Today we’re going to talk about one of those ***** issues that can make you want to throw your computer out the window ‘bad mtime’. If you’ve ever encountered this on Windows, you know what I’m talking about. But no need to get all worked up, because in this guide, we’ll be diving into Python’s bad mtime issue and how to fix it once and for all!
So, let’s start with the basics. What is ‘bad mtime’? Well, if you’re unfamiliar with the term, it stands for “bad modification time”. Essentially, when a file is modified on Windows (like when we run our Python scripts), its modification timestamp gets set to the current date and time. However, sometimes this timestamp can get messed up due to various factors like system clock issues or network latency.
Now, how this affects us in the world of Python. When you import a module that has been modified on disk (like when we run our scripts), Python checks its modification time to see if it needs to be reloaded. If the timestamp is ‘bad’, then Python will think that the file hasn’t changed and won’t load the updated version, even though there have actually been changes made!
This can cause all sorts of issues like slow startup times for your scripts or unexpected behavior due to outdated code being loaded. So, how do we fix this? Well, one solution is to simply delete the .pyc files that Python generates when it compiles our modules (these are the ones with the ‘bad mtime’ issue). However, this can be a pain if you have a lot of scripts or if you want to keep your code organized.
Another option is to use a tool like ‘touch’ on Linux/MacOS or ‘ren’ on Windows to reset the modification timestamp for our Python files. This will force Python to reload the updated version and avoid any issues with ‘bad mtime’. Here’s an example of how you can do this using ‘touch’ in Bash:
#!/bin/bash
# This is a bash script that uses the 'touch' command to reset the modification timestamp for a Python file.
# This is done to avoid any issues with 'bad mtime' when reloading the updated version of the file.
# First, we need to specify the file we want to reset the timestamp for.
# In this case, we will use 'my_script.py'.
file="my_script.py"
# Next, we use the 'touch' command to update the modification timestamp for the specified file.
# This will force Python to reload the updated version of the file.
touch "$file"
# Finally, we can check the modification timestamp for the file to ensure it has been updated.
# This can be done using the 'stat' command.
stat "$file"
# The script is now complete and the modification timestamp for 'my_script.py' has been reset.
This will reset the modification timestamp for our script, forcing Python to reload it when we run it again. However, if you’re on Windows and don’t have access to a Unix-like shell like Bash, then you can use ‘ren’ instead:
@echo off
REM This line turns off the command echo, preventing the commands from being displayed in the console
REM This line resets the modification timestamp for our script, forcing Python to reload it when we run it again
C:\> ren my_script.py my_script.py1
REM This line renames the original script to a temporary name, allowing us to rename it back to its original name in the next line
C:\> ren my_script.py1 my_script.py
REM This line renames the temporary script back to its original name, effectively resetting the modification timestamp for the script
This will rename our script and force Python to reload it when we run it again, effectively resetting the modification timestamp. Now, some common causes of ‘bad mtime’. One major cause is network latency if your computer’s clock isn’t synced with a reliable time server (like NTP), then you may experience issues with ‘bad mtime’. This can be especially problematic when working on large projects or collaborating with others.
Another common issue is system clock drift, which can occur due to various factors like power outages or hardware failures. To avoid this, it’s a good idea to regularly check your computer’s time and adjust it as needed (you can do this using the ‘date’ command in Bash).
Finally, some best practices for avoiding ‘bad mtime’. One simple solution is to use version control systems like Git or SVN to manage our code. This will allow us to easily track changes and avoid any issues with ‘bad mtime’, as well as provide a backup of our code in case anything goes wrong.
Another option is to use tools like ‘pyinstaller’ or ‘cx_Freeze’ to package our Python scripts into executable files, which can help us avoid any issues with ‘bad mtime’ and make it easier to distribute our code to others.