GitHub Stars

I like maces’s [1] project fastapi-htmx [2]. Extension for FastAPI [3] to make HTMX [4] easier to use. References: [1]: https://github.com/maces [2]: https://github.com/maces/fastapi-htmx [3]: /fastapi/ [4]: /htmx/

The work on interpreters [1] by ericsnowcurrently [2]. a placeholder References: [1]: https://github.com/ericsnowcurrently/interpreters [2]: https://github.com/ericsnowcurrently

Check out coolify [1] by coollabsio [2]. It’s a well-crafted project with great potential. An open-source & self-hostable Heroku / Netlify / Vercel alternative. References: [1]: https://github.com/coollabsio/coolify [2]: https://github.com/coollabsio

The next version of markata will be around a full second faster at building it’s docs, that’s a 30% bump in performance at the current state. This performance will come when virtual environments are stored in the same directory as the source code. [1] What happened?? # [2] I was looking through my profiler for some unexpected performance hits, and noticed that the docs plugin was taking nearly a full second (sometimes more), just to run glob. | |- 1.068 glob markata/plugins/docs.py:40 | | |- 0.838 <listcomp> markata/plugins/docs.py:82 | | | `- 0.817 PathSpec.match_file pathspec/pathspec.py:165 | | | [14 frames hidden] pathspec, <built-in>, <string> Python scandir ignores hidden directories # [3] I started looking for different solutions and what I found was that I was hitting pathspec with way more files than I needed to. len(list(Path().glob("**/*.py"))) # 6444 len([Path(f) for f in glob.glob("**/*.py", recursive=True)]) # 110 After digging into the docs I found that glob.glob uses os.scandir which ignores ‘.’ and ‘..’ directories while Path.glob does not. https://docs.python.org/3/library/os.html#os.scandir results? # [4] Now glob.py from the docs plugin does not...

I’m impressed by minijinja [1] from mitsuhiko [2]. MiniJinja is a powerful but minimal dependency template engine for Rust compatible with Jinja/Jinja2 References: [1]: https://github.com/mitsuhiko/minijinja [2]: https://github.com/mitsuhiko

I’m really excited about gpt-engineer [1], an amazing project by AntonOsika [2]. It’s worth exploring! Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from https://gptengineer.app References: [1]: https://github.com/AntonOsika/gpt-engineer [2]: https://github.com/AntonOsika

I like s0md3v’s [1] project roop [2]. one-click face swap References: [1]: https://github.com/s0md3v [2]: https://github.com/s0md3v/roop

tidwall [1] has done a fantastic job with jj [2]. Highly recommend taking a look. JSON Stream Editor (command line utility) References: [1]: https://github.com/tidwall [2]: https://github.com/tidwall/jj

I recently discovered elia [1] by darrenburns [2], and it’s truly impressive. A snappy, keyboard-centric terminal user interface for interacting with large language models. Chat with ChatGPT, Claude, Llama 3, Phi 3, Mistral, Gemma and more. References: [1]: https://github.com/darrenburns/elia [2]: https://github.com/darrenburns

global Field global BaseModel from pydantic import BaseModel from pydantic import Field Pydantic is a Python library for serializing data into models that can be validated with a deep set of built in valitators or your own custom validators, and deserialize back to JSON or dictionary. Installation # [1] To install pydantic you will first need python and pip. Once you have pip installed you can install pydantic with pip. pip install pydantic Always install in a virtual environment [2] Creating a Pydantic model # [3] To get started with pydantic you will first need to create a Pydantic model. This is a python class that inherits from pydantic.BaseModel. from pydantic import BaseModel from pydantic import Field from typing import Optional class Person(BaseModel): name: str = Field(...) age: int parsing an object # [4] person = Person(name="John Doe", age=30) print(person) name='John Doe' age=30 data serialization # [5] Pydantic has some very robust serialization methods that will automatically coherse your data into the type specified by the type-hint in the model if it can. person = Person(name=12, age="30") print(f'name: {person.name}, type: {type(person.name)}')...

The work on cal.com [1] by calcom [2]. Scheduling infrastructure for absolutely everyone. References: [1]: https://github.com/calcom/cal.com [2]: https://github.com/calcom

AUR [1].">paru is an aur helper that allows you to use a package manager to install packages from the aur. What’s the Aur # [2] The Aur is a set of community managed packages that can be installed on arch based distros. Why a helper? # [3] paru just makes it easy, no clone and run makepkg. You can do everything paru can do using the built in pacman installer. Manual Install from the Aur # [4] You will need to manually instal pacman from the aur in order to get started. sudo pacman -S --needed base-devel git clone https://aur.archlinux.org/paru.git cd paru makepkg -si Installing packages with paru # [5] Once setup you are ready to install packages from the AUR just like the core repos. # you can update your system using paru paru -Syu # you can install packages from the AUR paru -S tailscale paru -S prismlauncher # even core repo packages can be installed paru -S docker Paru in Docker # [6] Here is a snippet from my devtainer dockerfile [7]. Where I use paru to install packages from the AUR inside of a dockerfile. FROM archlinux RUN echo '[multilib]' >> /etc/pacman.conf && \ echo 'Include = /etc/pacman.d/mirrorlist' >> /etc/pacman.conf && \ pacman --noconfirm -Sy...

The work on hardtime.nvim [1] by m4xshen [2]. Establish good command workflow and quit bad habit References: [1]: https://github.com/m4xshen/hardtime.nvim [2]: https://github.com/m4xshen

I’m impressed by trogon [1] from Textualize [2]. Easily turn your Click CLI into a powerful terminal application References: [1]: https://github.com/Textualize/trogon [2]: https://github.com/Textualize

I’m impressed by swenv.nvim [1] from AckslD [2]. Tiny plugin to quickly switch python virtual environments from within neovim without restarting. References: [1]: https://github.com/AckslD/swenv.nvim [2]: https://github.com/AckslD

I’m really excited about pylyzer [1], an amazing project by mtshiba [2]. It’s worth exploring! A fast, feature-rich static code analyzer & language server for Python References: [1]: https://github.com/mtshiba/pylyzer [2]: https://github.com/mtshiba

I’m impressed by pandas-ai [1] from sinaptik-ai [2]. Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG. References: [1]: https://github.com/sinaptik-ai/pandas-ai [2]: https://github.com/sinaptik-ai

If you’re into interesting projects, don’t miss out on frogmouth [1], created by Textualize [2]. A Markdown browser for your terminal References: [1]: https://github.com/Textualize/frogmouth [2]: https://github.com/Textualize

Check out forge [1] by dfee [2]. It’s a well-crafted project with great potential. forge (python signatures) for fun and profit References: [1]: https://github.com/dfee/forge [2]: https://github.com/dfee

I like Slackadays’s [1] project Clipboard [2]. 😎🏖️🐬 Your new, 𝙧𝙞𝙙𝙤𝙣𝙠𝙪𝙡𝙞𝙘𝙞𝙤𝙪𝙨𝙡𝙮 smart clipboard manager References: [1]: https://github.com/Slackadays [2]: https://github.com/Slackadays/Clipboard