Python server programming: using CSV for data storage and processing

With the advent of the Internet era, data storage and processing have become very important. In modern computer science, many applications require processing and storing data. Therefore, server programming has become a very important field. The Python language has been widely used in server-side programming. Among them, CSV (Comma Separated Values), as a simple and commonly used file format, also plays an important role in server-side programming. This article will introduce how to use CSV for data storage and processing in Python server programming.

What is CSV?

CSV is a simple and common file format. Its English name is Comma Separated Values, which is translated into Chinese as comma separated values. CSV files can be opened, edited and generated using Microsoft Excel, Google Sheets, WPS and other software, and are generally used to store tabular data. The CSV file uses plain text format, and the data is separated by commas. Each row represents a record, and each column contains different data fields of the record. For example, the following is a CSV file containing student information:

Name,Age,Gender,Grade Tom,18,Male,Sophomore Lily,19,Female,Freshman Jerry,20,Male,Senior

In Python, we can use the csv module to manipulate CSV files, which provides a series of functions and classes for reading and writing CSV files.

Use CSV for data storage

In Python server programming, we can use CSV files to store data. For example, we can use CSV files to store data of student information. First, we need to create a CSV file that stores student information. This can be achieved using the following code:

import csv header = ['Name', 'Age', 'Gender', 'Grade'] rows = [ ['Tom', '18', 'Male', 'Sophomore'], ['Lily', '19', 'Female', 'Freshman'], ['Jerry', '20', 'Male', 'Senior'] ] with open('students.csv', 'w', newline='') as file: writer = csv.writer(file) writer.writerow(header) writer.writerows(rows)

First, we import the csv module. Then, the table header and table content are defined. Finally, use the with statement to open the file and write the CSV content. The first parameter is the name of the file and its path, and the second parameter is the mode in which the file is opened: "w" here means "write", which means we can write to the file. This method returns a file object, which we use to create a csv writer.

writerow() is used to write one row of data (i.e. one record), and writerows() is used to write multiple rows of data (i.e. multiple records). In the above code, we first write the table header, then write the content of the student information, and write the entire table into the CSV file.

Using CSV for data reading

In Python server programming, it is also very common to use CSV files for data reading. The following code shows how to use the csv module in Python to read a CSV file:

import csv with open('students.csv') as file: reader = csv.reader(file) header = next(reader) rows = list(reader) print(header) print(rows)

In this code, we open a CSV file to read in data. We first create a CSV reader object using the csv.reader() function. The reader object can be used to iterate over each row in a CSV file, returning each iteration a list containing all the data for the current row. The next() function is used to read the next line in the file. In this example, we use the next() function to read the first line of the file, which is the header. Next, use the list() function to read all the record lines, and finally get a nested list of record lines.

Use pandas library for CSV file processing

In addition to using the csv module, you can also use the pandas library for CSV file processing. Pandas is an efficient data processing tool that can easily manipulate large data sets. The following is an example of using the pandas library to read and process CSV files:

import pandas as pd df = pd.read_csv('students.csv') print(df.head())

In this code, we use the read_csv function in the pandas library to read data from the CSV file. What is returned is a dataframe, which is a data structure used to represent tabular data. Using the head() function, we can display the first few rows of data in the data frame.

Summary

Using CSV for data storage and processing is an important task in server programming. In Python, the csv module and pandas library provide methods and tools respectively to read, write, analyze and process data in CSV files. Through the introduction of this article, we should be able to use Python to write code to use CSV files for data storage and processing.

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