Paul Creusy PaulCreusy

How to create adaptive icons for Android application with Buildozer and Kivy

This document aims to explain how to create adaptive icons for Android applications developed with Kivy and compiled with Buildozer.

Context 📖

The configuration file buildozer.spec allows you to specify an icon to use for your application by editing the following portion of the file :

# (str) Icon of the application

Instructions to create automatic sphinx documentation based on app modules and packages

Install required packages

Install the following packages.

sphinx==7.2.6
sphinx_rtd_theme==2.0.0

How to self-sign a Windows package created with Pyinstaller

This document aims to explain all the necessary steps to self-sign a Windows executable.

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Prerequisites

Please make sure to match all the prerequisite before starting the process of signing the package.

Introduction

Recently Google made it compulsory that all new apps must be uploaded not as .apk files but as .aab files. Till just recently the tool Buildozer was only able to compile your python applications to .apk but recent changes have allowed us to compile to .aab format. This is an instruction set that can be used to create a release .aab.

What is an AAB

The new .aab format may be a little confusing. .aab stands for app bundles and consists of a bundle of apk's within it. When you upload an aab to the playstore you are basically uploading a bunch of apk. PlayStore then based on the device that is downloading your application will generate the required apk based on that devices architecture and other parameters.

The introduction of .aab doesn't mean that .apk are no longer useful. .aab are only used for releases where as .apk are still used for testing your application and sharing it with others to directly install(not through the store).

> Note: Test your applications

	import matplotlib.pyplot as plt
	import networkx as nx
	import numpy as np

	def plot_neuron_level_nid(model):
	"""
	Plot a neuron-level Neural Interpretation Diagram (NID) for a TensorFlow model,
	including biases.

	Parameters:

	__version__ = '1.0'

	from kivy.app import App
	from kivy.uix.boxlayout import BoxLayout
	from kivy.uix.label import Label
	from kivy.clock import Clock


	# Android NFC-specific imports
	from jnius import autoclass, cast

	import requests
	from azure.identity import InteractiveBrowserCredential

	# Define your Azure AD client ID
	client_id = ...

	# Define the Microsoft Graph API scope
	scope = ["User.Read"]

	# Create the InteractiveBrowserCredential instance

	from azure.identity import UsernamePasswordCredential

	credential = UsernamePasswordCredential(
	client_id="client_id_found_in_azure",
	username="email",
	password="password",
	)

	print(credential.get_token("https://graph.microsoft.com/.default"))

	def levenshtein(chaine1, chaine2):
	n = len(chaine1)
	m = len(chaine2)
	d = [[0 for j in range(m + 1)] for i in range(n + 1)]
	for i in range(0, n + 1):
	d[i][0] = i
	for j in range(0, m + 1):
	d[0][j] = j
	for i in range(0, n):
	for j in range(0, m):

	import os
	import tkinter as tk
	from tkinter import ttk

	class ScrollableFrame(ttk.Frame):
	def __init__(self, container, args, *kwargs):
	super().__init__(container, args, *kwargs)
	canvas = tk.Canvas(self, takefocus=0, highlightthickness=0)
	self.canvas = canvas
	scrollbar = ttk.Scrollbar(self, orient="vertical", command=canvas.yview)