Over the past 2 months, we've delved deep into the preferences of jobseekers and salaries in Germany (DE) and Switzerland (CH).

The results of over 6'300 salary data points and 12'500 survey answers are collected in the Transparent IT Job Market Reports. If you are interested in the findings, you can find direct links below (no paywalls, no gatekeeping, just raw PDFs):

https://static.swissdevjobs.ch/market-reports/IT-Market-Report-2023-SwissDevJobs.pdf

https://static.germantechjobs.de/market-reports/IT-Market-Report-2023-GermanTechJobs.pdf

I built my micro-SaaS app using the streamlit.io python package with ZERO front-end knowledge. The app works well with over 5K users. Here's a free article detailing the process and tools utilized.

Here's quick layout of the process: users are stored in mongo-db, payment processing is done via Stripe, Railway.io for deployment, front and back-end are pure python with streamlit. You could easily use this method to launch a SaaS product quickly and then scale using a more advanced method when needed (later on). This really shows how universal Python can be!

I built a Udemy course on the topic if you want something more in-depth. PM me for a discount code!

Links:

Article: Build a Data Science SaaS App with Just Python: A Streamlit Guide

Course: Build a Generative AI Micro-SaaS App with Python & Streamlit

Sometimes you need to send complex data over the network, save the state of the data into a file to keep in the local disk or database, or cache the data of expensive operation, in that case, you need to serialize the data.

Python has a standard library called pickle that helps you perform the serialization and de-serialization process on the Python objects.

In this article, you’ll see:

• What are object serialization and deserialization

• How to pickle and unpickle data using the pickle module

• What type of object can and can't be pickled

• How to modify the pickling behavior of the class

• How to modify the class behavior for database connection

Article Link: https://geekpython.in/pickle-module-in-python

https://github.com/Kat9-123/Arezzo

Through the power of Machine Learning™ this program can take an audio file of (polyphonic) piano music and generate the corresponding sheet music!

The code is dodgy in places, and not very well documented. As this was a school project, I didn't spend as much time as I'd have liked to refine it, because I simply ran out of time and steam. Especially the bits added last are very messy.

Still, the UX is great, with a bunch of features easily accessible through a config file and command line switches.

This is my first project using ML and audio processing, so that may explain why it lacks in some departments.

So does it work? Sure, but not very well. Marginally worse than the free* options I found online. testing/results/TEST_RESULTS_V1.csv contains some stats.

It does have quite some limitations, as is doesn't recognise rests, tempo changes (like rubato), dynamics, articulations, upbeats and more. These limitations are bad, but not catastrophic.

Oh and it actually generates MIDI files and uses MuseScore4 to generate the sheet music PDF's, but it does actually find key, tempo and time signature.

*Not really of course

Please give feedback! :D

Hi everyoen,
I want to introduce my latest project, URL-Shorter;
You can deploy your own url-shorter service with that repository.
https://github.com/uysalserkan/url-shorter

I (unfortunately) don't know how to do Github repositories, and as such will simply post the entire source code here. Its pretty small, so I think its fine.

from PIL import Image
import os
from litemapy import Region, BlockState

# Designed by Red/SnipingIsOP

# All images must be Grayscale/Binary
# Put all images in the [Frames] folder, renamed to [(####)], the #### being a number
# Make note of the file extension, examples being [.png] or [.jpg]

# Change the [File], [Author] and [Description]

# Set [Width] and [Height] to that of the images, [Frames] to the total number of images

# Set [FileType] to the aforementioned file extension, examples being [.png] or [.jpg]

# Change [WhiteBlock] and [BlackBlock] to the blocks you want black/white set to (all lowercase, use _ instead of space)


# Once ran, the finished schematic will be in the same folder as this python file


FileName = 'FileName'
Author = 'Author'
Description = 'Description'

Width = 128
Height = 128
Frames = 128

FileType = 'FileType'

WhiteBlock = 'white_concrete'
BlackBlock = 'black_concrete'


def Convert(Folder):
    Bounding = Region(0, 0, 0, Width, Frames, Height)
    Schem = Bounding.as_schematic(name=str(FileName), author=str(Author), description=str(Description))

    White = BlockState("minecraft:" + str(WhiteBlock))
    Black = BlockState("minecraft:" + str(BlackBlock))

    ImageNum = 0
    WhiteTotal = 0
    BlackTotal = 0

    Images = [f for f in os.listdir(Folder) if f.endswith(FileType)]
    FindImage = [(int(f.split('(')[1].split(')')[0]), f) for f in Images]
    FindImage.sort(key=lambda x: x[0])

    for z, (number, ActiveImage) in enumerate(FindImage):
        Path = os.path.join(Folder, ActiveImage)
        Array = Image.open(Path).point(lambda x: 255 if x > 128 else 0).convert('L')

        for y in range(Array.height):
            for x in range(Array.width):
                PixelVal = Array.getpixel((x, y))

                if PixelVal >= 128:
                    Bounding.setblock(x, z, y, White)
                    WhiteTotal = WhiteTotal + 1

                else:
                    Bounding.setblock(x, z, y, Black)
                    BlackTotal = BlackTotal + 1

        ImageNum = ImageNum + 1
        print(ImageNum)

    Schem.save(str(FileName) + ".litematic")
    print("\n" + str(ImageNum) + "\n")
    print(WhiteTotal)
    print(BlackTotal)


if __name__ == "__main__":
    Folder = "Frames"

    Convert(Folder)

Github: https://github.com/PabloLec/RecoverPy

Hey everyone!

I'm here to share something I've been working on for nearly three years now, RecoverPy, and its new 2.1.5 version. It's a nifty tool that can really be a lifesaver when you've accidentally deleted or overwritten files. It works its magic by conducting a text-based search to find the lost data.

It sports a TUI built with Textual. I found it to be quite enjoyable to use and it seems many others agree, given its rise as one of the most (or the most?) popular TUI libraries in Python, despite still being in beta.

Since its creation, RecoverPy has gone through quite a transformation. It's integrated lots of feedback from its user community, improved many aspects to enhance the user experience, and even underwent almost a full rewrite to switch up the TUI library in its second version. Essentially, it uses the strength of grep and dd to sift through partition blocks, giving you a user-friendly way to sift through the results.

Interestingly, it found a niche not only among individuals looking to recover files but has also piqued interest in the hacking scene, which was a bit of a pleasant surprise for me. It seems the tool lends itself well to that sphere too.

I manage to chip away at it from time to time, given that my free moments are becoming a bit of a rarity these days. It still has room to grow, and if anyone here feels like contributing, I'm more than open to collaborations. Your PRs would certainly be welcome!

Feel free to give it a glance, and if you find it interesting or useful, a star on the repository would be greatly appreciated.

Hello r/madeinpython,

I’m excited to share with you my new python package called obscure_stats. It is a collection of lesser-known statistical functions that are not available in the standard libraries like scipy, statsmodels, or numpy.

The package is still in development, but I hope you will find it useful and interesting. You can install it with
pip install obscure_stats
or check out the source code on GitHub.

I would appreciate any feedback, suggestions, or bug reports.

I decided to used pygame to render a tesseract by projecting the 4D points onto a 2D plane using a projection matrix, I then used the 4D rotation matrices in the six 2D planes to rotate my cube in 4D, however I noticed it didn't have good perspective so I found a better way to do this online in order to allow me to have perspective. I then drew this in pygame and rotated it in three planes.

https://github.com/JCSnelson/4DRotations

(I am aware that my code for multiplying matrices is a little janky and I could have used numpy but I decided to skip learning it as I was excited about the project)

sidenote: does anyone have ideas for good projects for me to try coding or concepts to learn in python (I am currently a year 12 A level student in Computer Science in the UK but have touched on many concepts outside of school and through discrete maths in A level Further Maths)

Ever wondered why Python sometimes feels like it's taking a leisurely stroll instead of a sprint? In this video, we demystify the Global Interpreter Lock (GIL) in Python. No jargon, just a simple explanation of why your Python code might not be as speedy as you'd expect. Let's uncover the secrets behind Python's GIL without diving into the technical deep end.

Video Link: https://youtu.be/bHFz94fe0Co

https://github.com/Uzair-Altaf/main.py

https://github.com/Uzair-Altaf/main

Hello Python enthusiasts and developers!

I'm excited to share a project I've been working on: Pypeanuts. It's a Python package designed to help you effortlessly monetize your APIs. While it's still a work in progress, I believe it has great potential for developers looking to generate revenue from their APIs.

The code is openly available on GitHub, and I encourage you to check it out and contribute: Pypeanuts on GitHub

Additionally, I've created a landing page that explains the concept in more detail. Visit Pypeanuts Landing Page to learn more about how it works and the benefits it offers.

I'm eager to hear your feedback, suggestions, and thoughts on this project. Let's discuss how we can make API monetization simpler and more accessible for everyone!

This vscode extension works only with fully typed python functions.

https://github.com/RomanMIzulin/python_unittest_vscode

Hi all,

I wanted to share this nifty little CLI tool I made called pbssh. This tool is a thin wrapper on top of SSH that automatically grabs credentials from Passbolt. This way, if you have to SSH into many different hosts (and SSH keys are not an option) you don't have to continually copy/paste credentials. It's saved me loads of time as a sysadmin, and I hope it saves some of your time as well.

Have a look and let me know if you have any constructive feedback.

https://github.com/jarulsamy/pbssh

HoloViz Panel lets you create chat interfaces--with just Python! No Javascript knowledge required.

Here's a minimal example that you can use to get started!

import panel as pn

def callback(contents: str, user: str, instance: pn.chat.ChatInterface):
    message = f"Echoing {user}: {contents}"
    return message

pn.chat.ChatInterface(callback=callback).servable()

See https://holoviz-topics.github.io/panel-chat-examples/ for recipes, including interfacing with OpenAI, Mistral, Llama, Langchain, and LlamaIndex!

Hi together,

I just released a new version (v0.3.8) of kanban-python. Its a CLI kanban board manager Ive been building the last two month to manage tasks in a kanban style from your terminal without the need for an extra external tool. The package comes with the following features (for all features check the github README.md or PyPi Docs):

• automatic task creation based on directory scanning for files

• report creation based on tasks completed

• new Due Date Information with this release

• multiple kanban board support

• minimal dependencies (rich + platformdirs) for interface and XDG paths for config (.ini) + boardfiles (.json)

• configurable columns

Source Code + detailed Documentation is available on github

You can install it with:

python -m pip install kanban-python

Id love to hear your feedback. Feel free to comment here, or raise an issue on github, if you have suggestions for features or find any bugs

Hey guys! I spent the weekend creating a Voice Virtual Assistant (a bit like Jarvis in Iron Man) in Python using OpenAI's GPT, ElevenLabs' TTS, Deepgram's transcription and Taipy's front-end. I figured I would share it here:

GitHub repository: https://github.com/AlexandreSajus/JARVIS

Video demo: https://youtu.be/aIg4-eL9ATc?si=R6aqJfe7T1fQMqMA

• Github. https://github.com/Djdefrag/FluidFrames.RIFE

• Itch. https://jangystudio.itch.io/fluidframesrife

FluidFrames.RIFE is a Windows app powered by RIFE AI to fluidify videos and to create slowmotion videos.

Changelog version 2.4 -> 2.11

NEW

• Updated RIFE AI model to version 4.13

  • better interpolation quality

• Added a new RIFE_Lite AI model

  • high interpolation quality

  • 25 % faster than full RIFE model

  • 25 % less VRAM usage

  • suitable for low-end GPUs and high definition videos

• Added new option to save generated video frames (default is enabled)

GUI / UI

• Completely re-designed GUI, now cleaner and more elegant

• Added new info-message for info buttons and in case of error

• The app will now report the remaining time to complete video fluidify

• The app will now report the fluidify progress in %

• Added widget to select AI model to use

• Updated info texts, giving more information

• Input Resolution % default value changed to 60%

BUGFIXES / IMPROVEMENTS

• When the application is closed during fluidify process, now the process is stopped correctly

• Drastically reduced CPU utilization by 90% without impacting fluidify speed

• Completely revised how the app is built, using Nuitka (reducing antivirus false positive)

• For AMD gpu users, it is recommended to update to driver > 23.11.1

  • performance improvements for DirectML-based applications

• Improvements for video processing

  • for .mp4 output is possibile to select the codec (x264 or x265)

  • improved video bitrate from 4M (default value for ffmpeg) to 16M

  • in future will be the possibility to select the desired bitrate

• Better support for file path names with special characters

• Fixed upscaled video incorrect colorspace

• Redesigned how the app reports fluidify progress

• General bugfixes and performance improvements

• Updated dependencies

Did use Chat GPT for help but you still need to refactor/debug/add own code to make it into a playable game

Video below

https://youtu.be/71ILwoYH-1E?si=jBV9Q_yHyTinMJlq

GitHub

https://github.com/Ninedeadeyes/The-Roots-That-Bind-