Current File : //lib/python3/dist-packages/mypy/semanal_main.py
"""Top-level logic for the semantic analyzer.
The semantic analyzer binds names, resolves imports, detects various
special constructs that don't have dedicated AST nodes after parse
(such as 'cast' which looks like a call), populates symbol tables, and
performs various simple consistency checks.
Semantic analysis of each SCC (strongly connected component; import
cycle) is performed in one unit. Each module is analyzed as multiple
separate *targets*; the module top level is one target and each function
is a target. Nested functions are not separate targets, however. This is
mostly identical to targets used by mypy daemon (but classes aren't
targets in semantic analysis).
We first analyze each module top level in an SCC. If we encounter some
names that we can't bind because the target of the name may not have
been processed yet, we *defer* the current target for further
processing. Deferred targets will be analyzed additional times until
everything can be bound, or we reach a maximum number of iterations.
We keep track of a set of incomplete namespaces, i.e. namespaces that we
haven't finished populating yet. References to these namespaces cause a
deferral if they can't be satisfied. Initially every module in the SCC
will be incomplete.
"""
from typing import List, Tuple, Optional, Union, Callable
from typing_extensions import TYPE_CHECKING, Final, TypeAlias as _TypeAlias
from mypy.backports import nullcontext
from mypy.nodes import (
MypyFile, TypeInfo, FuncDef, Decorator, OverloadedFuncDef, Var
)
from mypy.semanal_typeargs import TypeArgumentAnalyzer
from mypy.state import strict_optional_set
from mypy.semanal import (
SemanticAnalyzer, apply_semantic_analyzer_patches, remove_imported_names_from_symtable
)
from mypy.semanal_classprop import (
calculate_class_abstract_status, calculate_class_vars, check_protocol_status,
add_type_promotion
)
from mypy.errors import Errors
from mypy.semanal_infer import infer_decorator_signature_if_simple
from mypy.checker import FineGrainedDeferredNode
from mypy.server.aststrip import SavedAttributes
from mypy.util import is_typeshed_file
import mypy.build
if TYPE_CHECKING:
from mypy.build import Graph, State
Patches: _TypeAlias = List[Tuple[int, Callable[[], None]]]
# If we perform this many iterations, raise an exception since we are likely stuck.
MAX_ITERATIONS: Final = 20
# Number of passes over core modules before going on to the rest of the builtin SCC.
CORE_WARMUP: Final = 2
core_modules: Final = ['typing', 'builtins', 'abc', 'collections']
def semantic_analysis_for_scc(graph: 'Graph', scc: List[str], errors: Errors) -> None:
"""Perform semantic analysis for all modules in a SCC (import cycle).
Assume that reachability analysis has already been performed.
The scc will be processed roughly in the order the modules are included
in the list.
"""
patches: Patches = []
# Note that functions can't define new module-level attributes
# using 'global x', since module top levels are fully processed
# before functions. This limitation is unlikely to go away soon.
process_top_levels(graph, scc, patches)
process_functions(graph, scc, patches)
# We use patch callbacks to fix up things when we expect relatively few
# callbacks to be required.
apply_semantic_analyzer_patches(patches)
# This pass might need fallbacks calculated above.
check_type_arguments(graph, scc, errors)
calculate_class_properties(graph, scc, errors)
check_blockers(graph, scc)
# Clean-up builtins, so that TypeVar etc. are not accessible without importing.
if 'builtins' in scc:
cleanup_builtin_scc(graph['builtins'])
def cleanup_builtin_scc(state: 'State') -> None:
"""Remove imported names from builtins namespace.
This way names imported from typing in builtins.pyi aren't available
by default (without importing them). We can only do this after processing
the whole SCC is finished, when the imported names aren't needed for
processing builtins.pyi itself.
"""
assert state.tree is not None
remove_imported_names_from_symtable(state.tree.names, 'builtins')
def semantic_analysis_for_targets(
state: 'State',
nodes: List[FineGrainedDeferredNode],
graph: 'Graph',
saved_attrs: SavedAttributes) -> None:
"""Semantically analyze only selected nodes in a given module.
This essentially mirrors the logic of semantic_analysis_for_scc()
except that we process only some targets. This is used in fine grained
incremental mode, when propagating an update.
The saved_attrs are implicitly declared instance attributes (attributes
defined on self) removed by AST stripper that may need to be reintroduced
here. They must be added before any methods are analyzed.
"""
patches: Patches = []
if any(isinstance(n.node, MypyFile) for n in nodes):
# Process module top level first (if needed).
process_top_levels(graph, [state.id], patches)
restore_saved_attrs(saved_attrs)
analyzer = state.manager.semantic_analyzer
for n in nodes:
if isinstance(n.node, MypyFile):
# Already done above.
continue
process_top_level_function(analyzer, state, state.id,
n.node.fullname, n.node, n.active_typeinfo, patches)
apply_semantic_analyzer_patches(patches)
check_type_arguments_in_targets(nodes, state, state.manager.errors)
calculate_class_properties(graph, [state.id], state.manager.errors)
def restore_saved_attrs(saved_attrs: SavedAttributes) -> None:
"""Restore instance variables removed during AST strip that haven't been added yet."""
for (cdef, name), sym in saved_attrs.items():
info = cdef.info
existing = info.get(name)
defined_in_this_class = name in info.names
assert isinstance(sym.node, Var)
# This needs to mimic the logic in SemanticAnalyzer.analyze_member_lvalue()
# regarding the existing variable in class body or in a superclass:
# If the attribute of self is not defined in superclasses, create a new Var.
if (existing is None or
# (An abstract Var is considered as not defined.)
(isinstance(existing.node, Var) and existing.node.is_abstract_var) or
# Also an explicit declaration on self creates a new Var unless
# there is already one defined in the class body.
sym.node.explicit_self_type and not defined_in_this_class):
info.names[name] = sym
def process_top_levels(graph: 'Graph', scc: List[str], patches: Patches) -> None:
# Process top levels until everything has been bound.
# Reverse order of the scc so the first modules in the original list will be
# be processed first. This helps with performance.
scc = list(reversed(scc))
# Initialize ASTs and symbol tables.
for id in scc:
state = graph[id]
assert state.tree is not None
state.manager.semantic_analyzer.prepare_file(state.tree)
# Initially all namespaces in the SCC are incomplete (well they are empty).
state.manager.incomplete_namespaces.update(scc)
worklist = scc[:]
# HACK: process core stuff first. This is mostly needed to support defining
# named tuples in builtin SCC.
if all(m in worklist for m in core_modules):
worklist += list(reversed(core_modules)) * CORE_WARMUP
final_iteration = False
iteration = 0
analyzer = state.manager.semantic_analyzer
analyzer.deferral_debug_context.clear()
while worklist:
iteration += 1
if iteration > MAX_ITERATIONS:
# Just pick some module inside the current SCC for error context.
assert state.tree is not None
with analyzer.file_context(state.tree, state.options):
analyzer.report_hang()
break
if final_iteration:
# Give up. It's impossible to bind all names.
state.manager.incomplete_namespaces.clear()
all_deferred: List[str] = []
any_progress = False
while worklist:
next_id = worklist.pop()
state = graph[next_id]
assert state.tree is not None
deferred, incomplete, progress = semantic_analyze_target(next_id, state,
state.tree,
None,
final_iteration,
patches)
all_deferred += deferred
any_progress = any_progress or progress
if not incomplete:
state.manager.incomplete_namespaces.discard(next_id)
if final_iteration:
assert not all_deferred, 'Must not defer during final iteration'
# Reverse to process the targets in the same order on every iteration. This avoids
# processing the same target twice in a row, which is inefficient.
worklist = list(reversed(all_deferred))
final_iteration = not any_progress
def process_functions(graph: 'Graph', scc: List[str], patches: Patches) -> None:
# Process functions.
for module in scc:
tree = graph[module].tree
assert tree is not None
analyzer = graph[module].manager.semantic_analyzer
# In principle, functions can be processed in arbitrary order,
# but _methods_ must be processed in the order they are defined,
# because some features (most notably partial types) depend on
# order of definitions on self.
#
# There can be multiple generated methods per line. Use target
# name as the second sort key to get a repeatable sort order on
# Python 3.5, which doesn't preserve dictionary order.
targets = sorted(get_all_leaf_targets(tree), key=lambda x: (x[1].line, x[0]))
for target, node, active_type in targets:
assert isinstance(node, (FuncDef, OverloadedFuncDef, Decorator))
process_top_level_function(analyzer,
graph[module],
module,
target,
node,
active_type,
patches)
def process_top_level_function(analyzer: 'SemanticAnalyzer',
state: 'State',
module: str,
target: str,
node: Union[FuncDef, OverloadedFuncDef, Decorator],
active_type: Optional[TypeInfo],
patches: Patches) -> None:
"""Analyze single top-level function or method.
Process the body of the function (including nested functions) again and again,
until all names have been resolved (or iteration limit reached).
"""
# We need one more iteration after incomplete is False (e.g. to report errors, if any).
final_iteration = False
incomplete = True
# Start in the incomplete state (no missing names will be reported on first pass).
# Note that we use module name, since functions don't create qualified names.
deferred = [module]
analyzer.deferral_debug_context.clear()
analyzer.incomplete_namespaces.add(module)
iteration = 0
while deferred:
iteration += 1
if iteration == MAX_ITERATIONS:
# Just pick some module inside the current SCC for error context.
assert state.tree is not None
with analyzer.file_context(state.tree, state.options):
analyzer.report_hang()
break
if not (deferred or incomplete) or final_iteration:
# OK, this is one last pass, now missing names will be reported.
analyzer.incomplete_namespaces.discard(module)
deferred, incomplete, progress = semantic_analyze_target(target, state, node, active_type,
final_iteration, patches)
if final_iteration:
assert not deferred, 'Must not defer during final iteration'
if not progress:
final_iteration = True
analyzer.incomplete_namespaces.discard(module)
# After semantic analysis is done, discard local namespaces
# to avoid memory hoarding.
analyzer.saved_locals.clear()
TargetInfo = Tuple[str, Union[MypyFile, FuncDef, OverloadedFuncDef, Decorator], Optional[TypeInfo]]
def get_all_leaf_targets(file: MypyFile) -> List[TargetInfo]:
"""Return all leaf targets in a symbol table (module-level and methods)."""
result: List[TargetInfo] = []
for fullname, node, active_type in file.local_definitions():
if isinstance(node.node, (FuncDef, OverloadedFuncDef, Decorator)):
result.append((fullname, node.node, active_type))
return result
def semantic_analyze_target(target: str,
state: 'State',
node: Union[MypyFile, FuncDef, OverloadedFuncDef, Decorator],
active_type: Optional[TypeInfo],
final_iteration: bool,
patches: Patches) -> Tuple[List[str], bool, bool]:
"""Semantically analyze a single target.
Return tuple with these items:
- list of deferred targets
- was some definition incomplete (need to run another pass)
- were any new names defined (or placeholders replaced)
"""
state.manager.processed_targets.append(target)
tree = state.tree
assert tree is not None
analyzer = state.manager.semantic_analyzer
# TODO: Move initialization to somewhere else
analyzer.global_decls = [set()]
analyzer.nonlocal_decls = [set()]
analyzer.globals = tree.names
analyzer.progress = False
with state.wrap_context(check_blockers=False):
refresh_node = node
if isinstance(refresh_node, Decorator):
# Decorator expressions will be processed as part of the module top level.
refresh_node = refresh_node.func
analyzer.refresh_partial(refresh_node,
patches,
final_iteration,
file_node=tree,
options=state.options,
active_type=active_type)
if isinstance(node, Decorator):
infer_decorator_signature_if_simple(node, analyzer)
for dep in analyzer.imports:
state.add_dependency(dep)
priority = mypy.build.PRI_LOW
if priority <= state.priorities.get(dep, priority):
state.priorities[dep] = priority
# Clear out some stale data to avoid memory leaks and astmerge
# validity check confusion
analyzer.statement = None
del analyzer.cur_mod_node
if analyzer.deferred:
return [target], analyzer.incomplete, analyzer.progress
else:
return [], analyzer.incomplete, analyzer.progress
def check_type_arguments(graph: 'Graph', scc: List[str], errors: Errors) -> None:
for module in scc:
state = graph[module]
assert state.tree
analyzer = TypeArgumentAnalyzer(errors,
state.options,
is_typeshed_file(state.path or ''))
with state.wrap_context():
with strict_optional_set(state.options.strict_optional):
state.tree.accept(analyzer)
def check_type_arguments_in_targets(targets: List[FineGrainedDeferredNode], state: 'State',
errors: Errors) -> None:
"""Check type arguments against type variable bounds and restrictions.
This mirrors the logic in check_type_arguments() except that we process only
some targets. This is used in fine grained incremental mode.
"""
analyzer = TypeArgumentAnalyzer(errors,
state.options,
is_typeshed_file(state.path or ''))
with state.wrap_context():
with strict_optional_set(state.options.strict_optional):
for target in targets:
func: Optional[Union[FuncDef, OverloadedFuncDef]] = None
if isinstance(target.node, (FuncDef, OverloadedFuncDef)):
func = target.node
saved = (state.id, target.active_typeinfo, func) # module, class, function
with errors.scope.saved_scope(saved) if errors.scope else nullcontext():
analyzer.recurse_into_functions = func is not None
target.node.accept(analyzer)
def calculate_class_properties(graph: 'Graph', scc: List[str], errors: Errors) -> None:
for module in scc:
tree = graph[module].tree
assert tree
for _, node, _ in tree.local_definitions():
if isinstance(node.node, TypeInfo):
saved = (module, node.node, None) # module, class, function
with errors.scope.saved_scope(saved) if errors.scope else nullcontext():
calculate_class_abstract_status(node.node, tree.is_stub, errors)
check_protocol_status(node.node, errors)
calculate_class_vars(node.node)
add_type_promotion(node.node, tree.names, graph[module].options)
def check_blockers(graph: 'Graph', scc: List[str]) -> None:
for module in scc:
graph[module].check_blockers()
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