Source code for rics.misc

"""Miscellaneous utility methods for Python applications."""
import inspect
from importlib import import_module as _import_module
from pathlib import Path as _Path
from pprint import saferepr as _safe_repr
from types import ModuleType as _ModuleType
from typing import Any, Callable, Dict, Optional, Type, Union

from ._internal_support import _local_or_remote
from ._internal_support.types import PathLikeType
from .envinterp import UnsetVariableError as _UnsetVariableError, Variable as _Variable


[docs]def interpolate_environment_variables( s: str, *, # noqa: DAR401 allow_nested: bool = True, allow_blank: bool = False, ) -> str: """Interpolate environment variables in a string `s`. This function replaces references to environment variables with the actual value of the variable, or a default if specified. The syntax is similar to Bash string interpolation; use ``${<var>}`` for mandatory variables, and ``${<var>:default}`` for optional variables. Args: s: A string in which to interpolate. allow_blank: If ``True``, allow variables to be set but empty. allow_nested: If ``True`` allow using another environment variable as the default value. This option will not verify whether the actual values are interpolation-strings. Returns: A copy of `s`, after environment variable interpolation. Raises: ValueError: If nested variables are discovered (only when ``allow_nested=False``). UnsetVariableError: If any required environment variables are unset or blank (only when ``allow_blank=False``). See Also: The :mod:`rics.envinterp` module, which this function wraps. """ for var in _Variable.parse_string(s): if not allow_nested and (var.default and _Variable.parse_string(var.default)): raise ValueError(f"Nested variables forbidden since {allow_nested=}.") value = var.get_value(resolve_nested_defaults=allow_nested).strip() if not (allow_blank or value): raise _UnsetVariableError(var.name, f"Empty values forbidden since {allow_blank=}.") s = s.replace(var.full_match, value) return s
[docs]def get_by_full_name(name: str, default_module: Union[str, _ModuleType] = None) -> Any: """Combine :py:func:`~importlib.import_module` and :py:func:`getattr` to retrieve items by name. Args: name: A name or fully qualified name. default_module: A namespace to search if `name` is not fully qualified (contains no ``'.'``-characters). Returns: An object with the fully qualified name `name`. Raises: ValueError: If `name` does not contain any dots and ``default_module=None``. Examples: Retrieving a ``numpy`` function by name. >>> get_by_full_name("numpy.isnan") <ufunc 'isnan'> Falling back to builtins. >>> get_by_full_name("int", default_module="builtins") <class 'int'> """ if "." in name: module_name, _, member = name.rpartition(".") module = _import_module(module_name) else: if not default_module: raise ValueError("Names must be fully qualified when no default module is given.") # pragma: no cover module = _import_module(default_module) if isinstance(default_module, str) else default_module member = name return getattr(module, member)
[docs]def get_public_module(obj: Any, resolve_reexport: bool = False, include_name: bool = False) -> str: """Get the public module of `obj`. Args: obj: An object to resolve a public module for. resolve_reexport: If ``True``, traverse the module hierarchy and look for the earliest where `obj` is reexported. This may be expensive. include_name: If ``True``, include the name of `obj` reexported from a parent module. The first instance found will be used if `obj` is reexported multiple times. Returns: Public module of `obj`. Examples: Public module of ``pandas.DataFrame``. >>> from pandas import DataFrame as obj >>> get_public_module(obj) 'pandas.core.frame' >>> get_public_module(obj, resolve_reexport=True) 'pandas' >>> get_public_module(obj, resolve_reexport=True, include_name=True) 'pandas.DataFrame' Raises: ValueError: If `include_name` is given without `resolve_reexport`. See Also: The analogous :func:`get_by_full_name`-function. """ if include_name and not resolve_reexport: raise ValueError(f"Cannot combine {include_name=} with {resolve_reexport=}.") parts = [] for part in obj.__module__.split("."): if part[0] == "_": break parts.append(part) if resolve_reexport: obj_id = id(obj) for i in range(1, len(parts) + 1): module = _import_module(".".join(parts[:i])) for name, _ in inspect.getmembers(module, predicate=lambda member: id(member) == obj_id): parts = parts[:i] if include_name: parts.append(name) return ".".join(parts) return ".".join(parts)
[docs]def tname(arg: Optional[Union[Type[Any], Any]], prefix_classname: bool = False) -> str: """Get name of method or class. Args: arg: Something get a name for. prefix_classname: If ``True``, prepend the class name if `arg` belongs to a class. Returns: A name for `arg`. Raises: ValueError: If no name could be derived for `arg`. """ if arg is None: return "None" if hasattr(arg, "__qualname__"): return arg.__qualname__ if prefix_classname else arg.__name__ if hasattr(arg, "__name__"): return arg.__name__ if hasattr(arg, "fget"): # Instance-level properties accessed using the class. return tname(arg.fget, prefix_classname=prefix_classname) if hasattr(arg, "__class__"): return arg.__class__.__name__ else: raise ValueError(f"Could not derive a name for {arg=}.") # pragma: no cover
[docs]def format_kwargs(kwargs: Dict[str, Any], *, max_value_length: int = None) -> str: """Format keyword arguments. Args: kwargs: Arguments to format. max_value_length: If given, replace ``repr(value)`` with ``tname(value)`` if repr is longer than `max_value_length` characters. Returns: A string on the form `'key0=repr(value0), key1=repr(value1)'`. Raises: ValueError: For keys in `kwargs` that are not valid Python argument names. Examples: >>> format_kwargs({'an_int': 1, 'a_string': 'Hello!'}) "an_int=1, a_string='Hello!'" """ invalid = [k for k in kwargs if not k.isidentifier()] if invalid: raise ValueError(f"Got {len(invalid)} invalid identifiers: {invalid}.") def repr_value(value: Any) -> str: value_repr = _safe_repr(value) if max_value_length is None or len(value_repr) <= max_value_length: return value_repr return tname(value) return ", ".join(f"{k}={repr_value(v)}" for k, v in kwargs.items())
[docs]def get_local_or_remote( file: PathLikeType, remote_root: PathLikeType, local_root: PathLikeType = ".", force: bool = False, postprocessor: Callable[[str], Any] = None, show_progress: bool = _local_or_remote.TQDM_INSTALLED, ) -> _Path: r"""Retrieve the path of a local file, downloading it if needed. If `file` is not available at the local root path, it will be downloaded using `requests.get`_. A postprocessor may be given in which case the name of the final file will be ``local_root/<name-of-postprocessor>/file``. Removing a raw local file (i.e. ``local_root/file``) will invalidate postprocessed files as well. Args: file: A file to retrieve or download. remote_root: Remote URL where the data may be retrieved using ``requests.get``. local_root: Local directory where the file may be cached. force: If ``True``, always download and apply processing (if applicable). Existing files will be overwritten. postprocessor: A function which takes a single argument `input_path` and returns a pickleable type. show_progress: If ``True``, show a progress bar. Requires the `tqdm`_ package. Returns: An absolute path to the data. Raises: ValueError: If local root path does not exist or is not a directory. ValueError: If the local file does not exist and ``remote=None``. ModuleNotFoundError: If the ``tqdm`` package is not installed but ``show_progress=True``. Examples: Fetch the Title Basics table (a CSV file) of the `IMDb dataset`_. >>> from rics.misc import get_local_or_remote >>> import pandas as pd >>> >>> file = "name.basics.tsv.gz" >>> local_root = "my-data" # default = "." >>> remote_root = "https://datasets.imdbws.com" >>> path = get_local_or_remote(file, remote_root, local_root, show_progress=True) # doctest: +SKIP >>> pd.read_csv(path, sep="\t").shape # doctest: +SKIP https://datasets.imdbws.com/name.basics.tsv.gz: 100%|██████████| 214M/214M [00:05<00:00, 39.3MiB/s] (11453719, 6) We had download `name.basics.tsv.gz` the first time, but ``get_local_or_remote`` returns immediately the second time it is called. Fetching can be forced using ``force_remote=True``. >>> path = get_local_or_remote(file, remote_root, local_root, show_progress=True) # doctest: +SKIP >>> pd.read_csv(path, sep="\t").shape # doctest: +SKIP (11453719, 6) .. _IMDb dataset: https://www.imdb.com/interfaces/ .. _requests.get: https://2.python-requests.org/en/master/api/#requests.get .. _tqdm: https://pypi.org/project/tqdm/ """ return _local_or_remote.get_local_or_remote( file=file, local_root=local_root, remote_root=remote_root, force=force, postprocessor=postprocessor, show_progress=show_progress, )
[docs]def serializable(obj: Any) -> bool: """Check if `obj` is serializable using Pickle. Serializes to memory for speed. Args: obj: An object to attempt to serialize. Returns: ``True`` if `obj` was pickled without issues. """ import io import pickle # noqa: S403 bio = io.BytesIO() try: pickle.dump(obj, bio) return True except Exception: # noqa: B902 return False