""" Type inference of Python code in |jedi| is based on three assumptions: * The code uses as least side effects as possible. Jedi understands certain list/tuple/set modifications, but there's no guarantee that Jedi detects everything (list.append in different modules for example). * No magic is being used: - metaclasses - ``setattr()`` / ``__import__()`` - writing to ``globals()``, ``locals()``, ``object.__dict__`` * The programmer is not a total dick, e.g. like `this `_ :-) The actual algorithm is based on a principle I call lazy type inference. That said, the typical entry point for static analysis is calling ``infer_expr_stmt``. There's separate logic for autocompletion in the API, the inference_state is all about inferring an expression. TODO this paragraph is not what jedi does anymore, it's similar, but not the same. Now you need to understand what follows after ``infer_expr_stmt``. Let's make an example:: import datetime datetime.date.toda# <-- cursor here First of all, this module doesn't care about completion. It really just cares about ``datetime.date``. At the end of the procedure ``infer_expr_stmt`` will return the ``date`` class. To *visualize* this (simplified): - ``InferenceState.infer_expr_stmt`` doesn't do much, because there's no assignment. - ``Context.infer_node`` cares for resolving the dotted path - ``InferenceState.find_types`` searches for global definitions of datetime, which it finds in the definition of an import, by scanning the syntax tree. - Using the import logic, the datetime module is found. - Now ``find_types`` is called again by ``infer_node`` to find ``date`` inside the datetime module. Now what would happen if we wanted ``datetime.date.foo.bar``? Two more calls to ``find_types``. However the second call would be ignored, because the first one would return nothing (there's no foo attribute in ``date``). What if the import would contain another ``ExprStmt`` like this:: from foo import bar Date = bar.baz Well... You get it. Just another ``infer_expr_stmt`` recursion. It's really easy. Python can obviously get way more complicated then this. To understand tuple assignments, list comprehensions and everything else, a lot more code had to be written. Jedi has been tested very well, so you can just start modifying code. It's best to write your own test first for your "new" feature. Don't be scared of breaking stuff. As long as the tests pass, you're most likely to be fine. I need to mention now that lazy type inference is really good because it only *inferes* what needs to be *inferred*. All the statements and modules that are not used are just being ignored. """ import parso from jedi.file_io import FileIO from jedi import debug from jedi import settings from jedi.inference import imports from jedi.inference import recursion from jedi.inference.cache import inference_state_function_cache from jedi.inference import helpers from jedi.inference.names import TreeNameDefinition from jedi.inference.base_value import ContextualizedNode, \ ValueSet, iterate_values from jedi.inference.value import ClassValue, FunctionValue from jedi.inference.syntax_tree import infer_expr_stmt, \ check_tuple_assignments, tree_name_to_values from jedi.inference.imports import follow_error_node_imports_if_possible from jedi.plugins import plugin_manager class InferenceState: def __init__(self, project, environment=None, script_path=None): if environment is None: environment = project.get_environment() self.environment = environment self.script_path = script_path self.compiled_subprocess = environment.get_inference_state_subprocess(self) self.grammar = environment.get_grammar() self.latest_grammar = parso.load_grammar(version='3.12') self.memoize_cache = {} # for memoize decorators self.module_cache = imports.ModuleCache() # does the job of `sys.modules`. self.stub_module_cache = {} # Dict[Tuple[str, ...], Optional[ModuleValue]] self.compiled_cache = {} # see `inference.compiled.create()` self.inferred_element_counts = {} self.mixed_cache = {} # see `inference.compiled.mixed._create()` self.analysis = [] self.dynamic_params_depth = 0 self.do_dynamic_params_search = settings.dynamic_params self.is_analysis = False self.project = project self.access_cache = {} self.allow_unsafe_executions = False self.flow_analysis_enabled = True self.reset_recursion_limitations() def import_module(self, import_names, sys_path=None, prefer_stubs=True): return imports.import_module_by_names( self, import_names, sys_path, prefer_stubs=prefer_stubs) @staticmethod @plugin_manager.decorate() def execute(value, arguments): debug.dbg('execute: %s %s', value, arguments) with debug.increase_indent_cm(): value_set = value.py__call__(arguments=arguments) debug.dbg('execute result: %s in %s', value_set, value) return value_set # mypy doesn't suppport decorated propeties (https://github.com/python/mypy/issues/1362) @property # type: ignore[misc] @inference_state_function_cache() def builtins_module(self): module_name = 'builtins' builtins_module, = self.import_module((module_name,), sys_path=[]) return builtins_module @property # type: ignore[misc] @inference_state_function_cache() def typing_module(self): typing_module, = self.import_module(('typing',)) return typing_module def reset_recursion_limitations(self): self.recursion_detector = recursion.RecursionDetector() self.execution_recursion_detector = recursion.ExecutionRecursionDetector(self) def get_sys_path(self, **kwargs): """Convenience function""" return self.project._get_sys_path(self, **kwargs) def infer(self, context, name): def_ = name.get_definition(import_name_always=True) if def_ is not None: type_ = def_.type is_classdef = type_ == 'classdef' if is_classdef or type_ == 'funcdef': if is_classdef: c = ClassValue(self, context, name.parent) else: c = FunctionValue.from_context(context, name.parent) return ValueSet([c]) if type_ == 'expr_stmt': is_simple_name = name.parent.type not in ('power', 'trailer') if is_simple_name: return infer_expr_stmt(context, def_, name) if type_ == 'for_stmt': container_types = context.infer_node(def_.children[3]) cn = ContextualizedNode(context, def_.children[3]) for_types = iterate_values(container_types, cn) n = TreeNameDefinition(context, name) return check_tuple_assignments(n, for_types) if type_ in ('import_from', 'import_name'): return imports.infer_import(context, name) if type_ == 'with_stmt': return tree_name_to_values(self, context, name) elif type_ == 'param': return context.py__getattribute__(name.value, position=name.end_pos) elif type_ == 'namedexpr_test': return context.infer_node(def_) else: result = follow_error_node_imports_if_possible(context, name) if result is not None: return result return helpers.infer_call_of_leaf(context, name) def parse_and_get_code(self, code=None, path=None, use_latest_grammar=False, file_io=None, **kwargs): if code is None: if file_io is None: file_io = FileIO(path) code = file_io.read() # We cannot just use parso, because it doesn't use errors='replace'. code = parso.python_bytes_to_unicode(code, encoding='utf-8', errors='replace') if len(code) > settings._cropped_file_size: code = code[:settings._cropped_file_size] grammar = self.latest_grammar if use_latest_grammar else self.grammar return grammar.parse(code=code, path=path, file_io=file_io, **kwargs), code def parse(self, *args, **kwargs): return self.parse_and_get_code(*args, **kwargs)[0]