardet/	-	0755	rm
chardet-5.2.0.dist-info/	-	0755	rm
charset_normalizer/	-	0755	rm
charset_normalizer-2.1.1.dist-info/	-	0755	rm
clcagefslib/	-	0755	rm
clcommon/	-	0755	rm
clconfig/	-	0755	rm
clconfigure/	-	0755	rm
cldashboard/	-	0755	rm
clevents/	-	0755	rm
clflags/	-	0755	rm
cllicense/	-	0755	rm
cllimits/	-	0755	rm
cllimitslib_v2/	-	0755	rm
cllimits_validator/	-	0755	rm
cllvectl/	-	0755	rm
clpackages/	-	0755	rm
clquota/	-	0755	rm
clselect/	-	0755	rm
clselector/	-	0755	rm
clsentry/	-	0755	rm
clsummary/	-	0755	rm
clveconfig/	-	0755	rm
clwizard/	-	0755	rm
clwpos/	-	0755	rm
cl_dom_collector/	-	0755	rm
cl_website_collector/	-	0755	rm
configparser-5.0.2.dist-info/	-	0755	rm
contextlib2/	-	0755	rm
contextlib2-21.6.0.dist-info/	-	0755	rm
coverage/	-	0755	rm
coverage-7.2.7.dist-info/	-	0755	rm
cryptography/	-	0755	rm
cryptography-41.0.2.dist-info/	-	0755	rm
ddt-1.4.4.dist-info/	-	0755	rm
dill/	-	0755	rm
dill-0.3.7.dist-info/	-	0755	rm
distlib/	-	0755	rm
distlib-0.3.8.dist-info/	-	0755	rm
docopt-0.6.2.dist-info/	-	0755	rm
dodgy/	-	0755	rm
dodgy-0.2.1.dist-info/	-	0755	rm
filelock/	-	0755	rm
filelock-3.13.1.dist-info/	-	0755	rm
flake8/	-	0755	rm
flake8-5.0.4.dist-info/	-	0755	rm
flake8_polyfill/	-	0755	rm
flake8_polyfill-1.0.2.dist-info/	-	0755	rm
frozenlist/	-	0755	rm
frozenlist-1.4.0.dist-info/	-	0755	rm
future/	-	0755	rm
future-0.18.3.dist-info/	-	0755	rm
git/	-	0755	rm
gitdb/	-	0755	rm
gitdb-4.0.10.dist-info/	-	0755	rm
GitPython-3.1.32.dist-info/	-	0755	rm
guppy/	-	0755	rm
guppy3-3.1.3.dist-info/	-	0755	rm
idna/	-	0755	rm
idna-3.4.dist-info/	-	0755	rm
iniconfig/	-	0755	rm
iniconfig-2.0.0.dist-info/	-	0755	rm
isort/	-	0755	rm
isort-5.12.0.dist-info/	-	0755	rm
jinja2/	-	0755	rm
Jinja2-3.0.3.dist-info/	-	0755	rm
jsonschema/	-	0755	rm
jsonschema-3.2.0.dist-info/	-	0755	rm
jwt/	-	0755	rm
lazy_object_proxy/	-	0755	rm
lazy_object_proxy-1.9.0.dist-info/	-	0755	rm
libfuturize/	-	0755	rm
libpasteurize/	-	0755	rm
lvemanager/	-	0755	rm
lvestats/	-	0755	rm
lve_stats-2.0.dist-info/	-	0755	rm
lve_utils/	-	0755	rm
lxml/	-	0755	rm
lxml-4.9.2.dist-info/	-	0755	rm
mako/	-	0755	rm
Mako-1.2.4.dist-info/	-	0755	rm
markupsafe/	-	0755	rm
MarkupSafe-2.1.3.dist-info/	-	0755	rm
mccabe-0.7.0.dist-info/	-	0755	rm
mock/	-	0755	rm
mock-5.1.0.dist-info/	-	0755	rm
multidict/	-	0755	rm
multidict-6.0.4.dist-info/	-	0755	rm
numpy/	-	0755	rm
numpy-1.25.1.dist-info/	-	0755	rm
numpy.libs/	-	0755	rm
packaging/	-	0755	rm
packaging-23.1.dist-info/	-	0755	rm
past/	-	0755	rm
pep8_naming-0.10.0.dist-info/	-	0755	rm
pip/	-	0755	rm
pip-24.3.1.dist-info/	-	0755	rm
pkg_resources/	-	0755	rm
platformdirs/	-	0755	rm
platformdirs-3.11.0.dist-info/	-	0755	rm
pluggy/	-	0755	rm
pluggy-1.2.0.dist-info/	-	0755	rm
prettytable/	-	0755	rm
prettytable-3.8.0.dist-info/	-	0755	rm
prometheus_client/	-	0755	rm
prometheus_client-0.8.0.dist-info/	-	0755	rm
prospector/	-	0755	rm
prospector-1.10.2.dist-info/	-	0755	rm
psutil/	-	0755	rm
psutil-5.9.5.dist-info/	-	0755	rm
psycopg2/	-	0755	rm
psycopg2_binary-2.9.6.dist-info/	-	0755	rm
psycopg2_binary.libs/	-	0755	rm
pycodestyle-2.9.1.dist-info/	-	0755	rm
pycparser/	-	0755	rm
pycparser-2.21.dist-info/	-	0755	rm
pydocstyle/	-	0755	rm
pydocstyle-6.3.0.dist-info/	-	0755	rm
pyfakefs/	-	0755	rm
pyfakefs-5.10.2.dist-info/	-	0755	rm
pyflakes/	-	0755	rm
pyflakes-2.5.0.dist-info/	-	0755	rm
PyJWT-2.8.0.dist-info/	-	0755	rm
pylint/	-	0755	rm
pylint-2.17.4.dist-info/	-	0755	rm
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pylint_celery-0.3.dist-info/	-	0755	rm
pylint_django/	-	0755	rm
pylint_django-2.5.3.dist-info/	-	0755	rm
pylint_flask/	-	0755	rm
pylint_flask-0.6.dist-info/	-	0755	rm
pylint_plugin_utils/	-	0755	rm
pylint_plugin_utils-0.7.dist-info/	-	0755	rm
pylve-2.1-py3.11.egg-info/	-	0755	rm
pymysql/	-	0755	rm
PyMySQL-1.1.0.dist-info/	-	0755	rm
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pyrsistent-0.19.3.dist-info/	-	0755	rm
pytest/	-	0755	rm
pytest-7.4.0.dist-info/	-	0755	rm
pytest_check/	-	0755	rm
pytest_check-2.5.3.dist-info/	-	0755	rm
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pytest_snapshot-0.9.0.dist-info/	-	0755	rm
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pytest_subprocess-1.5.3.dist-info/	-	0755	rm
pytest_tap/	-	0755	rm
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python_pam-1.8.4.dist-info/	-	0755	rm
pyvirtualdisplay/	-	0755	rm
PyVirtualDisplay-3.0.dist-info/	-	0755	rm
PyYAML-6.0.1.dist-info/	-	0755	rm
raven/	-	0755	rm
raven-6.10.0.dist-info/	-	0755	rm
requests/	-	0755	rm
requests-2.31.0.dist-info/	-	0755	rm
requirements_detector/	-	0755	rm
requirements_detector-1.2.2.dist-info/	-	0755	rm
schema-0.7.5.dist-info/	-	0755	rm
semver/	-	0755	rm
semver-3.0.1.dist-info/	-	0755	rm
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setuptools-81.0.0.dist-info/	-	0755	rm
simplejson/	-	0755	rm
simplejson-3.19.1.dist-info/	-	0755	rm
six-1.16.0.dist-info/	-	0755	rm
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snowballstemmer-2.2.0.dist-info/	-	0755	rm
sqlalchemy/	-	0755	rm
sqlalchemy-1.3.24.dist-info/	-	0755	rm
ssa/	-	0755	rm
svgwrite/	-	0755	rm
svgwrite-1.4.3.dist-info/	-	0755	rm
tap/	-	0755	rm
tap_py-3.2.1.dist-info/	-	0755	rm
testfixtures/	-	0755	rm
testfixtures-7.1.0.dist-info/	-	0755	rm
toml/	-	0755	rm
toml-0.10.2.dist-info/	-	0755	rm
tomlkit/	-	0755	rm
tomlkit-0.11.8.dist-info/	-	0755	rm
typing_extensions-4.7.1.dist-info/	-	0755	rm
unshare-0.22.dist-info/	-	0755	rm
urllib3/	-	0755	rm
urllib3-2.0.4.dist-info/	-	0755	rm
vendors_api/	-	0755	rm
virtualenv/	-	0755	rm
virtualenv-20.21.1.dist-info/	-	0755	rm
wcwidth/	-	0755	rm
wcwidth-0.2.6.dist-info/	-	0755	rm
websiteisolation/	-	0755	rm
wmt/	-	0755	rm
wrapt/	-	0755	rm
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xray/	-	0755	rm
yaml/	-	0755	rm
yarl/	-	0755	rm
yarl-1.9.2.dist-info/	-	0755	rm
_distutils_hack/	-	0755	rm
_pytest/	-	0755	rm
_yaml/	-	0755	rm
__pycache__/	-	0755	rm
clcontrollib.py	53042	0644	edit dl rm
cldetectlib.py	18843	0644	edit dl rm
cldiaglib.py	49660	0644	edit dl rm
clhooklib.py	1296	0644	edit dl rm
cli_utils.py	1698	0644	edit dl rm
cllicenselib.py	11864	0644	edit dl rm
clsetuplib.py	5193	0644	edit dl rm
clsudo.py	23586	0644	edit dl rm
cl_proc_hidepid.py	4638	0644	edit dl rm
configparser.py	1546	0644	edit dl rm
ddt.py	12733	0644	edit dl rm
distutils-precedence.pth	151	0644	edit dl rm
docopt.py	19946	0644	edit dl rm
lveapi.py	23294	0644	edit dl rm
lvectllib.py	136479	0644	edit dl rm
lvestat.py	6997	0644	edit dl rm
mccabe.py	10654	0644	edit dl rm
pam.py	7556	0644	edit dl rm
pep8ext_naming.py	19052	0644	edit dl rm
py.py	263	0644	edit dl rm
pycodestyle.py	103501	0644	edit dl rm
pylve.cpython-311-x86_64-linux-gnu.so	29528	0755	edit dl rm
remove_ubc.py	5864	0755	edit dl rm
schema.py	30221	0644	edit dl rm
secureio.py	20037	0644	edit dl rm
simple_rpm.so	15544	0755	edit dl rm
six.py	34549	0644	edit dl rm
typing_extensions.py	111082	0644	edit dl rm
unshare.cpython-311-x86_64-linux-gnu.so	16704	0755	edit dl rm
_cffi_backend.cpython-311-x86_64-linux-gnu.so	274048	0755	edit dl rm
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Edit: /opt/cloudlinux/venv/lib/python3.11/site-packages/schema.py (30221B)

"""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 ""

cmd: