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"""
Implementations of standard library functions, because it's not possible to
understand them with Jedi.
To add a new implementation, create a function and add it to the
``_implemented`` dict at the bottom of this module.
Note that this module exists only to implement very specific functionality in
the standard library. The usual way to understand the standard library is the
compiled module that returns the types for C-builtins.
"""
import
collections
import
re
from
jedi
.
_compatibility
import
unicode
from
jedi
.
common
import
unite
from
jedi
.
evaluate
import
compiled
from
jedi
.
evaluate
import
representation
as
er
from
jedi
.
evaluate
import
iterable
from
jedi
.
parser
import
ParserWithRecovery
from
jedi
.
parser
import
tree
from
jedi
import
debug
from
jedi
.
evaluate
import
precedence
from
jedi
.
evaluate
import
param
from
jedi
.
evaluate
import
analysis
class
NotInStdLib
(
LookupError
):
pass
def
execute
(
evaluator
,
obj
,
arguments
):
try
:
obj_name
=
str
(
obj
.
name
)
except
AttributeError
:
pass
else
:
if
obj
.
parent
==
evaluator
.
BUILTINS
:
module_name
=
'builtins'
elif
isinstance
(
obj
.
parent
,
tree
.
Module
):
module_name
=
str
(
obj
.
parent
.
name
)
else
:
module_name
=
''
# for now we just support builtin functions.
try
:
func
=
_implemented
[
module_name
][
obj_name
]
except
KeyError
:
pass
else
:
return
func
(
evaluator
,
obj
,
arguments
)
raise
NotInStdLib
()
def
_follow_param
(
evaluator
,
arguments
,
index
):
try
:
key
,
values
=
list
(
arguments
.
unpack
())[
index
]
except
IndexError
:
return
set
()
else
:
return
unite
(
evaluator
.
eval_element
(
v
)
for
v
in
values
)
def
argument_clinic
(
string
,
want_obj
=
False
,
want_scope
=
False
,
want_arguments
=
False
):
"""
Works like Argument Clinic (PEP 436), to validate function params.
"""
clinic_args
=
[]
allow_kwargs
=
False
optional
=
False
while
string
:
# Optional arguments have to begin with a bracket. And should always be
# at the end of the arguments. This is therefore not a proper argument
# clinic implementation. `range()` for exmple allows an optional start
# value at the beginning.
match
=
re
.
match
(
'(?:(?:(\[),? ?|, ?|)(\w+)|, ?/)\]*'
,
string
)
string
=
string
[
len
(
match
.
group
(
0
)):]
if
not
match
.
group
(
2
):
# A slash -> allow named arguments
allow_kwargs
=
True
continue
optional
=
optional
or
bool
(
match
.
group
(
1
))
word
=
match
.
group
(
2
)
clinic_args
.
append
((
word
,
optional
,
allow_kwargs
))
def
f
(
func
):
def
wrapper
(
evaluator
,
obj
,
arguments
):
debug
.
dbg
(
'builtin start %s'
%
obj
,
color
=
'MAGENTA'
)
try
:
lst
=
list
(
arguments
.
eval_argument_clinic
(
clinic_args
))
except
ValueError
:
return
set
()
else
:
kwargs
=
{}
if
want_scope
:
kwargs
[
'scope'
]
=
arguments
.
scope
()
if
want_obj
:
kwargs
[
'obj'
]
=
obj
if
want_arguments
:
kwargs
[
'arguments'
]
=
arguments
return
func
(
evaluator
,
*
lst
,
**
kwargs
)
finally
:
debug
.
dbg
(
'builtin end'
,
color
=
'MAGENTA'
)
return
wrapper
return
f
@
argument_clinic
(
'object, name[, default], /'
)
def
builtins_getattr
(
evaluator
,
objects
,
names
,
defaults
=
None
):
# follow the first param
for
obj
in
objects
:
if
not
isinstance
(
obj
, (
er
.
Instance
,
er
.
Class
,
tree
.
Module
,
compiled
.
CompiledObject
)):
debug
.
warning
(
'getattr called without instance'
)
continue
for
name
in
names
:
if
precedence
.
is_string
(
name
):
return
evaluator
.
find_types
(
obj
,
name
.
obj
)
else
:
debug
.
warning
(
'getattr called without str'
)
continue
return
set
()
@
argument_clinic
(
'object[, bases, dict], /'
)
def
builtins_type
(
evaluator
,
objects
,
bases
,
dicts
):
if
bases
or
dicts
:
# It's a type creation... maybe someday...
return
set
()
else
:
return
set
([
o
.
py__class__
()
for
o
in
objects
])
class
SuperInstance
(
er
.
Instance
):
"""To be used like the object ``super`` returns."""
def
__init__
(
self
,
evaluator
,
cls
):
su
=
cls
.
py_mro
()[
1
]
super
().
__init__
(
evaluator
,
su
and
su
[
0
]
or
self
)
@
argument_clinic
(
'[type[, obj]], /'
,
want_scope
=
True
)
def
builtins_super
(
evaluator
,
types
,
objects
,
scope
):
# TODO make this able to detect multiple inheritance super
accept
=
(
tree
.
Function
,
er
.
FunctionExecution
)
if
scope
.
isinstance
(
*
accept
):
wanted
=
(
tree
.
Class
,
er
.
Instance
)
cls
=
scope
.
get_parent_until
(
accept
+
wanted
,
include_current
=
False
)
if
isinstance
(
cls
,
wanted
):
if
isinstance
(
cls
,
tree
.
Class
):
cls
=
er
.
Class
(
evaluator
,
cls
)
elif
isinstance
(
cls
,
er
.
Instance
):
cls
=
cls
.
base
su
=
cls
.
py__bases__
()
if
su
:
return
evaluator
.
execute
(
su
[
0
])
return
set
()
@
argument_clinic
(
'sequence, /'
,
want_obj
=
True
,
want_arguments
=
True
)
def
builtins_reversed
(
evaluator
,
sequences
,
obj
,
arguments
):
# While we could do without this variable (just by using sequences), we
# want static analysis to work well. Therefore we need to generated the
# values again.
first_arg
=
next
(
arguments
.
as_tuple
())[
0
]
ordered
=
list
(
iterable
.
py__iter__
(
evaluator
,
sequences
,
first_arg
))
rev
=
[
iterable
.
AlreadyEvaluated
(
o
)
for
o
in
reversed
(
ordered
)]
# Repack iterator values and then run it the normal way. This is
# necessary, because `reversed` is a function and autocompletion
# would fail in certain cases like `reversed(x).__iter__` if we
# just returned the result directly.
rev
=
iterable
.
AlreadyEvaluated
(
[
iterable
.
FakeSequence
(
evaluator
,
rev
,
'list'
)]
)
return
set
([
er
.
Instance
(
evaluator
,
obj
,
param
.
Arguments
(
evaluator
, [
rev
]))])
@
argument_clinic
(
'obj, type, /'
,
want_arguments
=
True
)
def
builtins_isinstance
(
evaluator
,
objects
,
types
,
arguments
):
bool_results
=
set
([])
for
o
in
objects
:
try
:
mro_func
=
o
.
py__class__
().
py__mro__
except
AttributeError
:
# This is temporary. Everything should have a class attribute in
# Python?! Maybe we'll leave it here, because some numpy objects or
# whatever might not.
return
set
([
compiled
.
create
(
True
),
compiled
.
create
(
False
)])
mro
=
mro_func
()
for
cls_or_tup
in
types
:
if
cls_or_tup
.
is_class
():
bool_results
.
add
(
cls_or_tup
in
mro
)
elif
str
(
cls_or_tup
.
name
)
==
'tuple'
\
and
cls_or_tup
.
get_parent_scope
()
==
evaluator
.
BUILTINS
:
# Check for tuples.
classes
=
unite
(
cls_or_tup
.
py__iter__
())
bool_results
.
add
(
any
(
cls
in
mro
for
cls
in
classes
))
else
:
_
,
nodes
=
list
(
arguments
.
unpack
())[
1
]
for
node
in
nodes
:
message
=
'TypeError: isinstance() arg 2 must be a '
\
'class, type, or tuple of classes and types, '
\
'not %s.'
%
cls_or_tup
analysis
.
add
(
evaluator
,
'type-error-isinstance'
,
node
,
message
)
return
set
(
compiled
.
create
(
evaluator
,
x
)
for
x
in
bool_results
)
def
collections_namedtuple
(
evaluator
,
obj
,
arguments
):
"""
Implementation of the namedtuple function.
This has to be done by processing the namedtuple class template and
evaluating the result.
.. note:: |jedi| only supports namedtuples on Python >2.6.
"""
# Namedtuples are not supported on Python 2.6
if
not
hasattr
(
collections
,
'_class_template'
):
return
set
()
# Process arguments
# TODO here we only use one of the types, we should use all.
name
=
list
(
_follow_param
(
evaluator
,
arguments
,
0
))[
0
].
obj
_fields
=
list
(
_follow_param
(
evaluator
,
arguments
,
1
))[
0
]
if
isinstance
(
_fields
,
compiled
.
CompiledObject
):
fields
=
_fields
.
obj
.
replace
(
','
,
' '
).
split
()
elif
isinstance
(
_fields
,
iterable
.
Array
):
try
:
fields
=
[
v
.
obj
for
v
in
unite
(
_fields
.
py__iter__
())]
except
AttributeError
:
return
set
()
else
:
return
set
()
# Build source
source
=
collections
.
_class_template
.
format
(
typename
=
name
,
field_names
=
fields
,
num_fields
=
len
(
fields
),
arg_list
=
', '
.
join
(
fields
),
repr_fmt
=
', '
.
join
(
collections
.
_repr_template
.
format
(
name
=
name
)
for
name
in
fields
),
field_defs
=
'
\n
'
.
join
(
collections
.
_field_template
.
format
(
index
=
index
,
name
=
name
)
for
index
,
name
in
enumerate
(
fields
))
)
# Parse source
generated_class
=
ParserWithRecovery
(
evaluator
.
grammar
,
unicode
(
source
)).
module
.
subscopes
[
0
]
return
set
([
er
.
Class
(
evaluator
,
generated_class
)])
@
argument_clinic
(
'first, /'
)
def
_return_first_param
(
evaluator
,
firsts
):
return
firsts
_implemented
=
{
'builtins'
: {
'getattr'
:
builtins_getattr
,
'type'
:
builtins_type
,
'super'
:
builtins_super
,
'reversed'
:
builtins_reversed
,
'isinstance'
:
builtins_isinstance
,
},
'copy'
: {
'copy'
:
_return_first_param
,
'deepcopy'
:
_return_first_param
,
},
'json'
: {
'load'
:
lambda
*
args
:
set
(),
'loads'
:
lambda
*
args
:
set
(),
},
'collections'
: {
'namedtuple'
:
collections_namedtuple
,
},
}
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