""" The config module holds package-wide configurables and provides a uniform API for working with them. Overview ======== This module supports the following requirements: - options are referenced using keys in dot.notation, e.g. "x.y.option - z". - keys are case-insensitive. - functions should accept partial/regex keys, when unambiguous. - options can be registered by modules at import time. - options can be registered at init-time (via core.config_init) - options have a default value, and (optionally) a description and validation function associated with them. - options can be deprecated, in which case referencing them should produce a warning. - deprecated options can optionally be rerouted to a replacement so that accessing a deprecated option reroutes to a differently named option. - options can be reset to their default value. - all option can be reset to their default value at once. - all options in a certain sub - namespace can be reset at once. - the user can set / get / reset or ask for the description of an option. - a developer can register and mark an option as deprecated. - you can register a callback to be invoked when the option value is set or reset. Changing the stored value is considered misuse, but is not verboten. Implementation ============== - Data is stored using nested dictionaries, and should be accessed through the provided API. - "Registered options" and "Deprecated options" have metadata associated with them, which are stored in auxiliary dictionaries keyed on the fully-qualified key, e.g. "x.y.z.option". - the config_init module is imported by the package's __init__.py file. placing any register_option() calls there will ensure those options are available as soon as pandas is loaded. If you use register_option in a module, it will only be available after that module is imported, which you should be aware of. - `config_prefix` is a context_manager (for use with the `with` keyword) which can save developers some typing, see the docstring. """ from __future__ import annotations from contextlib import ( ContextDecorator, contextmanager, ) import re from typing import ( TYPE_CHECKING, Any, Callable, Generic, NamedTuple, cast, ) import warnings from pandas._typing import ( F, T, ) from pandas.util._exceptions import find_stack_level if TYPE_CHECKING: from collections.abc import ( Generator, Iterable, ) class DeprecatedOption(NamedTuple): key: str msg: str | None rkey: str | None removal_ver: str | None class RegisteredOption(NamedTuple): key: str defval: object doc: str validator: Callable[[object], Any] | None cb: Callable[[str], Any] | None # holds deprecated option metadata _deprecated_options: dict[str, DeprecatedOption] = {} # holds registered option metadata _registered_options: dict[str, RegisteredOption] = {} # holds the current values for registered options _global_config: dict[str, Any] = {} # keys which have a special meaning _reserved_keys: list[str] = ["all"] class OptionError(AttributeError, KeyError): """ Exception raised for pandas.options. Backwards compatible with KeyError checks. Examples -------- >>> pd.options.context Traceback (most recent call last): OptionError: No such option """ # # User API def _get_single_key(pat: str, silent: bool) -> str: keys = _select_options(pat) if len(keys) == 0: if not silent: _warn_if_deprecated(pat) raise OptionError(f"No such keys(s): {repr(pat)}") if len(keys) > 1: raise OptionError("Pattern matched multiple keys") key = keys[0] if not silent: _warn_if_deprecated(key) key = _translate_key(key) return key def _get_option(pat: str, silent: bool = False) -> Any: key = _get_single_key(pat, silent) # walk the nested dict root, k = _get_root(key) return root[k] def _set_option(*args, **kwargs) -> None: # must at least 1 arg deal with constraints later nargs = len(args) if not nargs or nargs % 2 != 0: raise ValueError("Must provide an even number of non-keyword arguments") # default to false silent = kwargs.pop("silent", False) if kwargs: kwarg = next(iter(kwargs.keys())) raise TypeError(f'_set_option() got an unexpected keyword argument "{kwarg}"') for k, v in zip(args[::2], args[1::2]): key = _get_single_key(k, silent) o = _get_registered_option(key) if o and o.validator: o.validator(v) # walk the nested dict root, k_root = _get_root(key) root[k_root] = v if o.cb: if silent: with warnings.catch_warnings(record=True): o.cb(key) else: o.cb(key) def _describe_option(pat: str = "", _print_desc: bool = True) -> str | None: keys = _select_options(pat) if len(keys) == 0: raise OptionError("No such keys(s)") s = "\n".join([_build_option_description(k) for k in keys]) if _print_desc: print(s) return None return s def _reset_option(pat: str, silent: bool = False) -> None: keys = _select_options(pat) if len(keys) == 0: raise OptionError("No such keys(s)") if len(keys) > 1 and len(pat) < 4 and pat != "all": raise ValueError( "You must specify at least 4 characters when " "resetting multiple keys, use the special keyword " '"all" to reset all the options to their default value' ) for k in keys: _set_option(k, _registered_options[k].defval, silent=silent) def get_default_val(pat: str): key = _get_single_key(pat, silent=True) return _get_registered_option(key).defval class DictWrapper: """provide attribute-style access to a nested dict""" d: dict[str, Any] def __init__(self, d: dict[str, Any], prefix: str = "") -> None: object.__setattr__(self, "d", d) object.__setattr__(self, "prefix", prefix) def __setattr__(self, key: str, val: Any) -> None: prefix = object.__getattribute__(self, "prefix") if prefix: prefix += "." prefix += key # you can't set new keys # can you can't overwrite subtrees if key in self.d and not isinstance(self.d[key], dict): _set_option(prefix, val) else: raise OptionError("You can only set the value of existing options") def __getattr__(self, key: str): prefix = object.__getattribute__(self, "prefix") if prefix: prefix += "." prefix += key try: v = object.__getattribute__(self, "d")[key] except KeyError as err: raise OptionError("No such option") from err if isinstance(v, dict): return DictWrapper(v, prefix) else: return _get_option(prefix) def __dir__(self) -> list[str]: return list(self.d.keys()) # For user convenience, we'd like to have the available options described # in the docstring. For dev convenience we'd like to generate the docstrings # dynamically instead of maintaining them by hand. To this, we use the # class below which wraps functions inside a callable, and converts # __doc__ into a property function. The doctsrings below are templates # using the py2.6+ advanced formatting syntax to plug in a concise list # of options, and option descriptions. class CallableDynamicDoc(Generic[T]): def __init__(self, func: Callable[..., T], doc_tmpl: str) -> None: self.__doc_tmpl__ = doc_tmpl self.__func__ = func def __call__(self, *args, **kwds) -> T: return self.__func__(*args, **kwds) # error: Signature of "__doc__" incompatible with supertype "object" @property def __doc__(self) -> str: # type: ignore[override] opts_desc = _describe_option("all", _print_desc=False) opts_list = pp_options_list(list(_registered_options.keys())) return self.__doc_tmpl__.format(opts_desc=opts_desc, opts_list=opts_list) _get_option_tmpl = """ get_option(pat) Retrieves the value of the specified option. Available options: {opts_list} Parameters ---------- pat : str Regexp which should match a single option. Note: partial matches are supported for convenience, but unless you use the full option name (e.g. x.y.z.option_name), your code may break in future versions if new options with similar names are introduced. Returns ------- result : the value of the option Raises ------ OptionError : if no such option exists Notes ----- Please reference the :ref:`User Guide ` for more information. The available options with its descriptions: {opts_desc} Examples -------- >>> pd.get_option('display.max_columns') # doctest: +SKIP 4 """ _set_option_tmpl = """ set_option(pat, value) Sets the value of the specified option. Available options: {opts_list} Parameters ---------- pat : str Regexp which should match a single option. Note: partial matches are supported for convenience, but unless you use the full option name (e.g. x.y.z.option_name), your code may break in future versions if new options with similar names are introduced. value : object New value of option. Returns ------- None Raises ------ OptionError if no such option exists Notes ----- Please reference the :ref:`User Guide ` for more information. The available options with its descriptions: {opts_desc} Examples -------- >>> pd.set_option('display.max_columns', 4) >>> df = pd.DataFrame([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]]) >>> df 0 1 ... 3 4 0 1 2 ... 4 5 1 6 7 ... 9 10 [2 rows x 5 columns] >>> pd.reset_option('display.max_columns') """ _describe_option_tmpl = """ describe_option(pat, _print_desc=False) Prints the description for one or more registered options. Call with no arguments to get a listing for all registered options. Available options: {opts_list} Parameters ---------- pat : str Regexp pattern. All matching keys will have their description displayed. _print_desc : bool, default True If True (default) the description(s) will be printed to stdout. Otherwise, the description(s) will be returned as a unicode string (for testing). Returns ------- None by default, the description(s) as a unicode string if _print_desc is False Notes ----- Please reference the :ref:`User Guide ` for more information. The available options with its descriptions: {opts_desc} Examples -------- >>> pd.describe_option('display.max_columns') # doctest: +SKIP display.max_columns : int If max_cols is exceeded, switch to truncate view... """ _reset_option_tmpl = """ reset_option(pat) Reset one or more options to their default value. Pass "all" as argument to reset all options. Available options: {opts_list} Parameters ---------- pat : str/regex If specified only options matching `prefix*` will be reset. Note: partial matches are supported for convenience, but unless you use the full option name (e.g. x.y.z.option_name), your code may break in future versions if new options with similar names are introduced. Returns ------- None Notes ----- Please reference the :ref:`User Guide ` for more information. The available options with its descriptions: {opts_desc} Examples -------- >>> pd.reset_option('display.max_columns') # doctest: +SKIP """ # bind the functions with their docstrings into a Callable # and use that as the functions exposed in pd.api get_option = CallableDynamicDoc(_get_option, _get_option_tmpl) set_option = CallableDynamicDoc(_set_option, _set_option_tmpl) reset_option = CallableDynamicDoc(_reset_option, _reset_option_tmpl) describe_option = CallableDynamicDoc(_describe_option, _describe_option_tmpl) options = DictWrapper(_global_config) # # Functions for use by pandas developers, in addition to User - api class option_context(ContextDecorator): """ Context manager to temporarily set options in the `with` statement context. You need to invoke as ``option_context(pat, val, [(pat, val), ...])``. Examples -------- >>> from pandas import option_context >>> with option_context('display.max_rows', 10, 'display.max_columns', 5): ... pass """ def __init__(self, *args) -> None: if len(args) % 2 != 0 or len(args) < 2: raise ValueError( "Need to invoke as option_context(pat, val, [(pat, val), ...])." ) self.ops = list(zip(args[::2], args[1::2])) def __enter__(self) -> None: self.undo = [(pat, _get_option(pat)) for pat, val in self.ops] for pat, val in self.ops: _set_option(pat, val, silent=True) def __exit__(self, *args) -> None: if self.undo: for pat, val in self.undo: _set_option(pat, val, silent=True) def register_option( key: str, defval: object, doc: str = "", validator: Callable[[object], Any] | None = None, cb: Callable[[str], Any] | None = None, ) -> None: """ Register an option in the package-wide pandas config object Parameters ---------- key : str Fully-qualified key, e.g. "x.y.option - z". defval : object Default value of the option. doc : str Description of the option. validator : Callable, optional Function of a single argument, should raise `ValueError` if called with a value which is not a legal value for the option. cb a function of a single argument "key", which is called immediately after an option value is set/reset. key is the full name of the option. Raises ------ ValueError if `validator` is specified and `defval` is not a valid value. """ import keyword import tokenize key = key.lower() if key in _registered_options: raise OptionError(f"Option '{key}' has already been registered") if key in _reserved_keys: raise OptionError(f"Option '{key}' is a reserved key") # the default value should be legal if validator: validator(defval) # walk the nested dict, creating dicts as needed along the path path = key.split(".") for k in path: if not re.match("^" + tokenize.Name + "$", k): raise ValueError(f"{k} is not a valid identifier") if keyword.iskeyword(k): raise ValueError(f"{k} is a python keyword") cursor = _global_config msg = "Path prefix to option '{option}' is already an option" for i, p in enumerate(path[:-1]): if not isinstance(cursor, dict): raise OptionError(msg.format(option=".".join(path[:i]))) if p not in cursor: cursor[p] = {} cursor = cursor[p] if not isinstance(cursor, dict): raise OptionError(msg.format(option=".".join(path[:-1]))) cursor[path[-1]] = defval # initialize # save the option metadata _registered_options[key] = RegisteredOption( key=key, defval=defval, doc=doc, validator=validator, cb=cb ) def deprecate_option( key: str, msg: str | None = None, rkey: str | None = None, removal_ver: str | None = None, ) -> None: """ Mark option `key` as deprecated, if code attempts to access this option, a warning will be produced, using `msg` if given, or a default message if not. if `rkey` is given, any access to the key will be re-routed to `rkey`. Neither the existence of `key` nor that if `rkey` is checked. If they do not exist, any subsequence access will fail as usual, after the deprecation warning is given. Parameters ---------- key : str Name of the option to be deprecated. must be a fully-qualified option name (e.g "x.y.z.rkey"). msg : str, optional Warning message to output when the key is referenced. if no message is given a default message will be emitted. rkey : str, optional Name of an option to reroute access to. If specified, any referenced `key` will be re-routed to `rkey` including set/get/reset. rkey must be a fully-qualified option name (e.g "x.y.z.rkey"). used by the default message if no `msg` is specified. removal_ver : str, optional Specifies the version in which this option will be removed. used by the default message if no `msg` is specified. Raises ------ OptionError If the specified key has already been deprecated. """ key = key.lower() if key in _deprecated_options: raise OptionError(f"Option '{key}' has already been defined as deprecated.") _deprecated_options[key] = DeprecatedOption(key, msg, rkey, removal_ver) # # functions internal to the module def _select_options(pat: str) -> list[str]: """ returns a list of keys matching `pat` if pat=="all", returns all registered options """ # short-circuit for exact key if pat in _registered_options: return [pat] # else look through all of them keys = sorted(_registered_options.keys()) if pat == "all": # reserved key return keys return [k for k in keys if re.search(pat, k, re.I)] def _get_root(key: str) -> tuple[dict[str, Any], str]: path = key.split(".") cursor = _global_config for p in path[:-1]: cursor = cursor[p] return cursor, path[-1] def _is_deprecated(key: str) -> bool: """Returns True if the given option has been deprecated""" key = key.lower() return key in _deprecated_options def _get_deprecated_option(key: str): """ Retrieves the metadata for a deprecated option, if `key` is deprecated. Returns ------- DeprecatedOption (namedtuple) if key is deprecated, None otherwise """ try: d = _deprecated_options[key] except KeyError: return None else: return d def _get_registered_option(key: str): """ Retrieves the option metadata if `key` is a registered option. Returns ------- RegisteredOption (namedtuple) if key is deprecated, None otherwise """ return _registered_options.get(key) def _translate_key(key: str) -> str: """ if key id deprecated and a replacement key defined, will return the replacement key, otherwise returns `key` as - is """ d = _get_deprecated_option(key) if d: return d.rkey or key else: return key def _warn_if_deprecated(key: str) -> bool: """ Checks if `key` is a deprecated option and if so, prints a warning. Returns ------- bool - True if `key` is deprecated, False otherwise. """ d = _get_deprecated_option(key) if d: if d.msg: warnings.warn( d.msg, FutureWarning, stacklevel=find_stack_level(), ) else: msg = f"'{key}' is deprecated" if d.removal_ver: msg += f" and will be removed in {d.removal_ver}" if d.rkey: msg += f", please use '{d.rkey}' instead." else: msg += ", please refrain from using it." warnings.warn(msg, FutureWarning, stacklevel=find_stack_level()) return True return False def _build_option_description(k: str) -> str: """Builds a formatted description of a registered option and prints it""" o = _get_registered_option(k) d = _get_deprecated_option(k) s = f"{k} " if o.doc: s += "\n".join(o.doc.strip().split("\n")) else: s += "No description available." if o: s += f"\n [default: {o.defval}] [currently: {_get_option(k, True)}]" if d: rkey = d.rkey or "" s += "\n (Deprecated" s += f", use `{rkey}` instead." s += ")" return s def pp_options_list(keys: Iterable[str], width: int = 80, _print: bool = False): """Builds a concise listing of available options, grouped by prefix""" from itertools import groupby from textwrap import wrap def pp(name: str, ks: Iterable[str]) -> list[str]: pfx = "- " + name + ".[" if name else "" ls = wrap( ", ".join(ks), width, initial_indent=pfx, subsequent_indent=" ", break_long_words=False, ) if ls and ls[-1] and name: ls[-1] = ls[-1] + "]" return ls ls: list[str] = [] singles = [x for x in sorted(keys) if x.find(".") < 0] if singles: ls += pp("", singles) keys = [x for x in keys if x.find(".") >= 0] for k, g in groupby(sorted(keys), lambda x: x[: x.rfind(".")]): ks = [x[len(k) + 1 :] for x in list(g)] ls += pp(k, ks) s = "\n".join(ls) if _print: print(s) else: return s # # helpers @contextmanager def config_prefix(prefix: str) -> Generator[None, None, None]: """ contextmanager for multiple invocations of API with a common prefix supported API functions: (register / get / set )__option Warning: This is not thread - safe, and won't work properly if you import the API functions into your module using the "from x import y" construct. Example ------- import pandas._config.config as cf with cf.config_prefix("display.font"): cf.register_option("color", "red") cf.register_option("size", " 5 pt") cf.set_option(size, " 6 pt") cf.get_option(size) ... etc' will register options "display.font.color", "display.font.size", set the value of "display.font.size"... and so on. """ # Note: reset_option relies on set_option, and on key directly # it does not fit in to this monkey-patching scheme global register_option, get_option, set_option def wrap(func: F) -> F: def inner(key: str, *args, **kwds): pkey = f"{prefix}.{key}" return func(pkey, *args, **kwds) return cast(F, inner) _register_option = register_option _get_option = get_option _set_option = set_option set_option = wrap(set_option) get_option = wrap(get_option) register_option = wrap(register_option) try: yield finally: set_option = _set_option get_option = _get_option register_option = _register_option # These factories and methods are handy for use as the validator # arg in register_option def is_type_factory(_type: type[Any]) -> Callable[[Any], None]: """ Parameters ---------- `_type` - a type to be compared against (e.g. type(x) == `_type`) Returns ------- validator - a function of a single argument x , which raises ValueError if type(x) is not equal to `_type` """ def inner(x) -> None: if type(x) != _type: raise ValueError(f"Value must have type '{_type}'") return inner def is_instance_factory(_type) -> Callable[[Any], None]: """ Parameters ---------- `_type` - the type to be checked against Returns ------- validator - a function of a single argument x , which raises ValueError if x is not an instance of `_type` """ if isinstance(_type, (tuple, list)): _type = tuple(_type) type_repr = "|".join(map(str, _type)) else: type_repr = f"'{_type}'" def inner(x) -> None: if not isinstance(x, _type): raise ValueError(f"Value must be an instance of {type_repr}") return inner def is_one_of_factory(legal_values) -> Callable[[Any], None]: callables = [c for c in legal_values if callable(c)] legal_values = [c for c in legal_values if not callable(c)] def inner(x) -> None: if x not in legal_values: if not any(c(x) for c in callables): uvals = [str(lval) for lval in legal_values] pp_values = "|".join(uvals) msg = f"Value must be one of {pp_values}" if len(callables): msg += " or a callable" raise ValueError(msg) return inner def is_nonnegative_int(value: object) -> None: """ Verify that value is None or a positive int. Parameters ---------- value : None or int The `value` to be checked. Raises ------ ValueError When the value is not None or is a negative integer """ if value is None: return elif isinstance(value, int): if value >= 0: return msg = "Value must be a nonnegative integer or None" raise ValueError(msg) # common type validators, for convenience # usage: register_option(... , validator = is_int) is_int = is_type_factory(int) is_bool = is_type_factory(bool) is_float = is_type_factory(float) is_str = is_type_factory(str) is_text = is_instance_factory((str, bytes)) def is_callable(obj) -> bool: """ Parameters ---------- `obj` - the object to be checked Returns ------- validator - returns True if object is callable raises ValueError otherwise. """ if not callable(obj): raise ValueError("Value must be a callable") return True