| .. | |||||
| __pycache__ | |||||
| __init__.py | |||||
| ast.py | |||||
| compat.py | |||||
| exceptions.py | |||||
| functions.py | |||||
| lexer.py | |||||
| parser.py | |||||
| visitor.py |
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import math
import json
from jmespath import exceptions
from jmespath.compat import string_type as STRING_TYPE
from jmespath.compat import get_methods, with_metaclass
# python types -> jmespath types
TYPES_MAP = {
'bool': 'boolean',
'list': 'array',
'dict': 'object',
'NoneType': 'null',
'unicode': 'string',
'str': 'string',
'float': 'number',
'int': 'number',
'long': 'number',
'OrderedDict': 'object',
'_Projection': 'array',
'_Expression': 'expref',
}
# jmespath types -> python types
REVERSE_TYPES_MAP = {
'boolean': ('bool',),
'array': ('list', '_Projection'),
'object': ('dict', 'OrderedDict',),
'null': ('NoneType',),
'string': ('unicode', 'str'),
'number': ('float', 'int', 'long'),
'expref': ('_Expression',),
}
def signature(*arguments):
def _record_signature(func):
func.signature = arguments
return func
return _record_signature
class FunctionRegistry(type):
def __init__(cls, name, bases, attrs):
cls._populate_function_table()
super(FunctionRegistry, cls).__init__(name, bases, attrs)
def _populate_function_table(cls):
function_table = {}
# Any method with a @signature decorator that also
# starts with "_func_" is registered as a function.
# _func_max_by -> max_by function.
for name, method in get_methods(cls):
if not name.startswith('_func_'):
continue
signature = getattr(method, 'signature', None)
if signature is not None:
function_table[name[6:]] = {
'function': method,
'signature': signature,
}
cls.FUNCTION_TABLE = function_table
class Functions(with_metaclass(FunctionRegistry, object)):
FUNCTION_TABLE = {
}
def call_function(self, function_name, resolved_args):
try:
spec = self.FUNCTION_TABLE[function_name]
except KeyError:
raise exceptions.UnknownFunctionError(
"Unknown function: %s()" % function_name)
function = spec['function']
signature = spec['signature']
self._validate_arguments(resolved_args, signature, function_name)
return function(self, *resolved_args)
def _validate_arguments(self, args, signature, function_name):
if signature and signature[-1].get('variadic'):
if len(args) < len(signature):
raise exceptions.VariadictArityError(
len(signature), len(args), function_name)
elif len(args) != len(signature):
raise exceptions.ArityError(
len(signature), len(args), function_name)
return self._type_check(args, signature, function_name)
def _type_check(self, actual, signature, function_name):
for i in range(len(signature)):
allowed_types = signature[i]['types']
if allowed_types:
self._type_check_single(actual[i], allowed_types,
function_name)
def _type_check_single(self, current, types, function_name):
# Type checking involves checking the top level type,
# and in the case of arrays, potentially checking the types
# of each element.
allowed_types, allowed_subtypes = self._get_allowed_pytypes(types)
# We're not using isinstance() on purpose.
# The type model for jmespath does not map
# 1-1 with python types (booleans are considered
# integers in python for example).
actual_typename = type(current).__name__
if actual_typename not in allowed_types:
raise exceptions.JMESPathTypeError(
function_name, current,
self._convert_to_jmespath_type(actual_typename), types)
# If we're dealing with a list type, we can have
# additional restrictions on the type of the list
# elements (for example a function can require a
# list of numbers or a list of strings).
# Arrays are the only types that can have subtypes.
if allowed_subtypes:
self._subtype_check(current, allowed_subtypes,
types, function_name)
def _get_allowed_pytypes(self, types):
allowed_types = []
allowed_subtypes = []
for t in types:
type_ = t.split('-', 1)
if len(type_) == 2:
type_, subtype = type_
allowed_subtypes.append(REVERSE_TYPES_MAP[subtype])
else:
type_ = type_[0]
allowed_types.extend(REVERSE_TYPES_MAP[type_])
return allowed_types, allowed_subtypes
def _subtype_check(self, current, allowed_subtypes, types, function_name):
if len(allowed_subtypes) == 1:
# The easy case, we know up front what type
# we need to validate.
allowed_subtypes = allowed_subtypes[0]
for element in current:
actual_typename = type(element).__name__
if actual_typename not in allowed_subtypes:
raise exceptions.JMESPathTypeError(
function_name, element, actual_typename, types)
elif len(allowed_subtypes) > 1 and current:
# Dynamic type validation. Based on the first
# type we see, we validate that the remaining types
# match.
first = type(current[0]).__name__
for subtypes in allowed_subtypes:
if first in subtypes:
allowed = subtypes
break
else:
raise exceptions.JMESPathTypeError(
function_name, current[0], first, types)
for element in current:
actual_typename = type(element).__name__
if actual_typename not in allowed:
raise exceptions.JMESPathTypeError(
function_name, element, actual_typename, types)
@signature({'types': ['number']})
def _func_abs(self, arg):
return abs(arg)
@signature({'types': ['array-number']})
def _func_avg(self, arg):
if arg:
return sum(arg) / float(len(arg))
else:
return None
@signature({'types': [], 'variadic': True})
def _func_not_null(self, *arguments):
for argument in arguments:
if argument is not None:
return argument
@signature({'types': []})
def _func_to_array(self, arg):
if isinstance(arg, list):
return arg
else:
return [arg]
@signature({'types': []})
def _func_to_string(self, arg):
if isinstance(arg, STRING_TYPE):
return arg
else:
return json.dumps(arg, separators=(',', ':'),
default=str)
@signature({'types': []})
def _func_to_number(self, arg):
if isinstance(arg, (list, dict, bool)):
return None
elif arg is None:
return None
elif isinstance(arg, (int, float)):
return arg
else:
try:
return int(arg)
except ValueError:
try:
return float(arg)
except ValueError:
return None
@signature({'types': ['array', 'string']}, {'types': []})
def _func_contains(self, subject, search):
return search in subject
@signature({'types': ['string', 'array', 'object']})
def _func_length(self, arg):
return len(arg)
@signature({'types': ['string']}, {'types': ['string']})
def _func_ends_with(self, search, suffix):
return search.endswith(suffix)
@signature({'types': ['string']}, {'types': ['string']})
def _func_starts_with(self, search, suffix):
return search.startswith(suffix)
@signature({'types': ['array', 'string']})
def _func_reverse(self, arg):
if isinstance(arg, STRING_TYPE):
return arg[::-1]
else:
return list(reversed(arg))
@signature({"types": ['number']})
def _func_ceil(self, arg):
return math.ceil(arg)
@signature({"types": ['number']})
def _func_floor(self, arg):
return math.floor(arg)
@signature({"types": ['string']}, {"types": ['array-string']})
def _func_join(self, separator, array):
return separator.join(array)
@signature({'types': ['expref']}, {'types': ['array']})
def _func_map(self, expref, arg):
result = []
for element in arg:
result.append(expref.visit(expref.expression, element))
return result
@signature({"types": ['array-number', 'array-string']})
def _func_max(self, arg):
if arg:
return max(arg)
else:
return None
@signature({"types": ["object"], "variadic": True})
def _func_merge(self, *arguments):
merged = {}
for arg in arguments:
merged.update(arg)
return merged
@signature({"types": ['array-number', 'array-string']})
def _func_min(self, arg):
if arg:
return min(arg)
else:
return None
@signature({"types": ['array-string', 'array-number']})
def _func_sort(self, arg):
return list(sorted(arg))
@signature({"types": ['array-number']})
def _func_sum(self, arg):
return sum(arg)
@signature({"types": ['object']})
def _func_keys(self, arg):
# To be consistent with .values()
# should we also return the indices of a list?
return list(arg.keys())
@signature({"types": ['object']})
def _func_values(self, arg):
return list(arg.values())
@signature({'types': []})
def _func_type(self, arg):
if isinstance(arg, STRING_TYPE):
return "string"
elif isinstance(arg, bool):
return "boolean"
elif isinstance(arg, list):
return "array"
elif isinstance(arg, dict):
return "object"
elif isinstance(arg, (float, int)):
return "number"
elif arg is None:
return "null"
@signature({'types': ['array']}, {'types': ['expref']})
def _func_sort_by(self, array, expref):
if not array:
return array
# sort_by allows for the expref to be either a number of
# a string, so we have some special logic to handle this.
# We evaluate the first array element and verify that it's
# either a string of a number. We then create a key function
# that validates that type, which requires that remaining array
# elements resolve to the same type as the first element.
required_type = self._convert_to_jmespath_type(
type(expref.visit(expref.expression, array[0])).__name__)
if required_type not in ['number', 'string']:
raise exceptions.JMESPathTypeError(
'sort_by', array[0], required_type, ['string', 'number'])
keyfunc = self._create_key_func(expref,
[required_type],
'sort_by')
return list(sorted(array, key=keyfunc))
@signature({'types': ['array']}, {'types': ['expref']})
def _func_min_by(self, array, expref):
keyfunc = self._create_key_func(expref,
['number', 'string'],
'min_by')
if array:
return min(array, key=keyfunc)
else:
return None
@signature({'types': ['array']}, {'types': ['expref']})
def _func_max_by(self, array, expref):
keyfunc = self._create_key_func(expref,
['number', 'string'],
'max_by')
if array:
return max(array, key=keyfunc)
else:
return None
def _create_key_func(self, expref, allowed_types, function_name):
def keyfunc(x):
result = expref.visit(expref.expression, x)
actual_typename = type(result).__name__
jmespath_type = self._convert_to_jmespath_type(actual_typename)
# allowed_types is in term of jmespath types, not python types.
if jmespath_type not in allowed_types:
raise exceptions.JMESPathTypeError(
function_name, result, jmespath_type, allowed_types)
return result
return keyfunc
def _convert_to_jmespath_type(self, pyobject):
return TYPES_MAP.get(pyobject, 'unknown')
| .. | |||||
| __pycache__ | |||||
| __init__.py | |||||
| ast.py | |||||
| compat.py | |||||
| exceptions.py | |||||
| functions.py | |||||
| lexer.py | |||||
| parser.py | |||||
| visitor.py |