与json模块不同,pickle模块可以保存任意Python对象,包括列表。 下面是一个使用pickle模块将列表保存为二进制文件的示例代码: importpickledefsave_list_to_pickle(lst,file_path):withopen(file_path,'wb')asfile:pickle.dump(lst,file)# 示例my_list=[1,2,3,4,5]
方法一:使用pickle模块 在Python中,我们可以使用pickle模块将列表序列化为二进制数据,并保存到文件中。下次使用时,我们可以将文件中的二进制数据加载回来,并反序列化为列表。 importpickle# 将列表保存到文件defsave_list(list_data,file_path):withopen(file_path,'wb')asfile:pickle.dump(list_data,file)# 从...
| save_long(self, obj, pack=<built-infunction pack>)| |save_none(self, obj)| |save_pers(self, pid)| | save_reduce(self, func, args, state=None, listitems=None, dictitems=None, obj=None)| | save_string(self, obj, pack=<built-infunction pack>)| |save_tuple(self, obj)| | ...
存储: importpickle fileHandle= open ('pickleFile.txt','w') testList= [ 123, {'Calories': 190 },'Mr. Anderson', [ 1, 2, 7] ] pickle.dump ( testList, fileHandle ) fileHandle.close() 读取 importpickle fileHandle= open ('pickleFile.txt','r') testList=pickle.load ( fileHandle ...
pickle是Python序列化的一个库。将对象通过dumps转成字符串(或dump存入文件),之后可以通过loads这个字符串重新生成对象(或load文件生成对象)。 import pickle list1=["a","b"] path=r"E:\aTools\Python\old.txt" with open(path, 'wb') as text: pickle.dump(list1, text) with open(path, 'rb') as...
模块pickle 实现了对一个 Python 对象结构的二进制序列化和反序列化。 “Pickling” 是将 Python 对象及其所拥有的层次结构转化为一个字节流的过程,而“unpickling” 是相反的操作,会将(来自一个 binary file 或者 bytes-like object 的)字节流转化回一个...
它的参数类型是int, list of int, None, 或者是默认的'infer' 它的功能是:Row numbers to use as the column names, and the start of the data. 也就是,它是把某一行作为列名,并且,这一行是数据开始的行。我们测试一下。刚才我们在a.csv文件中只写了两行数据,为了方便测试,我们写上5行数据(大部分...
classes= pickle.load(open('classes.pkl','rb'))defclean_up_sentence(sentence):# tokenize the pattern - splittingwords into arraysentence_words = nltk.word_tokenize(sentence)# stemming every word - reducing tobase formsentence_words = [lemmatizer.lemmatize(word.lower()) for word in sentence_...
(data) data.columns = header_cols return data #Movie ID to movie name dict def create_movie_dict(movie_file): print(movie_file) df = pd.read_csv(movie_file,sep='|', encoding='latin-1',header=None) movie_dict = {} movie_ids = list(df[0].values) movie_name = list(df[1]....
First, let’s create a simple Python list: import pickle student_names = ['Alice','Bob','Elena','Jane','Kyle'] Now, let’s open a text file, write the list to it using the dumps() function, and close the file: with open('student_file.pkl', 'wb') as f: # open a text fi...