Source code for asreview.utils

# Copyright 2019-2022 The ASReview Authors. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

__all__ = [

import os
import sys
from pathlib import Path
from urllib.error import HTTPError
from urllib.parse import urlparse
from urllib.request import urlopen

import numpy as np

if sys.version_info >= (3, 10):
    from importlib.metadata import entry_points as _entry_points  # noqa
    from importlib_metadata import entry_points as _entry_points  # noqa

def _get_filename_from_url(url):
    if not is_url(url):
        raise ValueError(f"'{url}' is not a valid URL.")

    if Path(urlparse(url).path).suffix:
        return Path(urlparse(url).path).name
            return urlopen(url).headers.get_filename()
        except HTTPError as err:
            # 308 (Permanent Redirect) not supported
            # See
            if err.code == 308:
                return _get_filename_from_url(err.headers.get("Location"))
                raise err

[docs] def asreview_path(): """Get the location where projects are stored. Overwrite this location by specifying the ASREVIEW_PATH enviroment variable. """ if os.environ.get("ASREVIEW_PATH", None): asreview_path = Path(os.environ["ASREVIEW_PATH"]) else: asreview_path = Path("~", ".asreview").expanduser() asreview_path.mkdir(parents=True, exist_ok=True) return asreview_path
[docs] def get_data_home(data_home=None): """Return the path of the ASR data dir. This folder is used by some large dataset loaders to avoid downloading the data several times. By default the data dir is set to a folder named 'asr_data' in the user home folder. Alternatively, it can be set by the 'ASR_DATA' environment variable or programmatically by giving an explicit folder path. The '~' symbol is expanded to the user home folder. If the folder does not already exist, it is automatically created. Parameters ---------- data_home : str | None The path to scikit-learn data dir. """ if data_home is None: data_home = os.environ.get("ASR_DATA", Path("~", "asr_data")) data_home = Path(data_home).expanduser() if not data_home.exists(): data_home.mkdir(parents=True, exist_ok=True) return data_home
def format_to_str(obj): """Create string from object, concatenate if list.""" if isinstance(obj, str): return obj elif isinstance(obj, list): return " ".join(obj) elif obj is None or np.isnan(obj): return "" else: return str(obj) def is_iterable(i): """Check if a variable is iterable, but not a string.""" try: iter(i) if isinstance(i, str): return False return True except TypeError: return False def is_url(url): """Check if object is a valid url.""" try: result = urlparse(url) return all( getattr(result, x) not in [b"", ""] for x in ["scheme", "netloc", "path"] ) except Exception: return False def get_random_state(seed=None): """Constructor for the seeded random number generator. This is the preferred method of instantiating the SeededRandomState class. This function makes sure that the random number generator has been seeded properly. By having a seperate constructor function, we are following the same pattern as Numpy uses. Parameters ---------- seed : int | SeededRandomState | None, optional Seed for the random generator, or random generator itself. If this is None, a seed is generated randomly. By default None. Returns ------- SeededRandomState A random number generator, seeded by the provided seed. """ if isinstance(seed, SeededRandomState): return seed # # For the newer np.random.Generator class, the seed setting would be as follows: # # # if seed is None: # seed = secrets.randbits(128) if seed is None: rng = np.random.default_rng() seed = int(rng.integers(low=0, high=2**32)) if not isinstance(seed, int): raise ValueError( "'seed' should be of type int, SeededRandomNumberGenerator or None" ) return SeededRandomState(np.random.RandomState(seed), seed) class SeededRandomState(np.random.RandomState): def __init__(self, random_state, seed): """Random State that is always seeded. A wrapper class around np.random.Generator that has the attribute `seed` added. Never instantiate this class directly, always use the `get_random_generator` function. It is implicitly assumed that the generator has been seeded using the seed from the argument. The function `get_random_generator` makes sure this happens correctly. Parameters ---------- random_state : np.random.RandomState Random number generator that has been instantiated using `np.random.RandomState(seed)`. seed : int Integer that has been used as the seed of the generator. """ # For the newer `np.random.Generator` class the init argument would be # `generator.bit_generator`. For the legacy `np.random.RandomState` class you # you can get the seed by `random_state.get_state()[1][0]`. super().__init__(random_state.get_state()[1][0]) self.seed = seed