Reading Text Files Into Python
Open a document and load its contents.
Reading Text Files Into Python is a free NLP Academy lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the NLP Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Real Text Lives in Files
Most NLP work starts with documents stored on disk. Your first job is to load that text from a file into a Python string. 📄
Open a File With open
The open function connects Python to a file. You give it a path and a mode like r, which means read.
f = open("notes.txt", "r")
text = f.read()
f.close()Read the Whole File
The read method pulls the entire file into one string. That is handy for small documents you want to process all at once.
content = f.read()
print(len(content)) # total charactersAlways Close What You Open
An open file holds a system resource. Forgetting to close it can lose data or leak handles, so closing matters.
The with Statement Is Safer
A with block opens the file and closes it automatically when you are done, even if an error happens partway through.
with open("notes.txt", "r") as f:
text = f.read()Always Set the Encoding
Pass encoding so Python decodes bytes correctly. Using utf-8 explicitly avoids surprises across different machines.
with open("notes.txt", encoding="utf-8") as f:
text = f.read()Read Line by Line
Looping over the file object yields one line at a time. This is gentle on memory for very large documents.
with open("notes.txt", encoding="utf-8") as f:
for line in f:
print(line.strip())Get All Lines as a List
The readlines method returns every line as a list of strings, which is useful when you want to index or count lines.
lines = f.readlines()
print(len(lines)) # number of linesLines Keep Their Newline
Each read line ends with a hidden newline character. Call strip to remove that trailing whitespace before processing.
clean = line.strip()Handle Missing Files
If the path is wrong, Python raises a FileNotFoundError. Wrap risky reads in try and except to fail gracefully.
try:
open("missing.txt")
except FileNotFoundError:
print("No such file")Paths Matter
A relative path is read from where you run the script. When in doubt, use a full path so Python finds the right file.
Quick Check
Think about why one way of opening files is preferred.
Recap: Loading Text Safely
You learned to open files with a with block, set utf-8 encoding, read whole text or line by line, and handle missing files. 📥
Frequently asked questions
Is the “Reading Text Files Into Python” lesson free?
Yes — the full text of “Reading Text Files Into Python” is free to read here on the web, and the NLP Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the NLP Academy course, upgrade to CoddyKit PRO.
What will I learn in “Reading Text Files Into Python”?
Open a document and load its contents. You practise NLP Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start NLP Academy?
No prior experience is required. NLP Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Reading Text Files Into Python” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this NLP Academy lesson?
Yes. Every NLP Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Strings, Characters, and Encodings
- Reading Text Files Into Python
- Counting Words and Characters
- Building Your First Word Frequency Table