fr/fr_env/lib/python3.8/site-packages/pandas/_config/config.py

866 lines
23 KiB
Python

"""
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 collections import namedtuple
from contextlib import ContextDecorator, contextmanager
import re
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Type, cast
import warnings
from pandas._typing import F
DeprecatedOption = namedtuple("DeprecatedOption", "key msg rkey removal_ver")
RegisteredOption = namedtuple("RegisteredOption", "key defval doc validator cb")
# 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 for pandas.options, backwards compatible with KeyError
checks
"""
#
# 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):
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 = list(kwargs.keys())[0]
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 = _get_root(key)
root[k] = 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):
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)
else:
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"""
def __init__(self, d: Dict[str, Any], prefix: str = ""):
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) -> Iterable[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:
def __init__(self, func, doc_tmpl):
self.__doc_tmpl__ = doc_tmpl
self.__func__ = func
def __call__(self, *args, **kwds):
return self.__func__(*args, **kwds)
@property
def __doc__(self):
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
-----
The available options with its descriptions:
{opts_desc}
"""
_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
-----
The available options with its descriptions:
{opts_desc}
"""
_describe_option_tmpl = """
describe_option(pat, _print_desc=False)
Prints the description for one or more registered options.
Call with not 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
-----
The available options with its descriptions:
{opts_desc}
"""
_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
-----
The available options with its descriptions:
{opts_desc}
"""
# 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
--------
>>> with option_context('display.max_rows', 10, 'display.max_columns', 5):
... ...
"""
def __init__(self, *args):
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):
self.undo = [(pat, _get_option(pat, silent=True)) for pat, val in self.ops]
for pat, val in self.ops:
_set_option(pat, val, silent=True)
def __exit__(self, *args):
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: Optional[Callable[[Any], Any]] = None,
cb: Optional[Callable[[str], Any]] = 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: Optional[str] = None, rkey: Optional[str] = None, removal_ver=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 : 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:
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