Got a same error and this solved my error. Thanks! python 2 and python 3 differing in unicode handling is making pickled files quite incompatible to load. So Use python pickle's encoding argument. Link below helped me solve the similar problem when I was trying to open pickled data from my python 3.7, while my file was saved originally in python 2.x version. https://blog.modest-destiny.com/posts/python-2-and-3-compatible-pickle-save-and-load/ I copy the load_pickle function in my script and called the load_pickle(pickle_file) while loading my input_data like this:

input_data = load_pickle("my_dataset.pkl")

load_pickle函数在这里:

def load_pickle(pickle_file):
    try:
        with open(pickle_file, 'rb') as f:
            pickle_data = pickle.load(f)
    except UnicodeDecodeError as e:
        with open(pickle_file, 'rb') as f:
            pickle_data = pickle.load(f, encoding='latin1')
    except Exception as e:
        print('Unable to load data ', pickle_file, ':', e)
        raise
    return pickle_data

在Django (1.9.10)/Python 2.7.5项目中，我经常出现UnicodeDecodeError异常;主要是当我试图向日志记录提供unicode字符串时。我为任意对象创建了一个辅助函数，基本上格式化为8位ascii字符串，并将表中不包含的任何字符替换为'?'。我认为这不是最好的解决方案，但由于默认编码是ascii(我不想改变它)，它会这样做:

encode_for_logging(c, encoding='ascii'): 如果isinstance(c, basestring): 返回c.encode(encoding， 'replace') elif isinstance(c, Iterable): C_ = [] 对于v (c) c_。追加(encode_for_logging (v,编码) 返回c_ 其他: 返回encode_for_logging (unicode (c)) ｀

简而言之，为了确保在Python 2中正确处理unicode:

使用io。打开文件读写 使用from __future__ import unicode_literals 配置其他数据输入/输出(例如，数据库，网络)使用unicode 如果不能将输出配置为utf-8，请将输出转换为print(text。编码(“ascii”、“替换”).decode ())

有关解释，请参阅@Alastair McCormack的详细回答。

这招对我很管用:

    file = open('docs/my_messy_doc.pdf', 'rb')

我正在搜索解决以下错误信息:

Unicodedecodeerror: 'ascii'编解码器无法解码位置5454中的字节0xe2:序号不在范围(128)

我最终通过指定'encoding'来修复它:

f = open('../glove/glove.6B.100d.txt', encoding="utf-8")

希望它也能帮助到你。

这是我的解决方案，只需添加编码。 用open(file, encoding='utf8')作为f

因为读取glove文件需要很长时间，所以我建议将glove文件转换为numpy文件。当你读取嵌入权重时，它将节省你的时间。

import numpy as np
from tqdm import tqdm


def load_glove(file):
    """Loads GloVe vectors in numpy array.
    Args:
        file (str): a path to a glove file.
    Return:
        dict: a dict of numpy arrays.
    """
    embeddings_index = {}
    with open(file, encoding='utf8') as f:
        for i, line in tqdm(enumerate(f)):
            values = line.split()
            word = ''.join(values[:-300])
            coefs = np.asarray(values[-300:], dtype='float32')
            embeddings_index[word] = coefs

    return embeddings_index

# EMBEDDING_PATH = '../embedding_weights/glove.840B.300d.txt'
EMBEDDING_PATH = 'glove.840B.300d.txt'
embeddings = load_glove(EMBEDDING_PATH)

np.save('glove_embeddings.npy', embeddings) 

Gist链接:https://gist.github.com/BrambleXu/634a844cdd3cd04bb2e3ba3c83aef227