Allgemein – Developer Blog

Wer in Docker-Containern Python-Abhängigkeiten mit pip verwaltet, sollte einen Blick auf uv von Astral werfen. Dieses Tool bietet deutlich schnellere Installationen und robustere Verwaltung der Abhängigkeiten. Besonders für Django-Projekte in der CI oder Produktion kann das Build-Tempo spürbar verbessert werden. Auch die Pflege und das Aktualisieren der Abhängigkeiten werden einfacher.

`uv` im Dockerfile einbinden

Die empfohlene Methode nutzt ein Multi-Stage-Build, um das aktuelle uv-Binary direkt ins Image zu kopieren:

COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv

So spart man sich die Installation via pip oder Paketmanager und bleibt immer aktuell.

Wichtige Umgebungsvariablen

Im Dockerfile werden zentrale Umgebungsvariablen gesetzt:

ENV UV_PROJECT_ENVIRONMENT=/venv \
    UV_NO_MANAGED_PYTHON=1 \
    UV_PYTHON_DOWNLOADS=never \
    VIRTUAL_ENV=/venv

UV_NO_MANAGED_PYTHON=1: uv verwaltet Python nicht selbst.
UV_PYTHON_DOWNLOADS=never: Downloads werden komplett deaktiviert.
UV_PROJECT_ENVIRONMENT=/venv: Virtuelle Umgebung wird unter /venv verwaltet.

Performance-Verbesserungen

ENV UV_COMPILE_BYTECODE=1 \
    UV_LINK_MODE=copy \
    UV_CACHE_DIR=/app/.cache/uv

Bytecode wird beim Installieren erzeugt (.pyc), schnellere Startzeit.
Hardlink-Probleme werden durch Kopieren vermieden.
Caching via Docker-Mounts beschleunigt Builds enorm.

Sicherheit und Reproduzierbarkeit

ENV UV_FROZEN=1 \
    UV_REQUIRE_HASHES=1 \
    UV_VERIFY_HASHES=1

Nur exakt definierte Versionen werden installiert.
Jeder Download wird über einen kryptografischen Hash abgesichert.

Abhängigkeiten installieren

RUN uv venv $VIRTUAL_ENV

RUN --mount=type=cache,target=/app/.cache/uv \
    --mount=type=bind,source=uv.lock,target=uv.lock \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
    uv sync --no-install-project --no-editable

Diese Befehle installieren exakt die in der uv.lock Datei festgelegten Pakete.

Dev- und Test-Abhängigkeiten verwalten

Mit dependency-groups lassen sich verschiedene Umgebungen differenzieren:

[project]
dependencies = ["django~=5.2"]

[dependency-groups]

dev = [“django-debug-toolbar”] test = [“pytest”]

[tool.uv]

default-groups = []

Mit Build-Argumenten lassen sich Gruppen gezielt installieren:

ARG BUILD_GROUPS=""

RUN --mount=type=cache,target=/app/.cache/uv \
    --mount=type=bind,source=uv.lock,target=uv.lock \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
    uv venv $VIRTUAL_ENV && \
    uv sync --no-install-project --no-editable $BUILD_GROUPS

Beispielaufrufe:

# Nur Produktivabhängigkeiten
$ docker build .

# Mit Entwicklungswerkzeugen
$ docker build --build-arg BUILD_GROUPS="--group dev"

# Mit Testumgebung
$ docker build --build-arg BUILD_GROUPS="--group test"

Migration von `pip`

Bestehende Projekte lassen sich überführen mit:

uv add --requirements requirements.txt
uv add --group dev --requirements requirements-dev.txt
uv lock

Pflege und Updates

Veraltete Pakete prüfen:

uv pip list --outdated

Lock-Datei aktualisieren:

uv lock --upgrade

Damit bleibt die Abhängigkeitsverwaltung reproduzierbar, sicher und wartbar.

Diese Methode spart Zeit, Bandbreite und sorgt für eine klar strukturierte und abgesicherte Docker-Infrastruktur für Python-Projekte wie Django. Wer auf schnelle CI/CD-Pipelines, reproduzierbare Builds und saubere Produktionsimages setzt, findet in uv eine moderne und effiziente Lösung.

Hier das finale Dockerfile

### BUILD IMAGE ###

FROM python:3.13-slim AS builder

ENV DJANGO_SETTINGS_MODULE=myproj.settings \
    PATH="/venv/bin:$PATH" \
    PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    UV_CACHE_DIR=/root/.cache/uv \
    UV_COMPILE_BYTECODE=1 \
    UV_FROZEN=1 \
    UV_LINK_MODE=copy \
    UV_NO_MANAGED_PYTHON=1 \
    UV_PROJECT_ENVIRONMENT=/venv \
    UV_PYTHON_DOWNLOADS=never \
    UV_REQUIRE_HASHES=1 \
    UV_VERIFY_HASHES=1 \
    VIRTUAL_ENV=/venv

COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv

RUN <<EOT
apt-get update -y && \
apt-get install -y --no-install-recommends \
    build-essential \
    # other build dependencies here
EOT

WORKDIR /app

ARG BUILD_GROUPS=""

RUN --mount=type=cache,target=/app/.cache/uv \
    --mount=type=bind,source=uv.lock,target=uv.lock \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
    uv venv $VIRTUAL_ENV && \
    uv sync --no-install-project --no-editable $BUILD_GROUPS

# Copy what's needed to run collectstatic.
COPY myproj /app/myproj
COPY media /app/media
COPY manage.py /app/

RUN DEBUG=False ./manage.py collectstatic --noinput

### FINAL IMAGE ###

FROM python:3.13-slim

ARG PORT=8000
ENV DJANGO_SETTINGS_MODULE=myproj.settings \
    PATH="/venv/bin:$PATH" \
    PORT=${PORT} \
    PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    VIRTUAL_ENV=/venv

EXPOSE ${PORT}
ENTRYPOINT ["/bin/bash", "/app/bin/run"]
CMD ["prod"]

WORKDIR /app

RUN <<EOT
apt-get clean -y && \
apt-get update -y && \
apt-get install -y --no-install-recommends \
	# OS dependencies, e.g. bash, db clients, etc.
    bash && \
apt-get autoremove -y && \
apt-get clean -y && \
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
EOT

# Copy selectively from builder to optimize final image.
# --link enables better layer caching when base image changes
COPY --link --from=builder /venv /venv
COPY --link --from=builder /app/myproj /app/myproj
COPY --link --from=builder /app/static /app/static
COPY --link --from=builder /app/manage.py /app/manage.py

5Jun

Daily: How to Debug Streamlit Apps in VS-Code

by Ralph Allgemein

Create a launch.json file in .vscode

{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Streamlit",
            "type": "debugpy",
            "request": "launch",
            "module": "streamlit",
            "args": [
                "run",
                "${file}",
                "--server.port",
                "28100"
            ]
        }
    ]
}

27May

Daily: How to transcribe Videos

by Ralph Allgemein

Using Commandline and Python

Option 1: Transcribe with Whisper (official)

pip install git+https://github.com/openai/whisper.git

Then run:

whisper demo.mp4 --model medium --language auto --output_format txt

Optional flags:

--output_format srt (for subtitles)
--language en (to skip language detection)

Create a shell script to transcribe multiple files

#!/usr/bin/env bash

# Loop through all arguments (filenames)
for VIDEO in "$@"; do
    echo "Transcribing: $VIDEO"
    whisper "$VIDEO" --model medium --language en --output_format txt
done

Option 2: Transcribe with faster-whisper (much faster on CPU or GPU)

pip install faster-whisper

Run via Python:

import sys
from faster_whisper import WhisperModel

VIDEO=sys.arg[1]

model = WhisperModel("medium", device="cpu")  # or "cuda" for GPU
segments, info = model.transcribe(VIDEO)

with open("transcript.txt", "w") as f:
    for s in segments:
        f.write(f"{s.start:.2f} --> {s.end:.2f}: {s.text.strip()}\n")

Optional: Convert to audio (if needed)

If transcription fails or is slow, extract audio first:

ffmpeg -i your_video.mp4 -ar 16000 -ac 1 -c:a pcm_s16le audio.wav

Then transcribe audio.wav instead.

Problems with numpy

Error when running whisper: A module that was compiled using NumPy 1.x cannot be run in NumPy 2.2.6 as it may crash.

Reason:

The error you’re seeing comes from an incompatibility between NumPy 2.x and some Whisper dependencies that were compiled against NumPy 1.x.

Solution: Downgrade NumPy

You can fix this by downgrading NumPy to version 1.x:

pip install "numpy<2"

Then run Whisper again:

whisper demo.mp4 --model medium --language auto --output_format txt

Hide warning UserWarning: FP16 is not supported on CPU; using FP32 instead

Option 1: Suppress all Python warnings (quick + global)

In your terminal or script, set the environment variable:

PYTHONWARNINGS="ignore" whisper dmeo.mp4 --model medium<br></code>

Or, in Python code:

import warnings

warnings.filterwarnings("ignore")

Option 2: Suppress only that specific warning

If you’re using faster-whisper in Python and want to filter only that one:

import warnings

warnings.filterwarnings(
    "ignore",
    message="FP16 is not supported on CPU; using FP32 instead"
)

Option 3: Patch the library (if you’re comfortable)

You can find the line in the faster_whisper source code (usually in transcribe.py) that issues the warning and comment it out or remove it:

# warnings.warn("FP16 is not supported on CPU; using FP32 instead")

Not recommended unless you maintain the code.

17Apr

direnv – hide displaying variables

by Ralph Allgemein

Situation

Running direnv reload, you see something like this:

❯ direnv reload
direnv: loading ~/.envrc
direnv: export +ENV_HOME +ENV_NAME +UV_PROJECT_ENVIRONMENT +VIRTUAL_ENV +VIRTUAL_ENV_PROMPT +VSCODE_HOME ~PATH

Solution

Create the file $HOME/.config/direnv/direnv.toml

Use this content:
hide_env_diff = true

Script

#!/usr/bin/env bash

FILE_CONFIG=$HOME/.config/direnv/direnv.toml
FLDR_CONFIG=$(dirname $FILE_CONFIG)

echo "- Create folder $FLDR_CONFIG"
mkdir -p $FLDR_CONFIG

echo "- Create file   $FILE_CONFIG"
echo "  add hide_env_diff = true"
echo "hide_env_diff = true" >$FILE_CONFIG

26Nov

Prompt Engineering

by Ralph Allgemein

Read this

Leitfaden zum Prompt-Engineering

Prompting Techniques and Best Practices for Journalists

Prompting Fundamentals and How to Apply them Effectively

Beginner’s prompt handbook: ChatGPT for local news publishers

More technical

Llama 2 is here – get it on Hugging Face: How to prompt llama

18Oct

Vue – Cookbook

by Ralph Allgemein

Responsive Design

React on Size Change

<script>
export default {
    data() {
        return {
            isMobile: false,
            isDesktop: false,

            windowWidth: window.innerWidth,
            windowHeight: window.innerHeight,
        };
    },

    created() {
        this.updateWindowSize();
        window.addEventListener('resize', this.updateWindowSize);
    },

    methods: {
        updateWindowSize() {
            // console.log("updateWindowSize())");

            this.windowWidth = window.innerWidth;
            this.windowHeight = window.innerHeight;
            this.checkIsMobile();
        },

        checkIsMobile() {
            this.isMobile = this.windowWidth <= 768;
            // console.log(`checkIsMobile(): windowWidth = ${this.windowWidth} isMobile=${this.isMobile}`)
        },

        beforeUnmount() {
            console.log("beforeUnmount()");

            window.removeEventListener('resize', this.updateWindowSize);
        },

    },
};
</script>

Debugging

<script setup>
import {
    onActivated,
    onBeforeMount,
    onBeforeUnmount,
    onBeforeUpdate,
    /*  onCreated, */
    onDeactivated,
    onErrorCaptured,
    onMounted,
    /*  onRenderTracked,*/
    onRenderTriggered,
    onScopeDispose,
    onServerPrefetch,
    onUnmounted,
    onUpdated,
    /*  onWatcherCleanup, */

} from 'vue';

onActivated(() => { console.log('onActivated() called'); });
onBeforeMount(() => { console.log(`onBeforeMount():`) })
onBeforeUnmount(() => { console.log('onBeforeUnmount() called'); });
onBeforeUpdate(() => { console.log(`onBeforeUpdate():`) })
onDeactivated(() => { console.log('onDeactivated() called'); });
onErrorCaptured((err, instance, info) => { console.log('onErrorCaptured() called'); console.error(err); return false; });
onMounted(() => { console.log(`onMounted():`) })
onRenderTriggered((e) => { console.log('onRenderTriggered() called', e); });
onUnmounted(() => { console.log(`onUnmounted():`) })
onUpdated(() => { console.log('onUpdated() called'); });
onScopeDispose(() => { console.log('onScopeDispose() called'); });
onServerPrefetch(() => { console.log('onServerPrefetch() called'); });

</script>

7May

Learning | Hello World in different Languages

by Ralph Allgemein

Python

print("Hello, World!")

Java

public class HelloWorld {
    public static void main(String[] args) {
        System out println("Hello, World!");
    }
}

#include <stdio h>

int main() {
    printf("Hello, World!\n");
    return 0;
}

4 C++:

#include <iostream>

int main() {
    std::cout << "Hello, World!" << std::endl;
    return 0;
}

JavaScript

console log("Hello, World!");

Ruby

puts "Hello, World!"

Swift

print("Hello, World!")

package main

import "fmt"

func main() {
    fmt Println("Hello, World!")
}

Rust

fn main() {
    println!("Hello, World!");
}

PHP

<?php
echo "Hello, World!";
?>

Perl

print "Hello, World!\n";

Kotlin

fun main() {
    println("Hello, World!")
}

Scala

object HelloWorld {
  def main(args: Array[String]): Unit = {
    println("Hello, World!")
  }
}

Lua

print("Hello, World!")

Haskell

main :: IO ()
main = putStrLn "Hello, World!"

Dart

void main() {
  print('Hello, World!');
}

Shell

echo "Hello, World!"

Batch

@echo off
echo Hello, World!

PowerShell

Write-Output "Hello, World!"

VBScript

MsgBox "Hello, World!"

Objective-C

#import <Foundation/Foundation h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSLog(@"Hello, World!");
    }
    return 0;
}

Assembly

section  data
    hello db 'Hello, World!',10
    len equ $ - hello

section  text
    global _start

_start:
    ; write our string to stdout
    mov eax, 4         ; sys_write
    mov ebx, 1         ; file descriptor 1 (stdout)
    mov ecx, hello     ; message to write
    mov edx, len       ; message length
    int 0x80           ; syscall
    ; exit
    mov eax, 1         ; sys_exit
    xor ebx, ebx       ; exit status 0
    int 0x80           ; syscall

VBA (Visual Basic for Applications)

Sub HelloWorld()
    MsgBox "Hello, World!"
End Sub

Tcl

puts "Hello, World!"

COBOL

       IDENTIFICATION DIVISION 
       PROGRAM-ID  HELLO-WORLD 
       PROCEDURE DIVISION 
           DISPLAY "Hello, World!" 
           STOP RUN

26 F#:

printfn "Hello, World!"

Elixir

IO puts "Hello, World!"

SQL (MySQL)

SELECT 'Hello, World!';

SQL (SQLite)

SELECT 'Hello, World!';

SQL (PostgreSQL)

SELECT 'Hello, World!';

SQL (Oracle)

SELECT 'Hello, World!' FROM DUAL;

SQL (SQL Server)

PRINT 'Hello, World!';

Smalltalk

Transcript show: 'Hello, World!'; cr

cat("Hello, World!\n")

Bash

echo "Hello, World!"

Erlang

-module(hello) 
-export([hello_world/0]) 

hello_world() ->
    io:fwrite("Hello, World!~n")

Julia

println("Hello, World!")

MATLAB

disp('Hello, World!');

AutoHotkey

MsgBox, Hello, World!

Clojure

(println "Hello, World!")

Groovy

println "Hello, World!"

OCaml

print_endline "Hello, World!"

import std stdio;

void main()
{
    writeln("Hello, World!");
}

Crystal

puts "Hello, World!"

Nim

echo "Hello, World!"

Common Lisp

(format t "Hello, World!~



Scheme



(display "Hello, World!")
(newline)
Prolog
:- initialization(main) 

main :-
    write('Hello, World!'), nl,
    halt 
ABAP
REPORT ZHELLO_WORLD 

WRITE: / 'Hello, World!' 
VB NET
vb net
Module HelloWorld
    Sub Main()
        Console WriteLine("Hello, World!")
    End Sub
End Module

30Apr

AI Environment | Writing Apps for OpenAI, ChatGPT, Ollama and others

by Ralph Allgemein

Python UI Frameworks

Gradio
Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere!
Streamlit
Streamlit turns data scripts into shareable web apps in minutes.
All in pure Python. No front‑end experience required.
HyperDiv
Open-source framework for rapidly building reactive web apps in Python, with built-in Shoelace components, Markdown, charts, tables, and more.
Shoelace
A forward-thinking library of web components.

29Apr

Working with local LLMs

by Ralph Allgemein

List of Frameworks and Tools

Ollama

curl -fsSL https://ollama.com/install.sh | sh

 ollama run llama2

LLM

pip install llm
llm install llm-gpt4all
llm -m the-model-name "Your query"

llm aliases set falcon ggml-model-gpt4all-falcon-q4_0
llm                 -m ggml-model-gpt4all-falcon-q4_0 "Tell me a joke about computer programming"

Working with Hugging Face

List of Models

https://huggingface.co/models?sort=trending&search=gguf

Install models with Ollama

https://huggingface.co/docs/hub/ollama

The snippet would be in format:

ollama run hf.co/{username}/{repository}

Please note that you can use both hf.co and huggingface.co as the domain name.

Here are some models you can try:

ollama run hf.co/bartowski/Llama-3.2-1B-Instruct-GGUF
ollama run hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF
ollama run hf.co/arcee-ai/SuperNova-Medius-GGUF
ollama run hf.co/bartowski/Humanish-LLama3-8B-Instruct-GGUF

28Apr

Gatsby | Getting started with Gatsby

by Ralph Allgemein

Installation

npm init gatsby

pnpm create gatsby

❯ npm create gatsby
.../21.6.2/pnpm/store/v3/tmp/dlx-42253   |   +3 +
.../21.6.2/pnpm/store/v3/tmp/dlx-42253   | Progress: resolved 3, reused 1, downloaded 2, added 3, done
create-gatsby version 3.13.1

                                                                            Welcome to Gatsby!
What would you like to call your site?
✔ Getting-Started-with-Gatsby/ site
✔ Will you be using JavaScript or TypeScript?
· TypeScript
✔ Will you be using a CMS?
· No (or I'll add it later)
✔ Would you like to install a styling system?
· Tailwind CSS
✔ Would you like to install additional features with other plugins?
· Add responsive images
· Add an automatic sitemap
· Generate a manifest file
· Add Markdown and MDX support


Thanks! Here's what we'll now do:

    🛠  Create a new Gatsby site in the folder site
    🎨 Get you set up to use Tailwind CSS for styling your site
    🔌 Install gatsby-plugin-image, gatsby-plugin-sitemap, gatsby-plugin-manifest, gatsby-plugin-mdx

✔ Shall we do this? (Y/n) · Yes
✔ Created site from template
✔ Installed Gatsby
✔ Installed plugins
✔ Created site in site
🔌 Setting-up plugins...
info Adding gatsby-plugin-postcss
info Adding gatsby-plugin-image
info Adding gatsby-plugin-sitemap
info Adding gatsby-plugin-manifest
info Adding gatsby-plugin-mdx
info Adding gatsby-plugin-sharp
info Adding gatsby-transformer-sharp
info Adding gatsby-source-filesystem
info Adding gatsby-source-filesystem
info Installed gatsby-plugin-postcss in gatsby-config
success Adding gatsby-plugin-postcss to gatsby-config - 0.224s
info Installed gatsby-plugin-image in gatsby-config
success Adding gatsby-plugin-image to gatsby-config - 0.221s
info Installed gatsby-plugin-sitemap in gatsby-config
success Adding gatsby-plugin-sitemap to gatsby-config - 0.230s
info Installed gatsby-plugin-manifest in gatsby-config
success Adding gatsby-plugin-manifest to gatsby-config - 0.258s
info Installed gatsby-plugin-mdx in gatsby-config
success Adding gatsby-plugin-mdx to gatsby-config - 0.264s
info Installed gatsby-plugin-sharp in gatsby-config
success Adding gatsby-plugin-sharp to gatsby-config - 0.265s
info Installed gatsby-transformer-sharp in gatsby-config
success Adding gatsby-transformer-sharp to gatsby-config - 0.269s
info Installed gatsby-source-filesystem in gatsby-config
success Adding gatsby-source-filesystem (images) to gatsby-config - 0.279s
info Installed gatsby-source-filesystem in gatsby-config
success Adding gatsby-source-filesystem (pages) to gatsby-config - 0.286s
🎨 Adding necessary styling files...
🎉  Your new Gatsby site Getting Started with Gatsby has been successfully created
at /Users/Shared/CLOUD/Programmier-Workshops/Kurse/Gatsby/Einsteiger/Getting-Started-with-Gatsby/site.
Start by going to the directory with

  cd site

Start the local development server with

  npm run develop

See all commands at

  https://www.gatsbyjs.com/docs/reference/gatsby-cli/

❯ cd site
❯ npm install
❯ npm run develop

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uv im Dockerfile einbinden

Wichtige Umgebungsvariablen

Performance-Verbesserungen

Sicherheit und Reproduzierbarkeit

Abhängigkeiten installieren

Dev- und Test-Abhängigkeiten verwalten

Migration von pip

Pflege und Updates

Using Commandline and Python

Option 1: Transcribe with Whisper (official)

Create a shell script to transcribe multiple files

Option 2: Transcribe with faster-whisper (much faster on CPU or GPU)

Optional: Convert to audio (if needed)

Problems with numpy

Reason:

Solution: Downgrade NumPy

Hide warning UserWarning: FP16 is not supported on CPU; using FP32 instead

Option 1: Suppress all Python warnings (quick + global)

Option 2: Suppress only that specific warning

Option 3: Patch the library (if you’re comfortable)

Situation

Solution

Script

Read this

Responsive Design

React on Size Change

Debugging

Python UI Frameworks

Ollama

LLM

Working with Hugging Face

List of Models

Install models with Ollama

Installation

`uv` im Dockerfile einbinden

Migration von `pip`