In this article, we will learn how to write a list of dataclass instances to an Excel file using the popular Python library pandas. Pandas is a powerful tool for working with data in Python, and it provides a convenient way to write data to Excel files. We will walk through the steps of converting a list of dataclass instances to a pandas DataFrame and then using the to_excel method to write the DataFrame to an Excel file. By the end of this tutorial, you will have a good understanding of how to use pandas to write data to Excel files and will be able to apply this knowledge to your own data analysis projects.

What is a dataclass?

In Python, a dataclass is a class that is decorated with the @dataclass decorator and has several class variables defined using the field function. Dataclasses were introduced in Python 3.7 and are designed to make it easier to create classes that are primarily used to store data. They provide several benefits, such as automatically generating methods such as __init__, __repr__, and __eq__, and allowing you to use default values for class variables.

Writing a List of Dataclass Instances to an Excel File Using Pandas

To write a list of dataclass instances to an Excel file using pandas, here is one way to do it:

import pandas as pd
from dataclasses import dataclass

class Person:
    name: str
    age: str
    score: int

# Some function that builds a list of Person instances.
def get_people() -> List[Person]
    return list_of_people

# Convert the list of dataclass instances to a pandas DataFrame. 

df = pd.DataFrame.from_records([dataclasses.asdict(person) for person in list_of_people])

df.to_excel('path/to/file.xlsx', index=False)

This will create an Excel file with the specified file name and save it to the specified location. The index=False parameter tells pandas not to include the DataFrame’s index in the output.

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