import copy import sys import re import os from itertools import chain from contextlib import contextmanager from parso.python import tree from jedi._compatibility import unicode def is_stdlib_path(path): # Python standard library paths look like this: # /usr/lib/python3.5/... # TODO The implementation below is probably incorrect and not complete. if 'dist-packages' in path or 'site-packages' in path: return False base_path = os.path.join(sys.prefix, 'lib', 'python') return bool(re.match(re.escape(base_path) + r'\d.\d', path)) def deep_ast_copy(obj): """ Much, much faster than copy.deepcopy, but just for parser tree nodes. """ # If it's already in the cache, just return it. new_obj = copy.copy(obj) # Copy children new_children = [] for child in obj.children: if isinstance(child, tree.Leaf): new_child = copy.copy(child) new_child.parent = new_obj else: new_child = deep_ast_copy(child) new_child.parent = new_obj new_children.append(new_child) new_obj.children = new_children return new_obj def infer_call_of_leaf(context, leaf, cut_own_trailer=False): """ Creates a "call" node that consist of all ``trailer`` and ``power`` objects. E.g. if you call it with ``append``:: list([]).append(3) or None You would get a node with the content ``list([]).append`` back. This generates a copy of the original ast node. If you're using the leaf, e.g. the bracket `)` it will return ``list([])``. We use this function for two purposes. Given an expression ``bar.foo``, we may want to - infer the type of ``foo`` to offer completions after foo - infer the type of ``bar`` to be able to jump to the definition of foo The option ``cut_own_trailer`` must be set to true for the second purpose. """ trailer = leaf.parent if trailer.type == 'fstring': from jedi.inference import compiled return compiled.get_string_value_set(context.inference_state) # The leaf may not be the last or first child, because there exist three # different trailers: `( x )`, `[ x ]` and `.x`. In the first two examples # we should not match anything more than x. if trailer.type != 'trailer' or leaf not in (trailer.children[0], trailer.children[-1]): if leaf == ':': # Basically happens with foo[:] when the cursor is on the colon from jedi.inference.base_value import NO_VALUES return NO_VALUES if trailer.type == 'atom': return context.infer_node(trailer) return context.infer_node(leaf) power = trailer.parent index = power.children.index(trailer) if cut_own_trailer: cut = index else: cut = index + 1 if power.type == 'error_node': start = index while True: start -= 1 base = power.children[start] if base.type != 'trailer': break trailers = power.children[start + 1:cut] else: base = power.children[0] trailers = power.children[1:cut] if base == 'await': base = trailers[0] trailers = trailers[1:] values = context.infer_node(base) from jedi.inference.syntax_tree import infer_trailer for trailer in trailers: values = infer_trailer(context, values, trailer) return values def get_names_of_node(node): try: children = node.children except AttributeError: if node.type == 'name': return [node] else: return [] else: return list(chain.from_iterable(get_names_of_node(c) for c in children)) def is_string(value): if value.inference_state.environment.version_info.major == 2: str_classes = (unicode, bytes) else: str_classes = (unicode,) return value.is_compiled() and isinstance(value.get_safe_value(default=None), str_classes) def is_literal(value): return is_number(value) or is_string(value) def _get_safe_value_or_none(value, accept): value = value.get_safe_value(default=None) if isinstance(value, accept): return value def get_int_or_none(value): return _get_safe_value_or_none(value, int) def get_str_or_none(value): return _get_safe_value_or_none(value, (bytes, unicode)) def is_number(value): return _get_safe_value_or_none(value, (int, float)) is not None class SimpleGetItemNotFound(Exception): pass @contextmanager def reraise_getitem_errors(*exception_classes): try: yield except exception_classes as e: raise SimpleGetItemNotFound(e) def parse_dotted_names(nodes, is_import_from, until_node=None): level = 0 names = [] for node in nodes[1:]: if node in ('.', '...'): if not names: level += len(node.value) elif node.type == 'dotted_name': for n in node.children[::2]: names.append(n) if n is until_node: break else: continue break elif node.type == 'name': names.append(node) if node is until_node: break elif node == ',': if not is_import_from: names = [] else: # Here if the keyword `import` comes along it stops checking # for names. break return level, names def values_from_qualified_names(inference_state, *names): return inference_state.import_module(names[:-1]).py__getattribute__(names[-1]) def is_big_annoying_library(context): string_names = context.get_root_context().string_names if string_names is None: return False # Especially pandas and tensorflow are huge complicated Python libraries # that get even slower than they already are when Jedi tries to undrstand # dynamic features like decorators, ifs and other stuff. return string_names[0] in ('pandas', 'numpy', 'tensorflow', 'matplotlib')