mirror of https://github.com/morpheus65535/bazarr
153 lines
5.1 KiB
Python
153 lines
5.1 KiB
Python
"""
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Config module.
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"""
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from importlib import import_module
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from typing import Any, List
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from rebulk import Rebulk
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_regex_prefix = 're:'
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_import_prefix = 'import:'
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_import_cache = {}
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_eval_prefix = 'eval:'
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_eval_cache = {}
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_pattern_types = ('regex', 'string')
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_default_module_names = {
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'validator': 'guessit.rules.common.validators',
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'formatter': 'guessit.rules.common.formatters'
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}
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def _process_option(name: str, value: Any):
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if name in ('validator', 'conflict_solver', 'formatter'):
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if isinstance(value, dict):
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return {item_key: _process_option(name, item_value) for item_key, item_value in value.items()}
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if value is not None:
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return _process_option_executable(value, _default_module_names.get(name))
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return value
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def _import(value: str, default_module_name=None):
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if '.' in value:
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module_name, target = value.rsplit(':', 1)
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else:
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module_name = default_module_name
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target = value
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import_id = module_name + ":" + target
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if import_id in _import_cache:
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return _import_cache[import_id]
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mod = import_module(module_name)
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imported = mod
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for item in target.split("."):
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imported = getattr(imported, item)
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_import_cache[import_id] = imported
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return imported
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def _eval(value: str):
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compiled = _eval_cache.get(value)
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if not compiled:
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compiled = compile(value, '<string>', 'eval')
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return eval(compiled) # pylint:disable=eval-used
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def _process_option_executable(value: str, default_module_name=None):
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if value.startswith(_import_prefix):
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value = value[len(_import_prefix):]
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return _import(value, default_module_name)
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if value.startswith(_eval_prefix):
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value = value[len(_eval_prefix):]
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return _eval(value)
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if value.startswith('lambda ') or value.startswith('lambda:'):
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return _eval(value)
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return value
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def _process_callable_entry(callable_spec: str, rebulk: Rebulk, entry: dict):
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_process_option_executable(callable_spec)(rebulk, **entry)
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def _build_entry_decl(entry, options, value):
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entry_decl = dict(options.get(None, {}))
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if not value.startswith('_'):
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entry_decl['value'] = value
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if isinstance(entry, str):
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if entry.startswith(_regex_prefix):
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entry_decl["regex"] = [entry[len(_regex_prefix):]]
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else:
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entry_decl["string"] = [entry]
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else:
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entry_decl.update(entry)
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if "pattern" in entry_decl:
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legacy_pattern = entry.pop("pattern")
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if legacy_pattern.startswith(_regex_prefix):
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entry_decl["regex"] = [legacy_pattern[len(_regex_prefix):]]
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else:
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entry_decl["string"] = [legacy_pattern]
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return entry_decl
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def load_patterns(rebulk: Rebulk,
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pattern_type: str,
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patterns: List[str],
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options: dict = None):
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"""
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Load patterns for a prepared config entry
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:param rebulk: Rebulk builder to use.
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:param pattern_type: Pattern type.
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:param patterns: Patterns
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:param options: kwargs options to pass to rebulk pattern function.
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:return:
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"""
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default_options = options.get(None) if options else None
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item_options = dict(default_options) if default_options else {}
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pattern_type_option = options.get(pattern_type)
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if pattern_type_option:
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item_options.update(pattern_type_option)
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item_options = {name: _process_option(name, value) for name, value in item_options.items()}
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getattr(rebulk, pattern_type)(*patterns, **item_options)
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def load_config_patterns(rebulk: Rebulk,
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config: dict,
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options: dict = None):
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"""
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Load patterns defined in given config.
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:param rebulk: Rebulk builder to use.
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:param config: dict containing pattern definition.
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:param options: Additional pattern options to use.
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:type options: Dict[Dict[str, str]] A dict where key is the pattern type (regex, string, functional) and value is
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the default kwargs options to pass.
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:return:
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"""
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if options is None:
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options = {}
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for value, raw_entries in config.items():
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entries = raw_entries if isinstance(raw_entries, list) else [raw_entries]
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for entry in entries:
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if isinstance(entry, dict) and "callable" in entry.keys():
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_process_callable_entry(entry.pop("callable"), rebulk, entry)
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continue
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entry_decl = _build_entry_decl(entry, options, value)
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for pattern_type in _pattern_types:
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patterns = entry_decl.get(pattern_type)
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if not patterns:
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continue
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if not isinstance(patterns, list):
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patterns = [patterns]
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patterns_entry_decl = dict(entry_decl)
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for pattern_type_to_remove in _pattern_types:
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patterns_entry_decl.pop(pattern_type_to_remove, None)
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current_pattern_options = dict(options)
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current_pattern_options[None] = patterns_entry_decl
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load_patterns(rebulk, pattern_type, patterns, current_pattern_options)
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