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This article mainly introduces the python IO stream and object serialization instance analysis related knowledge, the content is detailed and easy to understand, the operation is simple and fast, has a certain reference value, I believe that everyone after reading this python IO stream and object serialization instance analysis article will have a harvest, let's take a look.

I. the operation of IO stream

(1)。 What is an IO stream (Input Output Stream)?

IO stream is mainly about the input and output operation of the computer. Common IO operations are generally referred to as memory.

IO streaming is a common persistence (permanent save) technique: data is output from memory to disk and saved.

(2) Classification of IO flows

According to data flow (from a memory point of view): input stream, output stream

According to the type of data: character stream, byte stream

Note:

Character stream: characters can only manipulate data with characters (read to the end with'')

Byte stream: bytes can be used to manipulate all data (read to the end is baked'). Byte stream operation big data, it is not recommended to read it at once

(3) how does .python operate IO streams? Use the open () global function to open the local file, and the return value is an IO stream object

# the format of the open () function open (file, mode='r', buffering=-1, encoding=None, errors=None, newline=None, closefd=True, opener=None) mode mode is:'r 'open for reading (default)' w 'open for writing, truncating the file first' x 'create a new file and open it for writing'a' open for writing Appending to the end of the file if it exists 'b'binary mode 't'text mode (default)'+ 'open a disk file for updating (reading and writing)' U'universal newline mode (deprecated) encoding encoding is used: default is none, and should be used when using it. Encoding= "utf-8"

Usually the open () function is used with the read () function, and the read () function is used to read the value of the IO stream object. In addition to the read () function, there are the following:

1.read (size=-1) # read, parameters can be with or without readline () # read readlines () by line # read # 1 by multiple lines. When there are no parameters Read all at once > f=open ("G:\ Python\ python exercise\ day09\ a.txt", encoding= "utf-8") > > f.read () # read all the first time read'I love my motherland'> f.read () # the second reading is empty'> > f.close () # automatically execute flush # 2. When there are parameters, it is usually used to read byte data. Means to read according to the parameters, so that if you read byte data, it is good for memory and the reading speed is fast. The computer will not crash > f=open ("G:\ Python\ python exercise\ day09\ a.txt" Encoding= "utf-8") > f.read (2) # first read'I love'> > f.read (2) # second read'my'> > f.read (2) # third read 'Motherland' > f.close () # automatically execute flush2.write (data) # write content to file > f=open ("a.txt" "rb") > data=f.read (4) > data b'\ xba\ x8c\ xe7\ x8b' > f1=open ("b.txt", "wb") > > f1.write (data) # write the byte data of f to f14 > f1.close () > f.close () > f1=open ("b.txt") "rb") # verify whether the b.txt file is written as data > f1.read () b'\ xba\ x8c\ xe7\ x8b' > f1.close () 3.writelines () # write multiple data to 4.flush () # refresh cache 5.close () # close the file object Note that close automatically calls flush for the final file refresh

(4). With statement block (with IO stream, you can turn off IO stream (close ()) by yourself)

Format: with open ("user.dat", "wb") as f: f.write (save_users) II. Object serialization

(1)。 What is object serialization?

The abstract concept of an object (container, object, etc.) into the process of actually storing character or byte data

(2)。 How to implement object serialization? Two modules: pickle module and json module

Json module: you can convert objects to character data

Pickle module: can convert objects to byte data

(3)。 Details of the two modules:

I. pickle module: serialize objects into byte data > import pickle > dir (pickle) 'dump',' dumps', 'load',' loads'1.dumps () # serialize objects into byte data, a parameter Used to put objects > > ls= > > import pickle > data=pickle.dumps (ls) # serialize ls into bytes and store it in data > data b'\ x80\ x03] Q\ x00 (K\ x01K\ x02K\ x03K\ x04e.' > > f=open ("b.txt") "wb") > f.write (data) # writes serialized byte data to the b.txt file 16 > f.close () > f=open ("b.txt") "rb") # verify whether the b.txt file is written as data > f.read () b'\ x80\ x03] Q\ x00 (K\ x01K\ x02K\ x03K\ x04e.' > > f.close () dump () # serializes objects into byte data And save it to file, two parameters for a drop object A stored file > pickle.dump (ls,open ("a.txt", "wb")) 2.loads () # deserializes a byte data object into its own object > f=open ("b.txt", "rb") > data=f.read () > pickle.loads (data) ['adata, 1] 2] load () # deserializes the byte data object of a file into its own object > > pickle.load (open ("b.txt", "rb")) ['await, 1, 2] II. Json module: objects can be serialized into character data > import json > dir (json)' dump', 'dumps',' load' 'loads'1.dumps () # serializes the object into character data, a parameter Used to play objects > ls= [1meme 2jing3jin4] > > data=json.dumps (ls) > f=open ("b.txt", "w") > f.write (data) 12 > f.close () > f=open ("b.txt") > > f.read ()'[1Jing 2jue 3] 4]'> f.close () dump () # serializes objects into character data And save it to file, two parameters for a drop object A saved file > ls= ['axiaqingzhongbaojia] > json.dump (ls,open ("b.txt", "w")) > f=open ("b.txt") > f.read ()' ["a", "b", 1 2]'> > f.close () 2.loads () # deserializes a character data object into its own object > f=open ("b.txt") > data=f.read () > json.loads (data) ['a character, 'baked, 1] 2] load () # deserializes the character data object of a file into its own object > json.load (open ("b.txt")) ['a stream and object serialization instance analysis of IO streams and objects in python ". This is the end of the article. Thank you for reading! I believe you all have some knowledge of "IO stream and object serialization instance analysis in python". If you want to learn more, you are welcome to follow the industry information channel.

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