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Converting Python Kivy to Android APK using Google Colab
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#kivy android app development #PyhtonProgramming #Kivymd #Mobileapp
In this lecture we will learn to create .apk file of an Kivy based calculator application
The Google Colab Way!
The conversion requires a Linux environment and Google provides it for free! If you belong to Data Science or Deep learning background then you must be aware of this platform.
It provides you a virtual machine with 75GB space, 12GB RAM, and around 12GB GPU power! You can use this platform to perform model training, checking logs, or running Python codes.
As this is a Linux based system, now the only thing required is to install the dependencies and initiate the process.
Link to access the Google colab notebook:
You can directly use my colab notebook where you just need to run all the cells, that’s it!
a) !pip install buildozer
b) !pip install cython==0.29.19
c) !sudo apt-get install -y \
python3-pip \
build-essential \
git \
python3 \
python3-dev \
ffmpeg \
libsdl2-dev \
libsdl2-image-dev \
libsdl2-mixer-dev \
libsdl2-ttf-dev \
libportmidi-dev \
libswscale-dev \
libavformat-dev \
libavcodec-dev \
zlib1g-dev
d) !sudo apt-get install -y \
libgstreamer1.0 \
gstreamer1.0-plugins-base \
gstreamer1.0-plugins-good
e) !sudo apt-get install build-essential libsqlite3-dev sqlite3 bzip2 libbz2-dev zlib1g-dev libssl-dev openssl libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libncursesw5-dev libffi-dev uuid-dev libffi6
f) !sudo apt-get install libffi-dev
g) !buildozer init
h) !buildozer -v android debug
i) !buildozer android clean
Before running the cells, make sure to upload your app code to the colab notebook and after running the bulldozer init command, make sure to edit the specs file generated and nothing else!
This is the easiest and most convenient way to build apps without the need for an actual system!
In this lecture we will learn to create .apk file of an Kivy based calculator application
The Google Colab Way!
The conversion requires a Linux environment and Google provides it for free! If you belong to Data Science or Deep learning background then you must be aware of this platform.
It provides you a virtual machine with 75GB space, 12GB RAM, and around 12GB GPU power! You can use this platform to perform model training, checking logs, or running Python codes.
As this is a Linux based system, now the only thing required is to install the dependencies and initiate the process.
Link to access the Google colab notebook:
You can directly use my colab notebook where you just need to run all the cells, that’s it!
a) !pip install buildozer
b) !pip install cython==0.29.19
c) !sudo apt-get install -y \
python3-pip \
build-essential \
git \
python3 \
python3-dev \
ffmpeg \
libsdl2-dev \
libsdl2-image-dev \
libsdl2-mixer-dev \
libsdl2-ttf-dev \
libportmidi-dev \
libswscale-dev \
libavformat-dev \
libavcodec-dev \
zlib1g-dev
d) !sudo apt-get install -y \
libgstreamer1.0 \
gstreamer1.0-plugins-base \
gstreamer1.0-plugins-good
e) !sudo apt-get install build-essential libsqlite3-dev sqlite3 bzip2 libbz2-dev zlib1g-dev libssl-dev openssl libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libncursesw5-dev libffi-dev uuid-dev libffi6
f) !sudo apt-get install libffi-dev
g) !buildozer init
h) !buildozer -v android debug
i) !buildozer android clean
Before running the cells, make sure to upload your app code to the colab notebook and after running the bulldozer init command, make sure to edit the specs file generated and nothing else!
This is the easiest and most convenient way to build apps without the need for an actual system!
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