Ways to Write Variables to a File in Python

During my ten years of developing Python applications, I have often needed to save data for later use. Whether it is a small configuration setting or a large dataset, knowing how to write variables to a file is a fundamental skill.

In this tutorial, I will show you exactly how I handle file writing in Python. I have used these methods in countless production environments to ensure data is stored safely and efficiently.

Table of Contents

Use the basic write() Method

The most direct way I save a string variable to a file is by using the built-in open() function combined with the write() method.

I find this method incredibly useful when I am creating simple logs or saving a single piece of information, like a California real estate property ID.

# Defining a variable with a USA property ID
property_id = "CA-90210-4567"

# Opening a file in write mode ('w')
with open("property_data.txt", "w") as file:
    # Writing the variable to the file
    file.write(property_id)

print("Data successfully written to property_data.txt")

You can refer to the screenshot below to see the output.

When I use the with statement, Python automatically closes the file for me. This is a practice I highly recommend to avoid memory leaks or file corruption.

1. Write Multiple Variables with writelines()

Sometimes I need to save a list of variables at once, such as a list of major US stock tickers. For this, the writelines() method is my go-to choice.

One thing I learned early on is that writelines() does not add new lines for you. I always make sure to include the \n character if I want each variable on a new row.

# List of US Tech Stock Tickers
stocks = ["AAPL\n", "MSFT\n", "GOOGL\n", "AMZN\n", "TSLA\n"]

# Opening the file to save the list
with open("us_stocks.txt", "w") as file:
    file.writelines(stocks)

print("Stock list saved to us_stocks.txt")

You can refer to the screenshot below to see the output.

This approach is much cleaner than looping through a list and calling write() repeatedly. It keeps my code concise and professional.

2. Save Variables as JSON Data

In my experience, when I deal with complex data like a user profile containing a name, age, and US state, saving it as a plain string isn’t enough.

I prefer using the json module. It allows me to save dictionaries or lists in a format that remains structured and easy for other applications to read.

import json

# US User Profile Data
user_profile = {
    "name": "James Miller",
    "age": 34,
    "location": "Austin, Texas",
    "is_premium_member": True
}

# Saving the dictionary variable to a JSON file
with open("user_profile.json", "w") as json_file:
    json.dump(user_profile, json_file, indent=4)

print("User profile saved as JSON.")

You can refer to the screenshot below to see the output.

I always use the indent parameter in json.dump(). It makes the file human-readable, which is a lifesaver when I’m debugging data late at night.

3. Use the Pickle Module for Python Objects

There are times when I need to save a Python variable exactly as it is, including its data type and structure, without converting it to text.

The pickle module is what I use for this. It serializes the object into a binary format. I find this particularly useful for saving machine learning models or complex nested lists.

import pickle

# A list representing quarterly revenue in USD for a startup
quarterly_revenue = [150000, 275000, 310000, 450000]

# Writing the list variable to a binary file
with open("revenue_data.pkl", "wb") as binary_file:
    pickle.dump(quarterly_revenue, binary_file)

print("Revenue data serialized and saved.")

You can refer to the screenshot below to see the output.

Note that I used “wb” (write binary) mode here. If you try to write a pickle file in standard text mode, the code will throw an error.

4. Append Variables to an Existing File

A common mistake I see junior developers make is overwriting a file when they actually meant to add data to it.

If I am tracking something over time, like daily temperatures in Chicago, I use the “a” (append) mode instead of “w”.

# New temperature reading in Fahrenheit
new_temp_record = "Chicago, IL: 72°F\n"

# Appending the variable to the end of the file
with open("weather_history.txt", "a") as file:
    file.write(new_temp_record)

print("New record added to weather_history.txt")

By using append mode, I ensure that my previous data stays intact while the new variable is tucked neatly at the bottom of the file.

5. Write Variables to a CSV File

If I am preparing data for a spreadsheet, like a list of employees in a New York office, I always opt for the csv module.

This makes it easy for my colleagues to open the resulting file in Excel or Google Sheets without any formatting headaches.

import csv

# US Employee Data: Name, Department, City
employee_data = [
    ["Sarah Connor", "Operations", "New York"],
    ["Michael Scott", "Management", "Scranton"],
    ["Donna Specter", "Legal", "Chicago"]
]

# Writing variables to a CSV file
with open("us_employees.csv", "w", newline='') as csvfile:
    writer = csv.writer(csvfile)
    writer.writerow(["Name", "Department", "City"]) # Header
    writer.writerows(employee_data)

print("Employee data saved to us_employees.csv")

I always include newline=” in the open() function for CSVs. It prevents those annoying extra blank lines that sometimes appear on Windows systems.

In this guide, I have shown you the most reliable ways to save your variables to a file in Python. Whether you need a simple text file, a structured JSON, or a spreadsheet-ready CSV, these methods have served me well over the last decade.

Ways to Write Variables to a File in Python

Use the basic write() Method

1. Write Multiple Variables with writelines()

2. Save Variables as JSON Data

3. Use the Pickle Module for Python Objects

4. Append Variables to an Existing File

5. Write Variables to a CSV File

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