Was Setting Up a Python Environment Like Falling in Love!? ~A Beginner Engineer's Journey to a Laid-back Python Life~ #50

1. Intro: Starting Python is a Battle with the Environment

Honestly, at first, I thought, "Isn't Python something you can just start using as soon as you install it?"

But in reality, I couldn't even get to the point of writing code. Phrases like "It's easy once you set up the environment," which sounded like seasoned software engineer talk, were completely meaningless to me at the time.

"No, I'm struggling because I can't decode the spell called 'environment setup'!" I would retort in my head.

So, I decided to escape from reality for a bit. Just as I was about to commit to "I'll just live my life in Excel..."

But then, a work project came up where I absolutely had to use Python. As a last resort, I roped in a junior colleague in their second year of work.

I made a desperate plea while offering coffee and dinner. "I'm sorry! I don't understand what 'environment setup' means! Nothing I look up makes sense! Please, just teach me how to start!"

The junior colleague laughed with a look of disbelief but taught me step-by-step. "The free office coffee won't cut it, you know... lol" "I know! I'll get you a large one from Komeda's Coffee!" "...So not Starbucks, then? lol"

From that day on, my Python story began. Installation, path settings, Anaconda, Jupyter... I spent nights in trial and error, clutching my head at the parade of words I didn't understand. But strangely, I was making progress, little by little.

2. First Love: Meeting Jupyter Notebook

The junior colleague recommended "Anaconda" and "JupyterLab." The reason was, "It's easy because it comes with a bunch of packages pre-installed."

...Wait, packages?

Me: "pip? I know HIP!" Junior: "Let's skip that joke... pip is an installer for adding Python libraries."

Still, I was grateful to the junior colleague who said, "I'll help you!" and did it with me.

When I was finally able to perform calculations and visualizations with pandas, it felt like a magic notebook. This was the moment I first felt, "Python is fun!"

However, I didn't know at the time that
many people choose VS Code over Jupyter depending on the use case.

As a result, I was in a state of "feeling like a genius inside the notebook, but a total klutz outside of it." It's a fond memory now how I mass-produced notebooks in my company PC's folders and couldn't tell which one was the real one.

3. An Adult's Partner: Visual Studio Code

I asked a software engineer, "What kind of environment do you usually write code in? I don't really get what 'environment' means, though lol." The engineer replied, "VS Code is easy to use. You can even run Jupyter with extensions."

...What! They're suddenly so kind once I can write a little bit of code!

I installed it right away.
I was intimidated by all the English when I launched it, but I found out I could change it to Japanese if I looked it up.
I see, so that's what extensions are.

From then on, I fell into the rabbit hole of extensions, spending more time choosing themes than writing Python code.

It was like a game of 'decorating my PC'.

But looking back calmly, my code was still leaning heavily on Excel.
I even ended up typing '.ipynb' instead of '.py' for the file extension.

VS Code is a mature partner.
But inside, I was still just an Excel kid.

4. Studying Abroad: Google Colab

The next thing I encountered was a savior that freed me from the shackles of my PC environment.
That was Google Colab.

When I heard a student I was working on a project with say, 'I'm using Python on a Mac',
'Who are you, some kind of rich kid?!'
I retorted.

As a Power BI lover, it was a shock.

It won't run on a Mac!

But that's where I discovered the interactive graphing library Plotly.

'This is just like Power BI!' I was instantly hooked.

Plus, Colab runs as long as you have a browser.
And you even get a GPU for free.
My excitement was at its peak!

However, I was brought to tears many times by the forced breakup event known as 'runtime disconnection'.
Yesterday's hard work, gone in an instant...

Still, being able to share notebooks with friends is the best.
It was truly like a 'study abroad romance'—exciting and addictive.

5. Summary: Python environments are like romance

• Jupyter Notebook: First love. Pure and fun.

• VS Code: A slightly more mature partner. High freedom, but requires care.

• Google Colab: A study abroad romance. Exciting, but unstable.

They all have their good points, so in the end, using them for different purposes is best.

6. The Punchline: And Now

I've wandered through many environments, but to be honest...
I still don't understand environment design (lol).
But it's funny, I've settled into a dual-wielding style of Google Colab and VS Code now.

Running things quickly in Colab, and doing some 'ambitious' analysis in VS Code.
Rather than racking my brain over environment setup, it's enough to just enjoy 'making it work'.
I realized that Python is a language with enough depth to allow for that kind of 'laid-back' approach.

Rather than building the perfect environment, focus on enjoying the process and keeping at it.
That is the conclusion of my Python life.

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