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Python File Error: Why Same File Type Fails?

Getting errors when handling duplicate file types in Python? Learn what causes this issue and how to fix your file sorting logic.

byDev Solutions

February 16, 2026

⚠️ File systems sometimes treat file names differently based on capitalization. This often causes errors in Python when you work with files that have the same type.
🧠 If you do not handle duplicate file names correctly, Python might overwrite files when you sort them. This happens without you meaning to.
☁ Hidden or temporary system files can stop your scripts from working. You need to filter these files out.
🔄 Using pathlib makes sorting or grouping files by extension work better across different operating systems. This is a big plus.
🔒 When you put file actions inside try/except blocks, your script is less likely to crash. This helps with problems like permission or access errors.

Python File Error: Why Same File Type Fails?

If you're working on a Python script that works with many file types—especially those with the same extensions—and see strange things happen like missing files, overwritten content, or crashes, you're probably dealing with a common problem. It comes from not handling files well. You need to understand how Python reads file structures and names. Good sorting and checking methods are also key. These things help you make scripts that work well and can handle more data. This guide will explain what causes these errors. It also offers ways to fix them. And it will help you avoid the common “same file type error” in Python.

How Python Interacts with the File System

Python uses libraries like os, glob, and pathlib a lot to work with files. Each module does different things. But you also need to know how your operating system’s file setup might change how they work together.

Here is what matters most:

Windows: Does not care about capitalization — Report.txt is seen the same as report.TXT.
Linux/macOS: Cares about capitalization — treats Report.txt and report.txt as different files.

This difference matters a lot. It affects how you handle files across different operating systems. A Python script might work perfectly on macOS. But it could fail completely on Windows, and the other way around. This is especially true when files have similar names but different capitalization.

Grabbing Files Using `glob` and `pathlib`

An example using glob that is not always safe:

import glob
txt_files = glob.glob("*.txt")  # Returns list of .txt filenames in current directory

This way is simple. But it:

Does not return full paths.
It might not work the same way on symbolic links or systems that care about capitalization.

A better way to do this across all systems, using pathlib:

from pathlib import Path
txt_files = list(Path(".").glob("*.txt"))  # Returns Path objects, great for chaining

pathlib works more consistently on all systems. Also, it fits better with newer Python features like f-strings and type notes.

Common Root Cause: Bad File Handling Logic

Many Python file errors happen because of how you open, read, and work with files of the same type. This is often true for data processed by machines. The main reason is bad logic.

Consider:

for file in files:
    if file.endswith(".txt"):
        with open(file) as f:
            process(f.read())

This might work in a folder you control, with 3 files named file1.txt, file2.txt, file3.txt. But in real situations, you could run into these problems:

Files with the same names across different folders
Hidden system files (like macOS .DS_Store)
Files with the same base name but different cases, extensions, or encoding

Problems You Might Encounter

One file writing over another without you meaning to.
Working on the wrong file because names matched by mistake.
Files might be removed while the script is running. Then the script skips them.
Encoding problems (e.g., reading UTF-16 files with default UTF-8).

Common Mistakes When Sorting Files by Type

Sorting files in Python seems easy. But it can be tricky. Scripts often fail. This happens because people do not fully understand how duplicate files, odd cases, and file names work.

Common Mistakes

You might trust that only .txt files are in a folder.
- But files like notes.TXT, notes.txt~, or ~temp.txt also show up.
- To fix this: make extensions lowercase. Also, filter out unwanted files.
You might assume how set() or dict() handle positions. This is wrong.
- Sets automatically get rid of duplicate keys.
- If you use a dictionary where file names are keys, then the same names will write over each other.
You might ignore dotfiles and temporary files.
- On Unix-like systems, files starting with . (dot) are hidden.
- Files that start with ~ are temporary files made during editing.

Safer List Comprehension

files = [f for f in os.listdir() if f.endswith(".txt") and not f.startswith(".") and "~" not in f]

You can filter more using regular expressions to check file names. This helps stop you from working with badly named files by mistake:

import re
valid_name = re.compile(r"^[\w\-. ]+$")
files = [f for f in os.listdir() if valid_name.match(f) and f.endswith('.txt')]

Helpful Steps for Fixing Bugs: Find What’s Breaking

To fix file scripts that have bugs, people often use an old method. They add many print statements and check points to make sure things are correct.

Practical Debugging Steps

✅ Print the list of files beforehand:

print("Discovered files:", [file for file in os.listdir() if file.endswith('.txt')])

✅ Quick check for file name types:

for file in files:
    assert file.endswith('.txt'), f"Unexpected type: {file}"

✅ Print and inspect path before any file operation:

for file in files:
    print(f"Opening file: {file}")
    with open(file, "r") as f:
        data = f.read()

✅ Check for file name clashes:

from pathlib import Path
all_filenames = [p.name for p in Path("logs").rglob("*.log")]
duplicates = set([f for f in all_filenames if all_filenames.count(f) > 1])
print("Duplicate filenames found:", duplicates)

Using Python Modules Designed for File Handling

Different libraries offer their own strong points:

Module	Pros	Cons
`os`	Small and always ready to use	Works with raw strings only
`glob`	Good at finding patterns	Does not return Path objects
`pathlib`	Newer, object-oriented, lets you link methods together	Slightly more verbose

Best Option for All Cases

from pathlib import Path
files = list(Path(".").glob("*.txt"))

This gives you Path objects. You can change them using things like .stem, .suffix, .name, or .parent. This makes your code much easier to read and stronger.

Cleaning and Checking File Inputs

Checking your file inputs is the first thing to do. This helps when you work with many files.

1. Log file names before processing

with open("found_files_log.txt", "w") as log:
    for file in files:
        log.write(f"{file}\n")

2. Check for special characters in file names

import re
for file in files:
    if not re.match(r'^[\w\-. ]+$', file):
        print(f"Found a file name that is not allowed: {file}")

3. Skip files that cause problems

for file in files:
    if file.startswith('.') or file.endswith('~') or "temp" in file.lower():
        continue

Sorting and Grouping Files by Type

It helps to make groups of files based on their extensions. Use defaultdict to group files clearly:

from collections import defaultdict
from pathlib import Path

file_map = defaultdict(list)

for file in Path(".").iterdir():
    if file.is_file():
        file_map[file.suffix.lower()].append(file)

print(file_map[".txt"])

Using `itertools.groupby`

This works very well when you have long lists of files:

import itertools

sorted_files = sorted(Path(".").iterdir(), key=lambda x: x.suffix)
for ext, group in itertools.groupby(sorted_files, key=lambda x: x.suffix):
    print(ext, list(group))

Using Try/Except Blocks to Avoid File Failures

Do not just assume a file is there. Put your code in try/except blocks. This stops your script from crashing while it runs.

import traceback

for file in files:
    try:
        with open(file, "r") as f:
            content = f.read()
        # Further processing
    except FileNotFoundError:
        print(f"File not found: {file}")
    except PermissionError:
        print(f"Access denied to: {file}")
    except Exception as e:
        print("An unexpected error occurred")
        traceback.print_exc()

Also, think about writing down all files that cause problems to a .log file. Then a person can look at it.

Avoid Doing the Same Work on Files More Than Once

If a script runs many times (like a cron job), you should avoid doing the same work over again.

Use JSON to Keep Track of Files You Have Processed

import json
tracked_file = "processed.json"

if Path(tracked_file).exists():
    processed = json.load(open(tracked_file))
else:
    processed = []

for file in files:
    if file in processed:
        continue
    # Process file
    processed.append(file)

json.dump(processed, open(tracked_file, "w"))

Using When a File Was Last Changed

import os
import time

for file in files:
    if (time.time() - os.path.getmtime(file)) < 300:
        print(f"New or modified file: {file}")

Best Practices: Writing File Handling Code That Does Not Break Easily

🔹 Use full paths wherever possible.
🔹 Keep input and output folders apart. This helps avoid confusion.
🔹 Do not use 'magic strings.' Put extensions like ".txt" into variables or constants instead.
🔹 Test on dummy files before real runs.
🔹 Use consistent naming rules. This helps stop the 'same file type error.'
🔹 Add checks to stop repeated work. Log files that were processed and those that failed.

Case Study: File Sorting Error from Name Clash

Here is a real example from the Devsolus community.

Scenario

/logs/server1/access.log
/logs/server2/access.log

Problem

Files had the same names. But they came from different servers. When someone copied them to a shared folder, one file wrote over the other.

Solution

from pathlib import Path
import shutil

output = Path("combined_logs")
output.mkdir(exist_ok=True)

for file in Path("logs").rglob("*.log"):
    identifier = file.parent.name + "_" + file.name
    shutil.copy(file, output / identifier)

This way, the file name includes the original folder. For example, server1_access.log and server2_access.log. This keeps the original meaning.

Checklist to Avoid 'Same File Type' Errors in Python

✅ Always filter .txt, .log, etc., with clear checks.
✅ Make file extensions lowercase using .lower().
✅ Clean up file names. Take out special or unwanted characters.
✅ Use Path objects for files. Do not use strings.
✅ Keep track of errors and write them down. Then you can review them.
✅ Group files by Path.suffix or .endswith().
✅ Stop file names from clashing. Use folder names and name hashes.
✅ Check your code with unit tests. Also use files that cause problems.

Good design, strong checks, and the right tools can help you. You can avoid Python's most annoying file processing problems. Use pathlib, good error handling, and smart grouping. This way, you can build systems that work well as your data grows. And they won't break down when a file name shows up more than once.

Are you still getting a strange python same file type error? Join the Devsolus community. Let experienced Python developers look at your code.