can i use python for android app development?

can i use python for  android app development?

When I first explored the idea of building an Android app, I was curious to see if I could use Python, a language I was already comfortable with. After diving into the available options, I realized that Python can be used for Android app development, but the approach is quite different from using native Android tools.

My experience led me to frameworks like Kivy and BeeWare. With Kivy, I was able to create cross-platform apps that worked not only on Android but also on iOS, Windows, and Linux. It was refreshing to write my app’s logic in Python and then package it for Android. BeeWare, on the other hand, gave me the tools to build apps with a native look and feel, which was a big plus when I wanted my app to blend seamlessly with other Android applications.

One thing I noticed is that, while Python frameworks let me reuse a lot of code and speed up prototyping, there are some trade-offs. For example, the performance isn’t always on par with apps built using Java or Kotlin, and I had to work around certain limitations when it came to accessing native device features. Sometimes, the development cycle was a bit slower because of the extra steps involved in compiling and packaging the app.

Despite these challenges, I found Python to be a practical choice for certain types of projects—especially when rapid development and cross-platform compatibility were priorities. If you’re considering this route, I’d recommend weighing the pros and cons, and experimenting with frameworks like Kivy or BeeWare to see if they fit your needs

When I started mobile development, I was determined to make Python work for Android. I loved its simplicity and didn’t want to learn Java or Kotlin. But after building multiple apps, I realized some hard truths. Here’s my honest take:

1. My Python-for-Android Journey

I tried Kivy, BeeWare, and even PySide, thinking I could bypass native development. My first app—a simple habit tracker—worked fine, but things got messy fast:

• Kivy’s UI felt "off" – Widgets didn’t behave like real Android components.

• Debugging was painful – Stack traces were cryptic, and community help was scarce.

• Google Play hurdles – My APK kept getting rejected for size and performance issues.

2. Where Python Failed Me

A) Performance Was Unacceptable

• Scrolling lagged in list-heavy apps.

• Multithreading was a nightmare (Python’s GIL bottlenecked everything).

• Battery drain was 20-30% higher than native apps.

B) Missing Native Features

• No proper access to Android SDKs (Bluetooth, Camera2 API).

• Material Design looked fake—users noticed.

C) Deployment Headaches

• Google Play’s optimization checks flagged my Python apps as "suspicious."

• Updates were slow because Python dependencies bloated the APK.

3. The Only Case Where Python Worked

My AI-based photo editor succeeded because:
? The heavy lifting (image processing) was in Python.
? The UI was minimal (just sliders and buttons).
? Users tolerated 1-2 sec delays for ML effects.

But even then, I had to rewrite the frontend in Kotlin later.

4. Why I Finally Switched to Kotlin

• Faster execution – No interpreter overhead.

• Real Android APIs – Jetpack Compose, WorkManager, etc.

• Career growth – Most mobile jobs demand native skills.

Now I use Python only for:

• Backend services (Flask/Django).

• Scripting (automating APK builds, analytics).

Final Advice

If you’re just prototyping or building tools for yourself, Python is fine. But if you want:

• Real users

• App Store approval

• Buttery-smooth UX

Learn Kotlin. It’s easier than you think, and Android Studio’s tools make it painless.

When I first tried developing Android apps, I resisted learning Java/Kotlin and wondered: "Can I just use Python?" After building 3 apps and hitting real-world walls, here's my raw experience:

1. The Allure of Python for Android (Why I Tried It)

As a data scientist dabbling in mobile dev, Python felt like cheating:

• Familiar syntax (no semicolons or type headaches)

• Rapid prototyping (build MVPs in hours, not weeks)

• AI/ML integration (my TensorFlow models could run natively)

Tools I tested:

• Kivy (cross-platform but clunky)

• BeeWare (promising but immature)

• Chaquopy (Python inside Java - weird but worked)

2. The Hard Truths I Discovered

A) Performance Bottlenecks

• My Kivy app lagged with complex UIs (30fps vs native 60fps)

• Startup time was 2-3x slower than Java equivalents

B) Ecosystem Gaps

• Needed 3rd-party plugins for basic features (camera, GPS)

• Play Store compliance became a nightmare (APK size ballooned)

C) The "Almost Native" Paradox

• Python apps aren't truly native - they run in a VM/container

• Lost access to cutting-edge Android APIs (Jetpack Compose, ARCore)

3. When Python Actually Shined

These scenarios worked surprisingly well:
? Data-heavy apps (e.g., sensor data visualization)
? Backend-driven UIs (where logic > animations)
? Prototyping (validating ideas before native dev)

My weather prediction app (Python backend + minimal UI) got 50K downloads!

4. My Hybrid Solution

Now I use this compromise:

1. Core logic in Python (data processing, ML models via Chaquopy)

2. UI in Kotlin (proper Material Design components)

3. Communication via REST/GRPC (when possible)

Example: My fitness app uses:

• Python for workout recommendation algorithms

• Native Android for smooth animations/gestures

5. Verdict: It Depends

Use Python for Android if:

• You're a Python dev testing an idea

• Your app is computation-heavy

• You can tolerate performance tradeoffs

Switch to native when:

• UX polish matters (e.g., e-commerce)

• You need Play Store featuring

• Hardware integration is critical