Working with different file formats (text, CSV, JSON) File formats are an essential aspect of working with files in Python automation. They allow us to store and exchange data in a structured manner. In this tutorial, we will explore how to work with three popular file formats: text, CSV, and JSON. These formats are widely used in various domains, including data analysis, data science, and web development. 1. Working with Text Files Text files are the simplest form of file formats. They contain plain text and do not have any specific structure. Python provides built-in functions to read, write, and manipulate text files. 1.1 Reading a Text File To read a text file, we use the `open()` function in Python. The `open()` function takes two arguments: the file name and the mode (“r” for reading, “w” for writing, “a” for appending, etc.). “`python with open(“example.txt”, “r”) as file: content = file.read() “` In the above code, we open the file `example.txt` in read mode and use the `read()` method to read the entire content of the file into the `content` variable. 1.2 Writing to a Text File To write to a text file, we use the `write()` method. It is important to note that opening a file in write mode will overwrite any existing content in the file. “`python with open(“new_file.txt”, “w”) as file: file.write(“Hello, World!”) “` In the above code, we create a new file named `new_file.txt` and write the text “Hello, World!” to it. If the file already exists, the previous content will be replaced. 2. Working with CSV Files CSV (Comma Separated Values) files are widely used to store tabular data. Each line in a CSV file represents a row, and the values are separated by commas. Python provides the `csv` module to work with CSV files. 2.1 Reading a CSV File To read a CSV file, we need to import the `csv` module and use its `reader()` function. “`python import csv with open(“data.csv”, “r”) as file: csv_reader = csv.reader(file) for row in csv_reader: print(row) “` In the above code, we open the file `data.csv` and use the `csv.reader()` function to create a reader object. We then iterate over the rows of the CSV file and print each row. 2.2 Writing to a CSV File To write to a CSV file, we use the `csv.writer()` function. “`python import csv data = [[“Name”, “Age”], [“John”, 25], [“Alice”, 30], [“Bob”, 35]] with open(“new_data.csv”, “w”) as file: csv_writer = csv.writer(file) csv_writer.writerows(data) “` In the above code, we create a list of lists `data` representing the rows of the CSV file. We then open the file `new_data.csv` and use the `csv.writer()` function to create a writer object. Finally, we use the `writerows()` method to write the data to the CSV file. 3. Working with JSON Files JSON (JavaScript Object Notation) is a popular file format for data interchange. It provides a lightweight and human-readable way to represent data objects. Python provides the `json` module to work with JSON files. 3.1 Reading a JSON File To read a JSON file, we need to import the `json` module and use its `load()` function. “`python import json with open(“data.json”, “r”) as file: data = json.load(file) “` In the above code, we open the file `data.json` and use the `json.load()` function to load the JSON data into the `data` variable. 3.2 Writing to a JSON File To write to a JSON file, we use the `dump()` function. “`python import json data = { “name”: “John”, “age”: 25, “city”: “New York” } with open(“new_data.json”, “w”) as file: json.dump(data, file) “` In the above code, we create a dictionary `data` representing the JSON object. We then open the file `new_data.json` and use the `json.dump()` function to write the data to the JSON file. Conclusion In this tutorial, we explored how to work with different file formats (text, CSV, JSON) in Python automation. We learned how to read and write files in these formats by utilizing built-in modules such as `csv` and `json`. By understanding these concepts, you can effectively work with a variety of file formats and handle the data within them.