Python-附加到pickle列表

我正在努力将列表附加到一个已修改的文件中。 代码如下：

#saving high scores to a pickled file

import pickle

first_name = input("Please enter your name:")
score = input("Please enter your score:")

scores = []
high_scores = first_name, score
scores.append(high_scores)

file = open("high_scores.dat", "ab")
pickle.dump(scores, file)
file.close()

file = open("high_scores.dat", "rb")
scores = pickle.load(file)
print(scores)
file.close()

第一次运行代码时，它会打印名称和分数

第二次运行代码时，它会打印2个名字和2个分数

---

第三次运行代码时，它会打印第一个名称和分数，但会用我输入的第三个名称和分数覆盖第二个名称和分数。我只想让它继续添加名字和分数。我不明白为什么它会保存第一个名字而覆盖第二个

在附加到列表之前，需要先从数据库（即pickle文件）中提取列表

import pickle
import os

high_scores_filename = 'high_scores.dat'

scores = []

# first time you run this, "high_scores.dat" won't exist
#   so we need to check for its existence before we load 
#   our "database"
if os.path.exists(high_scores_filename):
    # "with" statements are very handy for opening files. 
    with open(high_scores_filename,'rb') as rfp: 
        scores = pickle.load(rfp)
    # Notice that there's no "rfp.close()"
    #   ... the "with" clause calls close() automatically! 

first_name = input("Please enter your name:")
score = input("Please enter your score:")

high_scores = first_name, score
scores.append(high_scores)

# Now we "sync" our database
with open(high_scores_filename,'wb') as wfp:
    pickle.dump(scores, wfp)

# Re-load our database
with open(high_scores_filename,'rb') as rfp:
    scores = pickle.load(rfp)

print(scores)

---

如果要写入和读取pickle文件，可以对列表中的每个条目多次调用dump。每次转储时，都会向pickle文件追加一个分数，每次加载时都会读取下一个分数

>>> import pickle as dill
>>> 
>>> scores = [('joe', 1), ('bill', 2), ('betty', 100)]
>>> nscores = len(scores)
>>> 
>>> with open('high.pkl', 'ab') as f:
…   _ = [dill.dump(score, f) for score in scores]
... 
>>> 
>>> with open('high.pkl', 'ab') as f:
...   dill.dump(('mary', 1000), f)
... 
>>> # we added a score on the fly, so load nscores+1
>>> with open('high.pkl', 'rb') as f:
...     _scores = [dill.load(f) for i in range(nscores + 1)]
... 
>>> _scores
[('joe', 1), ('bill', 2), ('betty', 100), ('mary', 1000)]
>>>

代码失败的原因很可能是您正在用未勾选的分数列表替换原始的

分数。因此，如果有任何新的分数被添加，你会在记忆中把它们一扫而光

>>> scores
[('joe', 1), ('bill', 2), ('betty', 100)]
>>> f = open('high.pkl', 'wb')
>>> dill.dump(scores, f)
>>> f.close()
>>> 
>>> scores.append(('mary',1000))
>>> scores
[('joe', 1), ('bill', 2), ('betty', 100), ('mary', 1000)]
>>> 
>>> f = open('high.pkl', 'rb')
>>> _scores = dill.load(f)
>>> f.close()
>>> _scores
[('joe', 1), ('bill', 2), ('betty', 100)]
>>> blow away the old scores list, by pointing to _scores
>>> scores = _scores
>>> scores
[('joe', 1), ('bill', 2), ('betty', 100)]

因此与其说它是一个pickle问题，不如说它更像是
分数的python名称参考问题
Pickle
只是实例化一个新列表并将其称为
scores
（在您的例子中），然后它垃圾收集在此之前指向
scores
的任何东西

>>> scores = 1
>>> f = open('high.pkl', 'rb')
>>> scores = dill.load(f)
>>> f.close()
>>> scores
[('joe', 1), ('bill', 2), ('betty', 100)]

实际上并没有回答这个问题，但如果有人想在泡菜中一次添加一个项目，你可以通过

import pickle
import os

high_scores_filename = '/home/ubuntu-dev/Desktop/delete/high_scores.dat'

scores = []

# first time you run this, "high_scores.dat" won't exist
#   so we need to check for its existence before we load
#   our "database"
if os.path.exists(high_scores_filename):
    # "with" statements are very handy for opening files.
    with open(high_scores_filename,'rb') as rfp:
        scores = pickle.load(rfp)
    # Notice that there's no "rfp.close()"
    #   ... the "with" clause calls close() automatically!

names = ["mike", "bob", "joe"]

for name in names:
    high_score = name
    print(name)
    scores.append(high_score)

# Now we "sync" our database
with open(high_scores_filename,'wb') as wfp:
    pickle.dump(scores, wfp)

# Re-load our database
with open(high_scores_filename,'rb') as rfp:
    scores = pickle.load(rfp)

print(scores)

不要用腌菜，但要用h5py，这也能解决你的问题

with h5py.File('.\PreprocessedData.h5', 'a') as hf:
    hf["X_train"].resize((hf["X_train"].shape[0] + X_train_data.shape[0]), axis = 0)
    hf["X_train"][-X_train_data.shape[0]:] = X_train_data

    hf["X_test"].resize((hf["X_test"].shape[0] + X_test_data.shape[0]), axis = 0)
    hf["X_test"][-X_test_data.shape[0]:] = X_test_data


    hf["Y_train"].resize((hf["Y_train"].shape[0] + Y_train_data.shape[0]), axis = 0)
    hf["Y_train"][-Y_train_data.shape[0]:] = Y_train_data

    hf["Y_test"].resize((hf["Y_test"].shape[0] + Y_test_data.shape[0]), axis = 0)
    hf["Y_test"][-Y_test_data.shape[0]:] = Y_test_data

还感谢您对代码所做的额外解释。@dogwynn:如果您只是加载到一个新变量，为什么要检查该文件是否存在，以避免真正的问题？@MikeMcKerns:我想我不知道如何从一个不存在的文件调用pickle.load。我知道您可以使用DBv2 API模块（例如shelve）实现这一点，但我不知道有一个类似文件的对象（pickle.load需要）可以在“创建”模式下打开（而不创建）。否则，我的目标是拥有一个可以从命令行重复执行的脚本，每次添加一个新的（名称、分数）元组。@Charlie：我的荣幸。在书上看到另一个Python黑客总是很高兴的。：-）@dogwynn:mode
ab
代替
wb
将在文件不存在时创建一个文件，如果文件存在，则追加文件。此外我不是建议您尝试从一个不存在的文件
加载
，只是指出OP的问题更一般地是取消与现有列表同名的对象的链接，从而销毁在
转储
后对现有列表所做的任何编辑。也感谢您的输入。dogwynn的解决方案非常有效，但会采纳你所说的。为什么pickle-dill在这里？@DheerajMPai：因为我使用
dill
而不是
pickle
，所以我的解决方案就是这样使用的<代码>pickle
也可以工作，因此我没有编辑代码，而是更改了导入。一切都在挑选
dill
在这方面做得更好。@MikeMcKerns lolololAs用帖子的前5个词表示。为什么不使用
hickle
或
klepto
？它们都是为HDF5提供简单的
dump
和
load
pickle等效语法而构建的。如果你在我的回答中用hickle替换dill，我相信它应该可以工作，并存储为HDF5。是的，它可以工作。谢谢你的信息。我不知道希克尔的事。