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How To Python Read Txt File And Store Data In A List?
2025-07-07 17:10:05
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3 Answers
Isaac
2025-07-10 04:31:15
I remember when I first started coding in Python, I was super excited to work with files. Reading a .txt file and storing its data in a list is actually pretty straightforward. You can use the `open()` function to open the file, then loop through each line and append it to a list. Here's a simple way to do it:
`with open('yourfile.txt', 'r') as file:
data_list = [line.strip() for line in file]`
This code opens 'yourfile.txt' in read mode, strips any extra whitespace or newline characters from each line, and stores the cleaned lines in `data_list`. It's efficient and clean, perfect for beginners. If your file is huge, you might want to read it line by line instead of loading everything at once, but for most cases, this works like a charm.
`with open('yourfile.txt', 'r') as file:
data_list = [line.strip() for line in file]`
This code opens 'yourfile.txt' in read mode, strips any extra whitespace or newline characters from each line, and stores the cleaned lines in `data_list`. It's efficient and clean, perfect for beginners. If your file is huge, you might want to read it line by line instead of loading everything at once, but for most cases, this works like a charm.
Caleb
2025-07-08 02:10:22
Working with files in Python is one of those foundational skills that’s incredibly versatile. To read a .txt file and store its contents in a list, you can approach it in several ways depending on your needs. The most common method is using a context manager (`with` statement) to ensure the file closes properly after reading. Here’s a detailed example:
`with open('data.txt', 'r', encoding='utf-8') as f:
lines = f.readlines()
cleaned_lines = [line.strip() for line in lines]`
This reads all lines into `lines`, then strips whitespace and newline characters into `cleaned_lines`. If you’re dealing with large files, `readlines()` might consume too much memory. Instead, iterate directly over the file object:
`data = []
with open('large_file.txt', 'r') as file:
for line in file:
data.append(line.strip())`
This method is memory-efficient and scales well. For advanced use cases, like filtering specific lines or processing data on the fly, you can add conditions inside the loop. Python’s flexibility makes it easy to adapt to different file formats or data structures.
`with open('data.txt', 'r', encoding='utf-8') as f:
lines = f.readlines()
cleaned_lines = [line.strip() for line in lines]`
This reads all lines into `lines`, then strips whitespace and newline characters into `cleaned_lines`. If you’re dealing with large files, `readlines()` might consume too much memory. Instead, iterate directly over the file object:
`data = []
with open('large_file.txt', 'r') as file:
for line in file:
data.append(line.strip())`
This method is memory-efficient and scales well. For advanced use cases, like filtering specific lines or processing data on the fly, you can add conditions inside the loop. Python’s flexibility makes it easy to adapt to different file formats or data structures.
Yara
2025-07-11 20:26:31
I love how Python makes file handling feel almost magical. If you need to read a .txt file and dump its content into a list, here’s my go-to method. The `open()` function is your best friend, and list comprehensions keep things tidy. For example:
`file_path = 'notes.txt'
data = [line.rstrip('\n') for line in open(file_path, 'r')]`
This snippet opens 'notes.txt', iterates through each line, and removes the trailing newline character before adding it to the list `data`. It’s concise and Pythonic. If you’re paranoid about resource leaks (like me), wrap it in a `with` block:
`with open('notes.txt', 'r') as f:
data = [line.rstrip() for line in f]`
Bonus tip: If your file has blank lines or comments you want to skip, add a filter like `if line.strip()` inside the comprehension. Python’s simplicity lets you tweak this effortlessly for different scenarios.
`file_path = 'notes.txt'
data = [line.rstrip('\n') for line in open(file_path, 'r')]`
This snippet opens 'notes.txt', iterates through each line, and removes the trailing newline character before adding it to the list `data`. It’s concise and Pythonic. If you’re paranoid about resource leaks (like me), wrap it in a `with` block:
`with open('notes.txt', 'r') as f:
data = [line.rstrip() for line in f]`
Bonus tip: If your file has blank lines or comments you want to skip, add a filter like `if line.strip()` inside the comprehension. Python’s simplicity lets you tweak this effortlessly for different scenarios.
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