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865 lines
23 KiB
Python
865 lines
23 KiB
Python
"""
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The config module holds package-wide configurables and provides
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a uniform API for working with them.
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Overview
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========
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This module supports the following requirements:
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- options are referenced using keys in dot.notation, e.g. "x.y.option - z".
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- keys are case-insensitive.
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- functions should accept partial/regex keys, when unambiguous.
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- options can be registered by modules at import time.
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- options can be registered at init-time (via core.config_init)
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- options have a default value, and (optionally) a description and
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validation function associated with them.
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- options can be deprecated, in which case referencing them
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should produce a warning.
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- deprecated options can optionally be rerouted to a replacement
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so that accessing a deprecated option reroutes to a differently
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named option.
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- options can be reset to their default value.
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- all option can be reset to their default value at once.
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- all options in a certain sub - namespace can be reset at once.
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- the user can set / get / reset or ask for the description of an option.
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- a developer can register and mark an option as deprecated.
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- you can register a callback to be invoked when the option value
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is set or reset. Changing the stored value is considered misuse, but
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is not verboten.
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Implementation
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==============
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- Data is stored using nested dictionaries, and should be accessed
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through the provided API.
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- "Registered options" and "Deprecated options" have metadata associated
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with them, which are stored in auxiliary dictionaries keyed on the
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fully-qualified key, e.g. "x.y.z.option".
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- the config_init module is imported by the package's __init__.py file.
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placing any register_option() calls there will ensure those options
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are available as soon as pandas is loaded. If you use register_option
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in a module, it will only be available after that module is imported,
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which you should be aware of.
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- `config_prefix` is a context_manager (for use with the `with` keyword)
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which can save developers some typing, see the docstring.
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"""
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from collections import namedtuple
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from contextlib import ContextDecorator, contextmanager
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import re
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from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Type, cast
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import warnings
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from pandas._typing import F
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DeprecatedOption = namedtuple("DeprecatedOption", "key msg rkey removal_ver")
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RegisteredOption = namedtuple("RegisteredOption", "key defval doc validator cb")
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# holds deprecated option metadata
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_deprecated_options: Dict[str, DeprecatedOption] = {}
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# holds registered option metadata
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_registered_options: Dict[str, RegisteredOption] = {}
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# holds the current values for registered options
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_global_config: Dict[str, Any] = {}
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# keys which have a special meaning
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_reserved_keys: List[str] = ["all"]
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class OptionError(AttributeError, KeyError):
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"""
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Exception for pandas.options, backwards compatible with KeyError
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checks
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"""
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#
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# User API
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def _get_single_key(pat: str, silent: bool) -> str:
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keys = _select_options(pat)
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if len(keys) == 0:
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if not silent:
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_warn_if_deprecated(pat)
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raise OptionError(f"No such keys(s): {repr(pat)}")
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if len(keys) > 1:
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raise OptionError("Pattern matched multiple keys")
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key = keys[0]
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if not silent:
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_warn_if_deprecated(key)
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key = _translate_key(key)
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return key
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def _get_option(pat: str, silent: bool = False):
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key = _get_single_key(pat, silent)
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# walk the nested dict
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root, k = _get_root(key)
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return root[k]
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def _set_option(*args, **kwargs) -> None:
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# must at least 1 arg deal with constraints later
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nargs = len(args)
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if not nargs or nargs % 2 != 0:
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raise ValueError("Must provide an even number of non-keyword arguments")
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# default to false
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silent = kwargs.pop("silent", False)
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if kwargs:
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kwarg = list(kwargs.keys())[0]
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raise TypeError(f'_set_option() got an unexpected keyword argument "{kwarg}"')
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for k, v in zip(args[::2], args[1::2]):
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key = _get_single_key(k, silent)
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o = _get_registered_option(key)
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if o and o.validator:
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o.validator(v)
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# walk the nested dict
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root, k = _get_root(key)
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root[k] = v
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if o.cb:
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if silent:
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with warnings.catch_warnings(record=True):
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o.cb(key)
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else:
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o.cb(key)
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def _describe_option(pat: str = "", _print_desc: bool = True):
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keys = _select_options(pat)
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if len(keys) == 0:
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raise OptionError("No such keys(s)")
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s = "\n".join([_build_option_description(k) for k in keys])
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if _print_desc:
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print(s)
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else:
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return s
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def _reset_option(pat: str, silent: bool = False) -> None:
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keys = _select_options(pat)
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if len(keys) == 0:
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raise OptionError("No such keys(s)")
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if len(keys) > 1 and len(pat) < 4 and pat != "all":
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raise ValueError(
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"You must specify at least 4 characters when "
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"resetting multiple keys, use the special keyword "
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'"all" to reset all the options to their default value'
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)
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for k in keys:
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_set_option(k, _registered_options[k].defval, silent=silent)
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def get_default_val(pat: str):
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key = _get_single_key(pat, silent=True)
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return _get_registered_option(key).defval
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class DictWrapper:
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""" provide attribute-style access to a nested dict"""
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def __init__(self, d: Dict[str, Any], prefix: str = ""):
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object.__setattr__(self, "d", d)
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object.__setattr__(self, "prefix", prefix)
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def __setattr__(self, key: str, val: Any) -> None:
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prefix = object.__getattribute__(self, "prefix")
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if prefix:
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prefix += "."
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prefix += key
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# you can't set new keys
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# can you can't overwrite subtrees
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if key in self.d and not isinstance(self.d[key], dict):
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_set_option(prefix, val)
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else:
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raise OptionError("You can only set the value of existing options")
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def __getattr__(self, key: str):
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prefix = object.__getattribute__(self, "prefix")
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if prefix:
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prefix += "."
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prefix += key
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try:
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v = object.__getattribute__(self, "d")[key]
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except KeyError as err:
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raise OptionError("No such option") from err
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if isinstance(v, dict):
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return DictWrapper(v, prefix)
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else:
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return _get_option(prefix)
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def __dir__(self) -> Iterable[str]:
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return list(self.d.keys())
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# For user convenience, we'd like to have the available options described
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# in the docstring. For dev convenience we'd like to generate the docstrings
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# dynamically instead of maintaining them by hand. To this, we use the
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# class below which wraps functions inside a callable, and converts
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# __doc__ into a property function. The doctsrings below are templates
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# using the py2.6+ advanced formatting syntax to plug in a concise list
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# of options, and option descriptions.
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class CallableDynamicDoc:
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def __init__(self, func, doc_tmpl):
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self.__doc_tmpl__ = doc_tmpl
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self.__func__ = func
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def __call__(self, *args, **kwds):
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return self.__func__(*args, **kwds)
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@property
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def __doc__(self):
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opts_desc = _describe_option("all", _print_desc=False)
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opts_list = pp_options_list(list(_registered_options.keys()))
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return self.__doc_tmpl__.format(opts_desc=opts_desc, opts_list=opts_list)
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_get_option_tmpl = """
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get_option(pat)
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Retrieves the value of the specified option.
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Available options:
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{opts_list}
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Parameters
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----------
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pat : str
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Regexp which should match a single option.
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Note: partial matches are supported for convenience, but unless you use the
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full option name (e.g. x.y.z.option_name), your code may break in future
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versions if new options with similar names are introduced.
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Returns
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-------
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result : the value of the option
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Raises
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------
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OptionError : if no such option exists
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Notes
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-----
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The available options with its descriptions:
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{opts_desc}
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"""
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_set_option_tmpl = """
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set_option(pat, value)
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Sets the value of the specified option.
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Available options:
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{opts_list}
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Parameters
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----------
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pat : str
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Regexp which should match a single option.
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Note: partial matches are supported for convenience, but unless you use the
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full option name (e.g. x.y.z.option_name), your code may break in future
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versions if new options with similar names are introduced.
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value : object
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New value of option.
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Returns
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-------
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None
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Raises
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------
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OptionError if no such option exists
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Notes
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-----
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The available options with its descriptions:
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{opts_desc}
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"""
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_describe_option_tmpl = """
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describe_option(pat, _print_desc=False)
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Prints the description for one or more registered options.
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Call with not arguments to get a listing for all registered options.
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Available options:
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{opts_list}
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Parameters
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----------
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pat : str
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Regexp pattern. All matching keys will have their description displayed.
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_print_desc : bool, default True
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If True (default) the description(s) will be printed to stdout.
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Otherwise, the description(s) will be returned as a unicode string
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(for testing).
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Returns
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-------
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None by default, the description(s) as a unicode string if _print_desc
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is False
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Notes
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-----
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The available options with its descriptions:
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{opts_desc}
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"""
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_reset_option_tmpl = """
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reset_option(pat)
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Reset one or more options to their default value.
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Pass "all" as argument to reset all options.
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Available options:
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{opts_list}
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Parameters
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----------
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pat : str/regex
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If specified only options matching `prefix*` will be reset.
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Note: partial matches are supported for convenience, but unless you
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use the full option name (e.g. x.y.z.option_name), your code may break
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in future versions if new options with similar names are introduced.
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Returns
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-------
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None
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Notes
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-----
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The available options with its descriptions:
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{opts_desc}
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"""
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# bind the functions with their docstrings into a Callable
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# and use that as the functions exposed in pd.api
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get_option = CallableDynamicDoc(_get_option, _get_option_tmpl)
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set_option = CallableDynamicDoc(_set_option, _set_option_tmpl)
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reset_option = CallableDynamicDoc(_reset_option, _reset_option_tmpl)
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describe_option = CallableDynamicDoc(_describe_option, _describe_option_tmpl)
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options = DictWrapper(_global_config)
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#
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# Functions for use by pandas developers, in addition to User - api
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class option_context(ContextDecorator):
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"""
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Context manager to temporarily set options in the `with` statement context.
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You need to invoke as ``option_context(pat, val, [(pat, val), ...])``.
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Examples
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--------
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>>> with option_context('display.max_rows', 10, 'display.max_columns', 5):
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... ...
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"""
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def __init__(self, *args):
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if len(args) % 2 != 0 or len(args) < 2:
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raise ValueError(
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"Need to invoke as option_context(pat, val, [(pat, val), ...])."
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)
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self.ops = list(zip(args[::2], args[1::2]))
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def __enter__(self):
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self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
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for pat, val in self.ops:
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_set_option(pat, val, silent=True)
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def __exit__(self, *args):
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if self.undo:
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for pat, val in self.undo:
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_set_option(pat, val, silent=True)
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def register_option(
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key: str,
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defval: object,
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doc: str = "",
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validator: Optional[Callable[[Any], Any]] = None,
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cb: Optional[Callable[[str], Any]] = None,
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) -> None:
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"""
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Register an option in the package-wide pandas config object
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Parameters
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----------
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key : str
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Fully-qualified key, e.g. "x.y.option - z".
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defval : object
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Default value of the option.
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doc : str
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Description of the option.
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validator : Callable, optional
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Function of a single argument, should raise `ValueError` if
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called with a value which is not a legal value for the option.
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cb
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a function of a single argument "key", which is called
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immediately after an option value is set/reset. key is
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the full name of the option.
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Raises
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------
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ValueError if `validator` is specified and `defval` is not a valid value.
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"""
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import keyword
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import tokenize
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key = key.lower()
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if key in _registered_options:
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raise OptionError(f"Option '{key}' has already been registered")
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if key in _reserved_keys:
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raise OptionError(f"Option '{key}' is a reserved key")
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# the default value should be legal
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if validator:
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validator(defval)
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# walk the nested dict, creating dicts as needed along the path
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path = key.split(".")
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for k in path:
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if not re.match("^" + tokenize.Name + "$", k):
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raise ValueError(f"{k} is not a valid identifier")
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if keyword.iskeyword(k):
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raise ValueError(f"{k} is a python keyword")
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cursor = _global_config
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msg = "Path prefix to option '{option}' is already an option"
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for i, p in enumerate(path[:-1]):
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if not isinstance(cursor, dict):
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raise OptionError(msg.format(option=".".join(path[:i])))
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if p not in cursor:
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cursor[p] = {}
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cursor = cursor[p]
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if not isinstance(cursor, dict):
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raise OptionError(msg.format(option=".".join(path[:-1])))
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cursor[path[-1]] = defval # initialize
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# save the option metadata
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_registered_options[key] = RegisteredOption(
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key=key, defval=defval, doc=doc, validator=validator, cb=cb
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)
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def deprecate_option(
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key: str, msg: Optional[str] = None, rkey: Optional[str] = None, removal_ver=None
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) -> None:
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"""
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Mark option `key` as deprecated, if code attempts to access this option,
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a warning will be produced, using `msg` if given, or a default message
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if not.
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if `rkey` is given, any access to the key will be re-routed to `rkey`.
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Neither the existence of `key` nor that if `rkey` is checked. If they
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do not exist, any subsequence access will fail as usual, after the
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deprecation warning is given.
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Parameters
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----------
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key : str
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Name of the option to be deprecated.
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must be a fully-qualified option name (e.g "x.y.z.rkey").
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msg : str, optional
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Warning message to output when the key is referenced.
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if no message is given a default message will be emitted.
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rkey : str, optional
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Name of an option to reroute access to.
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If specified, any referenced `key` will be
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re-routed to `rkey` including set/get/reset.
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rkey must be a fully-qualified option name (e.g "x.y.z.rkey").
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used by the default message if no `msg` is specified.
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removal_ver : optional
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Specifies the version in which this option will
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be removed. used by the default message if no `msg` is specified.
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Raises
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------
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OptionError
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If the specified key has already been deprecated.
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"""
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key = key.lower()
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if key in _deprecated_options:
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raise OptionError(f"Option '{key}' has already been defined as deprecated.")
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_deprecated_options[key] = DeprecatedOption(key, msg, rkey, removal_ver)
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#
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# functions internal to the module
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def _select_options(pat: str) -> List[str]:
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"""
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returns a list of keys matching `pat`
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if pat=="all", returns all registered options
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"""
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# short-circuit for exact key
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if pat in _registered_options:
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return [pat]
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# else look through all of them
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keys = sorted(_registered_options.keys())
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if pat == "all": # reserved key
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return keys
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return [k for k in keys if re.search(pat, k, re.I)]
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def _get_root(key: str) -> Tuple[Dict[str, Any], str]:
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path = key.split(".")
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cursor = _global_config
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for p in path[:-1]:
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cursor = cursor[p]
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return cursor, path[-1]
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def _is_deprecated(key: str) -> bool:
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""" Returns True if the given option has been deprecated """
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key = key.lower()
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return key in _deprecated_options
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def _get_deprecated_option(key: str):
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"""
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Retrieves the metadata for a deprecated option, if `key` is deprecated.
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|
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:
|
|
print(d.msg)
|
|
warnings.warn(d.msg, FutureWarning)
|
|
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)
|
|
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=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):
|
|
"""
|
|
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, reset_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)
|
|
yield None
|
|
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: Optional[int]) -> 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
|