Use Python without installing on Windows

For some weeks, I went back to Barcelona to renew documents and meet friends. And, of course, to enjoy the sun but that's implicit :)

(this is not the friend I talk about in the story!)

It’s funny how on videocalls you usually don’t get past the life updates, but in a face to face conversation everything flows better. While I’m a fan of working remotely, I do appreciate that f2f has its advantages. It was in one of those where a friend was telling me how in his work as an Industrial Engineer he needs to do what I usually call a “monkey job”, many times a month.

Disclaimer:

• The code in this post is not optimal, and does not pretend to be. But it works, and my friend does not really care about it taking 1 or 5 seconds, or some stuff being hardcoded. The objective is just to show something working end to end.
• I did all development in my Bootcamp’d Windows 10, where I installed Python. Tested in two native Windows 10 machines, where Python was not installed.

The problem

My friend works, among many other things, configuring the sensors and widgets that interact with chemical reactors to produce drugs. Oftentimes, he needs to modify the configuration by updating some values. His current approach is to open the file with Notepad++ and use find/replace some dozens of times. In addition to automation, he would like to delegate the task to to more junior employees but it is somewhat risky as any mistake might make the whole production to stop.

In this regard, he was asking me whether this could be automated, and how I would do it. As a Data Scientist working 99% of the last 6 years with Python, I obviously suggested to use this. The way I framed it was the following. Someone (him) would add a configuration file where each row would be a tuple with the keyword to find and the keyword to replace. Then, a Python script would take the input file and generate an output file given the configuration. For someone seasoned in Python, the above is no more than 10min coding. Easy-peasy.

Let’s see an example of what I had in mind after my first answer:

config.csv:

 input,output
 PROTOCOL_A, PROTOCOL_B
 DRUG_X, DRUG_Y

main.py:

 import re
 import pandas as pd

 if __name__ == "__main__":

     config = pd.read_csv("config.csv", index_col=0).output.to_dict()
     print(config)

     with open("input_file.csv", "r") as f:
         text = f.read()
     print(text)
     print()
     for input_value, output_value in config.items():
         text = re.sub(input_value, output_value, text)

     print(text)
     with open("output_file.csv", "w") as f:
         f.write(text)

Cool, so with a few lines of code it's solved. My friend, though, does not know Python at all, and his natural follow-up question was:

• Ok, but how Python works? Do I have to install anything?
• Well… yes. But it’s minimal. Nothing to worry about.
• I don’t want to install anything. Can’t we do this with a “.exe” or “.bat”? I’m sure you can code in Windows without having to install Python.

While for some folks the above questions might be excessive, there is an underlying motivation in all these, which I then discovered. He wants to use this in the client’s machine, having Windows, where he cannot install anything.

The solution

CX_freeze is a Python library that

creates standalone executables from Python scripts, with the same performance. It is cross-platform and should work on any platform that Python itself works on.

The solution is then straightforward. Install cx_freeze and just run:

cxfreeze -c main.py

and it should work. Does it? Well, the reality is that there is an annoying dependency Windows needs called vcruntime140.dll. I’m not sure what this does, but I just downloaded it (there are thousands of places where you can find it), and placed it next to the python3.dll file. After this, it worked like a charm!

Lighweighting the package

The above is enough for a minimum PoC, but produces a 134 MB package. How come? This is just a few lines of code! Well, the reason is we are using pandas, a Python library that can do many other things, but absolutely not required for this trivial task. Let’s do everything with the Python standard library and remove the dependency:

 import re

 if __name__ == "__main__":

     with open("config.csv", "r") as f:
         lines = f.readlines()
     config = [line.strip().split(",") for line in lines]
     config = {i[0]: i[1] for i in config[1:]}
     print(config)

     with open("input_file.csv", "r") as f:
         text = f.read()
     print(text)
     print()
     for input_value, output_value in config.items():
         text = re.sub(input_value, output_value, text)


     print(text)
     with open("output_file.csv", "w") as f:
         f.write(text)

In addition to this, I found out that the Python version also impacts the final package size:

python	pandas	size
3.9	Y	134 MB
3.9	N	30 MB
3.8	N	30 MB
3.7	N	16 MB

So I recreated my conda environment with 3.7 as in:

conda create -n find_replace_script python=3.7

and produced the final package, obtaining a tiny 8MB file after zip compression.

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And that's all for today, hope you enjoyed the story, or find this useful if you arrive here via Google Search :)

Don’t hesitate to ask me if you have questions about the above. Have fun!