Happy New Year! Flet project has reached ⭐️ 3.3K stars ⭐️ on GitHub which is very exciting and encouraging! Thank you all for your support!

We are starting this year with the release of Flet 0.3.2 bringing a long-awaited feature: creating standalone desktop bundles with a custom icon!

flet command has been used for running Flet program with hot reload, but we recently re-worked Flet CLI to support multiple actions.

There is a new flet pack command that wraps PyInstaller API to package your Flet Python app into a standalone Windows executable or macOS app bundle which can be run by a user with no Python installed.

Command's --icon argument is now changing not only executable's icon, but Flet's app window icon and the icon shown in macOS dock, Windows taskbar, macOS "About" dialog, Task Manager and Activity Monitor:

Bundle name, version and copyright can be changed too:

Find all available options for packaging desktop apps in the updated guide.

Upgrade Flet module to the latest version (pip install flet --upgrade), give flet pack command a try and let us know what you think!

This post is a continuation of Flet mobile strategy published a few months ago.

Our original approach to Flet running on a mobile device was Server-Driven UI. Though SDUI has its own benefits (like bypassing App Store for app updates) it doesn't work in all cases, requires web server to host Python part of the app and, as a result, adds latency which is not great for user actions requiring nearly instance UI response, like drawing apps.

I've been thinking on how to make Python runtime embedded into Flutter iOS or Android app to run user Python program. No doubt, it's technically possible as Kivy and BeeWare projects do that already.

Flet is a fast-evolving framework with a new functionality and bug fixes being committed every other day.

The development model with one pull request per release didn't work well for the project as users waited for weeks to get hands on a new release and, honestly, from development perspective producing large "heroic" releases takes a lot of energy 🫠.

From now on we'll be breaking releases into multiple pull requests with one feature/bugfix per PR.

Every PR merged into main branch will be publishing pre-release (developmental release) package to pypi.org having version format of X.Y.Z.devN.

We just released Flet 0.1.65 which is adding a bunch of mobile-optimized controls, fixing some bugs and introducing a new layout control - ResponsiveRow.

ResponsiveRow control​

ResponsiveRow borrows the idea of grid layout from Bootstrap web framework.

ResponsiveRow allows aligning child controls to virtual columns. By default, a virtual grid has 12 columns, but that can be customized with ResponsiveRow.columns property.

Similar to expand property every control now has col property which allows specifying how many columns a control should span. For example, to make a layout consisting of two columns spanning 6 virtual columns each:

import flet as ft

ft.ResponsiveRow([
    ft.Column(col=6, controls=ft.Text("Column 1")),
    ft.Column(col=6, controls=ft.Text("Column 2"))
])

We are thrilled to introduce Matplotlib and Plotly charting controls in Flet 0.1.63!

Matplotlib and Plotly are the most recognized Python charting libraries with a ton of features. They are greatly compatible with other scientific Python libraries such as Numpy or Pandas.

No doubt, it would be nearly impossible to replicate their functionality as pure Flutter widgets. Fortunately, both Matplotlib and Plotly can export charts into various formats, such as SVG. On the other hand Flet can display SVG images and that gives a perfect combination - Flet charting controls for Matplotlib and Plotly!

The resulting solution works so great that it's possible to display almost any example from Matplotlib and Plotly galleries - your imagination is the only limit!

Plot a simple bar chart:

a nice scatter with legend:

or some multi-chart contour plot:

Check the docs for Matplotlib and Plotly charting controls:

• MatplotlibChart
• PlotlyChart

Explore Flet chart examples.