--- title: Modules, Packages, and File Handling date: 2026-01-03T18:14:43Z modified: 2026-01-04T20:27:28Z permalink: "https://www.micheledpierri.com/python/modules-files/" type: page status: publish excerpt: "" wpid: 2505 featured_image: "https://www.micheledpierri.com/wp-content/uploads/2026/01/Python_08.webp" featured_image_alt: Children dressed in lab coats are studying a python timestamp: 2026-01-04T20:27:28Z tags: [] --- ## Lesson Objectives By the end of this lesson, you will be able to: - Import and use Python modules - Understand the difference between modules and packages - Read from and write to text files - Organize code into reusable components This lesson introduces **scalability**: code stops living in a single file and becomes a structured system. --- ## 1️⃣ What Is a Module A **module** is a Python file that contains: - functions - variables - classes Every `.py` file is a module. Example: # math.py def square(x): return x * x ``` # math.py def square(x): return x * x ``` You can use it in another file. --- ## 2️⃣ Importing Modules ### Import the Entire Module import math print(math.sqrt(16)) ``` import math print(math.sqrt(16)) ``` You access module content using dot notation. ### Import Specific Objects from math import sqrt print(sqrt(16)) ``` from math import sqrt print(sqrt(16)) ``` Use this carefully to avoid name conflicts. ### Aliasing Imports import numpy as np ``` import numpy as np ``` This is extremely common in data analysis. --- ## 3️⃣ Built-in vs External Modules ### Built-in Modules Python ships with many built-in modules: - `math` - `os` - `sys` - `random` Example: import random random.randint(1, 10) ``` import random random.randint(1, 10) ``` --- ### External Packages External packages must be installed. Example (in terminal): pip install numpy ``` pip install numpy ``` Then (in code editor): import numpy as np ``` import numpy as np ``` This is how the scientific ecosystem works. --- ## 4️⃣ What Is a Package A **package** is a collection of modules. Example structure: my_project/ │ ├── analysis/ │ ├── __init__.py │ ├── stats.py │ └── preprocessing.py ``` my_project/ │ ├── analysis/ │ ├── __init__.py │ ├── stats.py │ └── preprocessing.py ``` Packages allow: - logical grouping - reusable pipelines - clean project structure --- ## 5️⃣ Reading Files in Python Reading files is fundamental in data analysis. ### Basic File Reading file = open("data.txt", "r") content = file.read() file.close() ``` file = open("data.txt", "r") content = file.read() file.close() ``` This works, but it is **not recommended**. ### Using `with` (Best Practice) with open("data.txt", "r") as file: content = file.read() ``` with open("data.txt", "r") as file: content = file.read() ``` Why `with`? - automatically closes the file - safer and cleaner --- ## 6️⃣ Writing Files in Python ### Writing Text with open("output.txt", "w") as file: file.write("Hello Python") ``` with open("output.txt", "w") as file: file.write("Hello Python") ``` Mode `"w"` overwrites existing files. ### Appending Text with open("output.txt", "a") as file: file.write("\\nNew line") ``` with open("output.txt", "a") as file: file.write("\\nNew line") ``` --- ## 7️⃣ Reading Files Line by Line Useful for large files. with open("data.txt", "r") as file: for line in file: print(line.strip()) ``` with open("data.txt", "r") as file: for line in file: print(line.strip()) ``` This pattern is common when processing logs or datasets. --- ## 8️⃣ Why This Matters for Data Analysis Modules and files allow you to: - separate logic (clean code) - reuse functions across projects - load datasets from disk - save results and reports Every serious analytical workflow depends on these concepts. --- ## FAQ — Frequently Asked Questions **Q: What happens if the file does not exist?** A: Python raises a `FileNotFoundError`. **Q: Should I always use `with` when opening files?** A: Yes, almost always. **Q: Where should my modules live?** A: Inside the project folder, organized by purpose. **Q: Are CSV and Excel files read this way?** A: Technically yes, but libraries like `pandas` are preferred. --- ## Exercises ### Exercise 1 Import the `math` module and compute the square root of 25. ### Exercise 2 Import only `pi` from `math` and print it. ### Exercise 3 Create a module `utils.py` with a function `cube(x)`. ### Exercise 4 Import `cube` in another file and use it. ### Exercise 5 Write a file called `hello.txt` containing `"Hello Python"`. ### Exercise 6 Append a second line to the same file. ### Exercise 7 Read and print the content of `hello.txt`. ### Exercise 8 Read a file line by line. ### Exercise 9 Explain why `with` is safer than `open()` + `close()`. ### Exercise 10 Explain why modules are essential in large projects. --- ## Solutions ### Exercise 1 import math math.sqrt(25) ``` import math math.sqrt(25) ``` ### Exercise 2 from math import pi print(pi) ``` from math import pi print(pi) ``` ### Exercise 3 # utils.py def cube(x): return x ** 3 ``` # utils.py def cube(x): return x ** 3 ``` ### Exercise 4 from utils import cube cube(3) ``` from utils import cube cube(3) ``` ### Exercise 5 with open("hello.txt", "w") as f: f.write("Hello Python") ``` with open("hello.txt", "w") as f: f.write("Hello Python") ``` ### Exercise 6 with open("hello.txt", "a") as f: f.write("\\nSecond line") ``` with open("hello.txt", "a") as f: f.write("\\nSecond line") ``` ## Exercise 7 with open("hello.txt", "r") as f: print(f.read()) ``` with open("hello.txt", "r") as f: print(f.read()) ``` ## Exercise 8 with open("hello.txt", "r") as f: for line in f: print(line.strip()) ``` with open("hello.txt", "r") as f: for line in f: print(line.strip()) ``` ### Exercise 9 # Automatic file closing, fewer errors ``` # Automatic file closing, fewer errors ``` ### Exercise 10 # Modules improve structure, reuse, and maintainability ``` # Modules improve structure, reuse, and maintainability ``` --- ## 🚀 Next Lesson Preview In **Lesson 9**, we will cover: - runtime errors - exceptions - `try / except` blocks - writing robust and fault-tolerant code ## This is where Python code becomes **reliable**, not just correct.