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3RNN/Lib/site-packages/pandas/_config/config.py
s464967 8af59a8246 1.0
2024-05-26 19:49:15 +02:00

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"""
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 <options>` 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 <options>` 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 <options>` 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 <options>` 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
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