#git cli

[robomad]

Deploying Django Applications to Heroku

Learn how to deploy your Django applications to Heroku with this comprehensive guide. Follow step-by-step instructions to set up, configure, and deploy your app seamlessly.

Introduction Deploying Django applications to Heroku is a streamlined process thanks to Heroku’s powerful platform-as-a-service (PaaS) offerings. Heroku abstracts away much of the infrastructure management, allowing developers to focus on building and deploying their applications. This guide will walk you through the steps to deploy a Django application to Heroku, including setting up the…

[virtualizationhowto]

Docker Development Environment: Test your Containers with Docker Desktop

Docker Development Environment: Test your Containers with Docker Desktop #homelab #docker #DockerDesktopDevelopment #SelfHostedContainerTesting #DockerDevEnvironment #ConfigurableDevelopmentEnvironment #DockerContainerManagement #DockerDesktopGUI

One of the benefits of a Docker container is it allows you to have quick and easy test/dev environments on your local machine that are easy to set up. Let’s see how we can set up a Docker development environment with Docker Desktop. Table of contentsQuick overview of Docker Development EnvironmentSetting Up Your Docker Development Environment with Docker Desktop1. Install Docker Desktop2. Create…

[sexhaver]

okay at this point im beyond being annoyed at incurious idiots who refuse to google basic word definitions and make that everyone else's problem and have moved on to being concerned. not for these people directly, obviously, they can choke, but why are there more and more of them every day? is it something with microplastics? literally every single thing this person is complaining about being ungoogleable (git, cli, command line, foss) has its definition as the first google result for just. typing that word into the search bar. like you typed it into the comment box. i feel like im going insane

[technicjelle]

Infrastructure for Disaster Control, a.k.a. Automatic Builds

We all know the feeling of pure and utter stress when, ten minutes before the deadline, you finally click the Build And Export in your game engine and then it fails to build for some reason.

To prevent issues like this, people invented automated builds, also sometimes referred to as CI/CD.

This is a mechanism that tests the project every single time a change is made (a git commit is pushed, or a Perforce changelist is submitted). Because of this, we very quickly know whenever a change broke the build, which means we can fix it immediately, instead of having to fix it at the end.

It is also useful whenever a regression happens that doesn't break the build. We can go back to a previous build, and see if the issue is there or not. By checking a few builds by way of binary search, we can very quickly pinpoint the exact change that caused the regression. We have used this a few times, in fact. Once, the weaving machines stopped showing up in the build, and with this method, we were able to pinpoint the exact change that caused it, and then we submitted a fix!

It's very useful to have an archive of builds for every change we made to the project.

There are multiple different softwares that do this kind of thing, but Jenkins is by and far the most used. Both by indies, but also large AAA studios! So knowing how it works is very useful, so that's why I picked Jenkins for the job. Again, like with Perforce, it was pretty easy to install!

Here is a list of every build run that Jenkins did, including a neat little graph :)

Configuring it was quite tricky, though. I had to create a console terminal CLI command that makes Unreal Engine build project. Resources used: (one) (two)

It took many days of constant iteration, but in the end, I got it to work very well!

I also wrote some explanations of what Jenkins is and how to use it on the Jenkins pages themselves, for my teammates to read:

Dashboard (The Home Page):

Project Page:

Now, it is of course very useful to build the project and catch errors when they happen, but if no-one looks on the Jenkins page, then no-one will see the status! Even if the website is accessible to everyone, people won't really look there very often. Which kind of makes the whole thing useless… So to solve that issue, I implemented Discord pings! There is a Jenkins plugin that automatically sends messages to a specific Discord channel once the build is done. This lets everyone know when the build succeeded or failed.

We of course already had a discord server that we used to discuss everything in, and to hold out online meetings with. So this #build-status channel fit in perfectly, and it was super helpful in catching and solving issues.

Whenever a build failed, people could click on the link, and see the console output that Unreal Engine gave during the build, so we could instantly see where the issue was coming from. And because it rebuilds for every change that is made, we know for certain that the issue can only have come from the change that was just made! This meant that keeping every change small, made it easier to find and fix problems!

Whenever a build succeeds, it gets stored on the server, in the build archive.

But storing it on the server alone is nice and all, but people can't really do anything with them there. I could personally access them by remotely connecting to the server, but I cannot make my teammates go through all that. So I needed to make them more accessible for the whole team, to download whenever they please.

For this, I wanted to create a small website, from which they can download them. Just by going to the link, they could scroll through every build and download it immediately.

I already knew of multiple ways of easily doing this, so I tried out a few.

The Python programming language actually ships with a built-in webserver module that can be used very easily with a single command. But Python wasn't installed, and installing Python on Windows is kind of annoying, so I wanted something else. Something simpler.

I often use the program "darkhttpd" whenever I want a simple webserver, so I tried to download that, but I couldn't get it to work on Windows. Seems like it only really supports Linux…

So I went looking for other, single-executable, webserver programs that do support Windows.

And so I stumbled on "caddy". I'd actually heard of it before, but never used it, as I never had a need for it before then. For actual full websites, I've always used nginx. After some time of looking at the official documentation of caddy's various configuration file formats and command-line arguments, and tweaking things, I had it working like I wanted! It now even automatically starts when the computer boots up, which is something that Perforce and Jenkins set up automatically. Resources used: (one) (two) (three) (four)

And I think that's it! Unfortunately, none of this will roll over to the next team that has to work on this project, because none of this is code that is inside our project folder.

Here’s a summary of the setup, drawn as a network map:

Future

There is a concept called IAC, Infrastructure As Code, which I would like to look into, in the future. It seems very useful for these kinds of situations where other people have to be able to take over, and reproduce the setups.

[govindhtech]

What is Argo CD? And When Was Argo CD Established?

What Is Argo CD?

Argo CD is declarative Kubernetes GitOps continuous delivery.

In DevOps, ArgoCD is a Continuous Delivery (CD) technology that has become well-liked for delivering applications to Kubernetes. It is based on the GitOps deployment methodology.

When was Argo CD Established?

Argo CD was created at Intuit and made publicly available following Applatix’s 2018 acquisition by Intuit. The founding developers of Applatix, Hong Wang, Jesse Suen, and Alexander Matyushentsev, made the Argo project open-source in 2017.

Why Argo CD?

Declarative and version-controlled application definitions, configurations, and environments are ideal. Automated, auditable, and easily comprehensible application deployment and lifecycle management are essential.

Getting Started

Quick Start

kubectl create namespace argocd kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml

For some features, more user-friendly documentation is offered. Refer to the upgrade guide if you want to upgrade your Argo CD. Those interested in creating third-party connectors can access developer-oriented resources.

How it works

Argo CD defines the intended application state by employing Git repositories as the source of truth, in accordance with the GitOps pattern. There are various approaches to specify Kubernetes manifests:

Applications for Customization

Helm charts

JSONNET files

Simple YAML/JSON manifest directory

Any custom configuration management tool that is set up as a plugin

The deployment of the intended application states in the designated target settings is automated by Argo CD. Deployments of applications can monitor changes to branches, tags, or pinned to a particular manifest version at a Git commit.

Architecture

The implementation of Argo CD is a Kubernetes controller that continually observes active apps and contrasts their present, live state with the target state (as defined in the Git repository). Out Of Sync is the term used to describe a deployed application whose live state differs from the target state. In addition to reporting and visualizing the differences, Argo CD offers the ability to manually or automatically sync the current state back to the intended goal state. The designated target environments can automatically apply and reflect any changes made to the intended target state in the Git repository.

Components

API Server

The Web UI, CLI, and CI/CD systems use the API, which is exposed by the gRPC/REST server. Its duties include the following:

Status reporting and application management

Launching application functions (such as rollback, sync, and user-defined actions)

Cluster credential management and repository (k8s secrets)

RBAC enforcement

Authentication, and auth delegation to outside identity providers

Git webhook event listener/forwarder

Repository Server

An internal service called the repository server keeps a local cache of the Git repository containing the application manifests. When given the following inputs, it is in charge of creating and returning the Kubernetes manifests:

URL of the repository

Revision (tag, branch, commit)

Path of the application

Template-specific configurations: helm values.yaml, parameters

A Kubernetes controller known as the application controller keeps an eye on all active apps and contrasts their actual, live state with the intended target state as defined in the repository. When it identifies an Out Of Sync application state, it may take remedial action. It is in charge of calling any user-specified hooks for lifecycle events (Sync, PostSync, and PreSync).

Features

Applications are automatically deployed to designated target environments.

Multiple configuration management/templating tools (Kustomize, Helm, Jsonnet, and plain-YAML) are supported.

Capacity to oversee and implement across several clusters

Integration of SSO (OIDC, OAuth2, LDAP, SAML 2.0, Microsoft, LinkedIn, GitHub, GitLab)

RBAC and multi-tenancy authorization policies

Rollback/Roll-anywhere to any Git repository-committed application configuration

Analysis of the application resources’ health state

Automated visualization and detection of configuration drift

Applications can be synced manually or automatically to their desired state.

Web user interface that shows program activity in real time

CLI for CI integration and automation

Integration of webhooks (GitHub, BitBucket, GitLab)

Tokens of access for automation

Hooks for PreSync, Sync, and PostSync to facilitate intricate application rollouts (such as canary and blue/green upgrades)

Application event and API call audit trails

Prometheus measurements

To override helm parameters in Git, use parameter overrides.

Read more on Govindhtech.com

[guzsdaily]

Good Code is Boring

Daily Blogs 358 - Oct 28th, 12.024

Something I started to notice and think about, is how much most good code is kinda boring.

Clever Code

Go (or "Golang" for SEO friendliness) is my third or fourth programming language that I learned, and it is somewhat a new paradigm for me.

My first language was Java, famous for its Object-Oriented Programming (OOP) paradigms and features. I learned it for game development, which is somewhat okay with Java, and to be honest, I hardly remember how it was. However, I learned from others how much OOP can get out of control and be a nightmare with inheritance inside inheritance inside inheritance.

And then I learned JavaScript after some years... fucking god. But being honest, in the start JS was a blast, and I still think it is a good language... for the browser. If you start to go outside from the standard vanilla JavaScript, things start to be clever. In an engineering view, the ecosystem is really powerful, things such as JSX and all the frameworks that use it, the compilers for Vue and Svelte, and the whole bundling, and splitting, and transpiling of Rollup, ESBuild, Vite and using TypeScript, to compile a language to another, that will have a build process, all of this, for an interpreted language... it is a marvel of engineering, but it is just too much.

Finally, I learned Rust... which I kinda like it. I didn't really make a big project with it, just a small CLI for manipulating markdown, which was nice and when I found a good solution for converting Markdown AST to NPF it was a big hit of dopamine because it was really elegant. However, nowadays, I do feel like it is having the same problems of JavaScript. Macros are a good feature, but end up being the go-to solution when you simply can't make the code "look pretty"; or having to use a library to anything a little more complex; or having to deal with lifetimes. And if you want to do anything a little more complex "the Rust way", you will easily do head to head with a wall of skill-issues. I still love it and its complexity, and for things like compiler and transpilers it feels like a good shot.

Going Go

This year I started to learn Go (or "Golang" for SEO friendliness), and it has being kinda awesome.

Go is kinda like Python in its learning curve, and it is somewhat like C but without all the needing of handling memory and needing to create complex data structured from scratch. And I have never really loved it, but never really hated it, since it is mostly just boring and simple.

There are no macros or magic syntax. No pattern matching on types, since you can just use a switch statement. You don't have to worry a lot about packages, since the standard library will cover you up to 80% of features. If you need a package, you don't need to worry about a centralized registry to upload and the security vulnerability of a single failure point, all packages are just Git repositories that you import and that's it. And no file management, since it just uses the file system for packages and imports.

And it feels like Go pretty much made all the obvious decisions that make sense, and you mostly never question or care about them, because they don't annoy you. The syntax doesn't get into your way. And in the end you just end up comparing to other languages' features, saying to yourself "man... we could save some lines here" knowing damn well it's not worth it. It's boring.

You write code, make your feature be completed in some hours, and compile it with go build. And run the binary, and it's fast.

Going Simple

And writing Go kinda opened a new passion in programming for me.

Coming from JavaScript and Rust really made me be costumed with complexity, and going now to Go really is making me value simplicity and having the less moving parts are possible.

I am becoming more aware from installing dependencies, checking to see their dependencies, to be sure that I'm not putting 100 projects under my own. And when I need something more complex but specific, just copy-and-paste it and put the proper license and notice of it, no need to install a whole project. All other necessities I just write my own version, since most of the time it can be simpler, a learning opportunity, and a better solution for your specific problem. With Go I just need go build to build my project, and when I need JavaScript, I just fucking write it and that's it, no TypeScript (JSDoc covers 99% of the use cases for TS), just write JS for the browser, check if what you're using is supported by modern browsers, and serve them as-is.

Doing this is really opening some opportunities to learn how to implement solutions, instead of just using libraries or cumbersome language features to implement it, since I mostly read from source-code of said libraries and implement the concept myself. Not only this, but this is really making me appreciate more standards and tooling, both from languages and from ecosystem (such as web standards), since I can just follow them and have things work easily with the outside world.

The evolution

And I kinda already feel like this is making me a better developer overhaul. I knew that with an interesting experiment I made.

One of my first actual projects was, of course, a to-do app. I wrote it in Vue using Nuxt, and it was great not-gonna-lie, Nuxt and Vue are awesome frameworks and still one of my favorites, but damn well it was overkill for a to-do app. Looking back... more than 30k lines of code for this app is just too much.

And that's what I thought around the start of this year, which is why I made an experiment, creating a to-do app in just one HTML file, using AlpineJS and PicoCSS.

The file ended up having just 350 files.

Today's artists & creative things Music: Torna a casa - by Måneskin

© 2024 Gustavo "Guz" L. de Mello. Licensed under CC BY-SA 4.0

[mentalisttraceur-software]

This post was created and written in Emacs as Markdown (with Frontmatter YAML), and then I used my mostly-finished Python code to post it as NPF using the Tumblr API.

The Python packages I'm using are

`pytumblr2` for interacting with the API using Tumblr's "Neue Post Format",

`python-frontmatter` for reading the frontmatter (but not writing; I hate how it disruptively rearranges and reformats existing YAML),

`mistune` for the Markdown parsing, for now with just the strikethrough extension (`marko` seems like it would be a fine alternative if you prefer strict CommonMark compatibility or have other extension wants).

The workflow I now have looks something like this:

Create a new note in Emacs. I use the Denote package, for many reasons which I'll save for another post.

Denote automatically manages some fields in the frontmatter for the information it owns/manages.

Denote has pretty good code for managing tags (Denote calls them "keywords"). The tags go both in the file name and in the frontmatter. There's some smarts to auto-suggest tags based on tags you already use, etc.

The usual composable benefits apply. Denote uses completing-read to get tags from you when used interactively, so you can get nicer narrowing search UX with Vertico, Orderless, and so on.

So when I create a new "note" (post draft in this case) I get prompted for file name, then tags.

I have my own custom code to make tag adding/removing much nicer than the stock Denote experience (saves manual steps, etc).

Edit the post as any other text file in Emacs. I get all the quality-of-life improvements to text editing particular to my tastes.

If I stop and come back later, I can use any search on the file names or contents, or even search the contents of the note folder dired buffer, to find the post draft in a few seconds.

Every time I save this file, Syncthing spreads it to all my devices. If I want, I can trivially use Emac's feature of auto-saving and keeping a configurable number of old copies for these files.

I have a proper undo tree, if basic undo/redo isn't enough, and in the undo tree UI I can even toggle displaying the diff for each change.

My tools such as viewing unsaved changes with `git diff`, or my partial write and partial revert like `git add -p`, are now options I have within easy reach (and this composes with all enhancements to my Git config, such as using Git Delta or Difftastic).

After a successful new post creation, my Python code adds a "tumblr" field with post ID and blog name to the frontmatter YAML. If I tell it to publish a post that already has that information, it edits the existing post. I can also tell it to delete the post mentioned in that field, and if that succeeds it removes the field from the file too.

The giant leap of me being able to draft/edit/manage my posts outside of Tumblr is... more than halfway complete. The last step to an MVP is exposing the Python functions in a CLI and wrapping it with some Emacs keybinds/UX. Longer-term TODOs:

Links! MVP is to just add links to my Markdown-to-NPF code. Ideal is to use Denote links and have my code translate that to Tumblr links.

Would be nice to use the local "title" of the file as the Tumblr URL slug.

Pictures/videos! I basically never make posts with media, but sometimes I want to, and it would be nice to have this available.

[mentalisttraceur-incomplete]

There's this pattern I see in software which really bothers me.

People are far too willing or even eager to dismiss features/abstractions that empower doing something unless they have an example.

Most good functionality will have more uses than you could think of. You have to have a superpower before you can conceive of most ways it could be used.

Usually, at the moment that I recognize that something would be useful to implement, I can describe 0-2 examples for it, and those examples are almost always some niche thing which won't be compelling to most.

A few months ago, I implemented overwriting paste in my vi-like Emacs setup. I put the cursor on where I want the paste to start, I hit "gp", and it replaces the text starting from the cursor, until it runs out of characters to paste.

Vi-style editing in CLI/REPL prompts

My in-Emacs window management

Git cotree

I could probably never convince most people that this is useful to have. I could've never thought of, or remember, all the ways in which I use it. And yet I use it on average at least once a day.

[waywardgardenfury]

i (now) use arch btw

after a few months of not posting anything here, i finally managed to get arch working with awesomewm :)

initially when i tried a few months back, it was going fine until i could no longer hear audio for some reason lol. after searching for a solution i eventually gave up and retreated back to mint for the time being. after getting my infamous itch to just nuke everything and start again, i reinstalled arch and tried once again and i gotta say, its been going REALLY well.

the first time i ever attempted an install of arch (before archinstall was a thing) i somehow forgot to install a network manager and therefore couldnt really do much else. i really enjoyed setting it all up manually, but the fact that in the end i didnt really have it working was very annoying. the next time around, archinstall was there to back me up and its made everything so much easier!!! for me its broken down the barrier of entry significantly. i simply chose the desktop setup i wanted, and it chose the relevant packages. i went with a window manager rather than a full desktop environment this time around, more specifically awesomeWM. i wanted to go with something more bare-bones and configure it from the ground up so i could learn what sort of packages go into a full de. in addition people often talk about how much more efficient they find using wms, both productivity and resource wise. i see why! my entire operating system on boot uses like <500mb of ram, which is baffling that its possible. plus, the use of shortcuts of navigating around has been great.

i ended up going with awesome as nvidia has been absolutely the biggest issue with this whole process. for some reason my graphics card just HATES wayland which eliminates some options off the bat. ive had soo many issues in the past with it, so trying to use xorg is probably my best bet going forward and luckily its still a very popular choice, no shortage of resources for me. i did have a few issues setting it up on arch, as i wasnt really familiar with how to configure it at first but getting nvidia-settings it made it much easier for me for now.

pacman was an interesting change to get used to. discovering that it didnt have some packages that i have usually was interesting, but then shortly i discovered the aur and yay. it opened me up to a wide range of new packages that werent even on some of the package managers i had tried previously, like dnf and apt. in contrast to those, i found pacman and now yay much easier and incredibly fast to use. there just becomes more and more reasons to use arch every time i open it haha.

one of the things i havent got around to choosing is a file manager. having to navigate my files entirely by terminal has helped build the muscle memory of commands i didnt know before. plus may even be faster than i found previously? i may get around to setting up some aliases if i feel like i could shorten some tasks. using cli packages in terminal over graphical packages has helped me to learn git some more as well, which im sure will be useful for me in the years to come. in regards to the terminal too, im looking into switching to zsh instead of bash which i currently dont know what the difference is between shells or what they do exactly but ill find out.

i have only been using arch consistently for a few days at this point. and awesome is still pretty ugly, so the next task for me is to spice it up a bit with some theming. i dont have much, if any, experience with lua, which apparently is the language that awesome uses to write its dotfiles (also took me a minute to learn what dotfiles actually were). the last time i used lua was probably in roblox studio at like the age of 10 or something, so its been a while. i have a few articles and videos lined up that i need to watch for an introduction, so i already have an idea of where to start. with that said however, if anyone has any advice or tips send them my way!

now the obvious question for myself after this is what project am i actually going to do next? i want to actually develop software but i find it extremely intimidating. so there are a couple options for me going forward. one of the big ideas in my mind is developing a longer form game project in godot. i have developed smaller projects in the past to get used to the engine, but i want to try my hand at doing something over the course of multiple weeks. i have poor time management skills and tend to get sidetracked with other projects but i really want something i can chip away at every day for a few hours. and i think a game could be just that! plus, it gives me a creative outlet as well. i can make the music and art for that and combine a few hobbies into one.

arch & awesome has been definitely an interesting change to get used to, but it has been so fun! learning how to do everything myself has been what i have been craving and every day i regret abandoning windows less and less. i cannot sing the praises of linux and its community enough for scratching my brain in the right places! at some point i want to make a post detailing my full journey with linux, so keep an eye or two out for that.

if anyone wants to talk with me about any of this feel free to send me a message! dms are always open :)

[josephkdavis]

8 Game-Changing Developer Tools to Skyrocket Your Productivity.

Let’s be honest: Sometimes coding isn’t the hard part—it’s everything else. The context switching. The bugs you can’t reproduce. The terminal black hole you get sucked into at 2AM.

Over the past year, I tried dozens of tools. These 8? They legitimately changed the game for me.

Here’s the list I wish someone handed me earlier 👇

🧠 Raycast – It’s Like Mac Spotlight, but on Steroids You know that moment when you reach for Spotlight and it’s painfully slow?

Raycast fixes that. It's lightning fast, totally extendable, and lets me do stuff like:

Run scripts

Search docs

Control GitHub PRs

Even trigger workflows

All with a couple keystrokes.

Productivity level: 🔥 Programmer with a keyboard superpower

🤖 Tabby (formerly Codeium) – AI Autocomplete, No Cloud Required This is your AI pair programmer, but local. It runs on your machine, respects your privacy, and still feels scary accurate.

You just code—and Tabby whispers the next line before you think it.

Hot take: AI autocomplete is now baseline. Tabby just does it smarter.

🖥️ Warp – The Terminal You Didn’t Know You Needed The first time I opened Warp, I was like: “Wait… why hasn’t the terminal looked like this all along?”

Input blocks

Modern UI

Real-time suggestions

Collaboration built-in

Feels like: VS Code had a baby with your terminal—and it grew up fast.

🧑‍🤝‍🧑 Zed – Pair Programming, but Actually Fun Zed is a super snappy code editor with real-time multiplayer built in. Think Google Docs, but for code—with speed that makes VS Code look sleepy.

Perfect for: Pair programming, mentoring, or just working with your future self.

🔍 LogRocket – Debug Like You’re Watching a Replay Have you ever tried to debug a user issue with just an error log?

LogRocket is like, “Here, watch the actual replay of what happened.”

See user sessions

Capture console logs

Rewind the moment everything broke

Result: 10x fewer “Can you send a screenshot?” messages.

⚡ Fig – Terminal Autocomplete That Feels Like Magic Fig turns your CLI into a cheat code machine.

Flags? Autocompleted.

Scripts? Suggested.

Git commands? Faster than your memory.

Vibe: It’s like your terminal suddenly got a brain (and a heart).

🧯 Sentry – Know When Things Break Before Twitter Does Sentry tells you when your app throws an error—in real time.

It works across languages, frameworks, and stacks. You get:

Stack traces

Performance metrics

Release tracking

Translation: Fewer angry DMs from product managers.

🔒 Tailscale – Private Networking Without the VPN Pain Need to connect your laptop, server, and Raspberry Pi like they’re in the same room?

Tailscale makes that happen with zero setup hell.

No port forwarding. No crying into your terminal.

Just install → login → done.

🎉 TL;DR: Stop Fighting Your Tools Being a dev today means juggling:

Meetings

Bugs

Context switches

200 Chrome tabs

These tools helped me claw back hours every week—and made coding feel fun again.

[liquidwebdevelopers]

Custom Shopify Theme Development: Building E-Commerce That Matches Your Brand

In today's fast-paced online world, getting out isn't an option; it's essential. It's important to consider that your Shopify store's design isn't only about aesthetics, but also about attracting the attention of customers, building trust, and generating conversions. This is where custom Shopify theme development can be a significant game changer.

Instead of using generic templates that are pre-made, custom theme development provides your store a design that is a reflection of your brand. Pixel by pixel after click.

What is Custom Shopify Theme Development?

The customization process for Shopify theme development is the process of creating and programming a custom-made design for the Shopify store. Instead of using pre-designed themes that are available from Shopify's Theme Store Shopify Theme Store, a custom theme is created from scratch or extensively customized to meet your company's particular needs. Control as well as creativity and conversion.

Control creative thinking, control, and conversion.

Why Go Custom? (Top Benefits)

1. Total Branding Control

With a custom theme, every part of your store—colors, layout, buttons, typography—is designed to reflect your brand identity, not someone else’s.

2. Optimized for Conversions

Standard themes are built for everyone. Custom themes are built for your customers, optimized to guide them smoothly from product discovery to checkout.

3. Blazing Fast Performance

A custom-built theme contains only the code you need, which speeds up loading times, enhances user experience, and boosts SEO rankings.

4. Mobile-First and UX-Centered

Modern custom themes are crafted with a mobile-first approach, ensuring seamless navigation, fast interaction, and high conversions on smartphones and tablets.

5. Flexibility for Scaling

Need to integrate advanced features, unique product pages, or third-party APIs? A custom theme makes that possible without performance bottlenecks.

Key Components of a Custom Shopify Theme

1. Homepage Layout

A fully customized homepage designed to hook visitors, introduce your brand, highlight bestsellers, and drive them deeper into the store.

2. Custom Product Pages

Built with tailored layouts to emphasize features, benefits, social proof (like reviews), and dynamic upselling sections.

3. Collection Filters & Sorting

Smart, user-friendly filtering systems that help customers find what they need in seconds.

4. Optimized Cart & Checkout Flow

A streamlined path from browsing to purchase, minimizing abandoned carts.

5. Advanced Navigation Menus

Mega menus, sticky headers, or mobile accordion menus—built your way to ensure ease of use.

The Custom Theme Development Process (Step-by-Step)

Step 1: Discovery & Strategy

Understand your brand, target audience, and store goals. This phase includes competitor analysis and planning site architecture.

Step 2: Wireframes & Design Mockups

UX/UI designers create mockups of key pages using tools like Figma or Adobe XD.

Step 3: Theme Coding & Development

Developers write clean, responsive Liquid code (Shopify’s templating language), combined with HTML, CSS, JavaScript, and JSON.

Step 4: App & Feature Integration

Add custom functionalities such as wishlists, subscription options, multilingual support, or personalized recommendations.

Step 5: Testing & QA

Extensive testing across devices and browsers for bugs, loading speed, and user experience.

Step 6: Launch & Optimization

Once approved, the theme is published. Post-launch optimization includes SEO tuning, analytics setup, and A/B testing.

Tools & Technologies Used

Shopify Liquid—Shopify’s templating language

HTML5/CSS3—for structure and styling

JavaScript/jQuery—for dynamic elements

JSON—for theme settings

Git—for version control

Figma/Sketch/Adobe—For UI/UX design

Shopify CLI—For local theme development and deployment

Custom vs. Pre-Built Theme: What's Better?

Feature Pre-Built Theme Custom Theme: Low upfront cost Higher, one-time investment Branding Limited customization 100% brand-aligned Performance May include excess code Clean, lightweight code Scalability Less flexible Easily scalable and extendable Support & Maintenance Generic support Tailored to your setup

If your business is growing and you want to leave a lasting impression, custom is the way to go.

Who Should Invest in Custom Shopify Theme Development?

Established brands needing a strong digital presence.

Niche businesses with complex product requirements.

Startups aiming to disrupt with a bold brand identity.

Agencies and designers building Shopify solutions for clients.

SEO & Performance Optimization in Custom Themes

A professionally developed custom theme isn’t just beautiful—it’s also built to rank high and convert visitors.

Fast load speeds

Structured schema markup

Custom meta tags & SEO-friendly URLs

Optimized image formats

Mobile-first responsive layouts

Lightweight code for better Core Web Vitals

Final Thoughts: Is Custom Shopify Theme Development Worth It?

If you're committed to your e-commerce, buying the custom Shopify theme is among the best decisions you could make. It provides you with a distinct advantage in a competitive marketplace, builds brand equity over time, and gives users an experience that converts.

Rather than trying to fit into a cookie-cutter template, custom theme development lets your brand shine in its own unique light exactly the way it should.

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Openai لإسقاط نموذج مربك مع إطلاق GPT-5

ستبدأ Openai في التخلص التدريجي من نظامها الحالي لنماذج تسمية الأساس ، لتحل محل العلامة التجارية العددية "GPT" الحالية بهوية موحدة بموجب إصدار GPT-5 القادم.التحول ، الذي أعلن خلال حديث رديت ولكن مع أعضاء CORE Codex وأعضاء فريق البحث ، يعكس نية Openai تبسيط تفاعلات المنتج وتقليل الغموض بين إمكانيات النموذج وأسطح الاستخدام.يعمل Codex ، مساعد الترميز الذي يعمل به الذكاء الاصطناعي ، حاليًا عبر مسارين للنشر الأساسيين: واجهة ChatGpt و Codex CLI. نماذج بما في ذلك Codex-1 و تدعم Codex-Mini هذه العروض.وفقًا لـ Openai ، يهدف Jerry Tworek ، GPT-5 ، إلى توحيد مثل هذه الاختلافات ، مما يتيح الوصول إلى القدرات دون التبديل بين إصدارات النموذج أو الواجه��ت. صرح Tworek ،"GPT-5 هو نموذجنا الأساسي التالي الذي يهدف إلى جعل كل ما يمكن أن يقوم به نماذجنا حاليًا مع تبديل النماذج الأقل."أدوات Openai الجديدة للترميز والذاكرة وتشغيل النظاميتزامن هذا الإعلان مع تقارب أوسع عبر أدوات Openai ، والمدرسة ، والمشغل ، وأنظمة الذاكرة ، ووظائف البحث العميق في إطار عمل موحد. تم تصميم هذه الهندسة المعمارية للسماح للنماذج بإنشاء التعليمات البرمجية وتنفيذها والتحقق منها في صناديق الرمل السحابية عن بعد.أكد باحثو Openai المتعددين على أن تمايز النماذج من خلال اللواحق الرقمية لم يعد يعكس كيفية تفاعل المستخدمين مع القدرات ، خاصة مع عملاء ChatGPT ينفذون مهام الترميز متعددة الخطوات بشكل غير متزامن.يتم تعيين تقاعد اللواحق النموذجية على خلفية التركيز المتزايد على Openai على سلوك الوكيل على استنتاج النموذج الثابت. بدلاً من إصدارات العلامات التجارية مع معرفات مثل GPT-4 أو GPT-4O-MINI ، سيحدد النظام بشكل متزايد من خلال الوظيفة ، مثل Codex لوكلاء المطورين أو المشغل لتفاعلات النظام المحلية.وفقًا لـ Andrey Mishchenko ، فإن هذا الانتقال عملي أيضًا: تم تحسين Codex-1 لبيئة تنفيذ ChatGPT ، مما يجعله غير مناسب لاستخدام API الأوسع في شكله الحالي ، على الرغم من أن الشركة تعمل على توحيد وكلاء لتنفيذ واجهة برمجة التطبيقات.في حين تم إصدار GPT-4O علنًا مع متغيرات محدودة ، تشير المعايير الداخلية إلى أن الجيل القادم سيعطي الأولوية للاسترداد وطول العمر على التحسينات العددية الإضافية. أشار العديد من الباحثين إلى أن الأداء الحقيقي لـ CODEX قد اقترب بالفعل من التوقعات أو تجاوزه في المعايير مثل SWE-BENCY ، حتى مع بقاء التحديثات مثل CODEX-1-PRO.يهدف تقارب النموذج الأساسي إلى معالجة التفتت عبر واجهات يواجه المطور ، والتي ولدت تشويشًا حول الإصدار الأكثر ملاءمة في سياقات مختلفة.يأتي هذا التبسيط في الوقت الذي يوسع فيه Openai استراتيجية التكامل عبر بيئات التنمية. من المتوقع أن يكون الدعم المستقبلي لمقدمي خدمات GIT خارج Github Cloud والتوافق مع أنظمة إدارة المشاريع وأدوات الاتصال.أكد Hanson Wang عضو فريق CODEX أن النشر من خلال خطوط أنابيب CI والبنية التحتية المحلية ممكن بالفعل باستخدام CLI. تعمل وكلاء Codex الآن في حاويات معزولة مع عمر محدد ، مما يسمح بتنفيذ المهام الذي تصل إلى ساعة لكل وظيفة ، وفقًا لجوشوا ما.توسع نموذج Openaiتم تصنيف نماذج لغة Openai تاريخياً على أساس الحجم أو التطور الزمني ، مثل GPT-3 و GPT-3.5 و GPT-4 و GPT-4O. ومع ذلك ، فإن GPT-4.1 و GPT-4.5 هما ، في بعض النواحي ، قبل ، وبطرق أخرى ، خلف النموذج الأخير ، وهو GPT-4O.مع بدء النماذج الأساسية في تنفيذ المزيد من المهام مباشرة ، بما في ذلك قراءة مستودعات القراءة ، واختبارات التشغيل ، والتنسيق ، فإن أهمية الإصدار قد تقلصت لصالح الوصول القائم على القدرة. يعكس هذا التحول أنماط الاستخدام الداخلي ، حيث يعتمد المطورون على تفويض المهام أكثر من اختيار إصدار النموذج.Tworek ، الذي يستجيب لاستعلام حول ما إذا كان المخطط والمشغل سوف يندمج في النهاية للتعامل مع المهام بما في ذلك التحقق من صحة واجهة المستخدم الأمامية وإجراءات النظام ، أجاب ،"لدينا بالفعل سطح منتج يمكنه القيام بالأشياء على جهاز الكمبيوتر الخاص بك - يسمى المشغل ... في النهاية نريد أن تشعر تلك الأدوات بأنها شيء واحد."تم وصف Codex نفسه بأنه مشروع ولد من الإحباط الداخلي في نماذج Openai الخاصة في التنمية اليومية ، وهو شعور ردده العديد من أعضاء الفريق خلال الجلسة.يعكس قرار إصدار نموذج غروب الشمس أيضًا دفعة نحو النموذجية في مكدس نشر Openai. سيحتفظ مستخدمو الفريق والمؤسسات بالتحكم الصارم للبيانات ، مع استبعاد محتوى Codex من التدريب النموذجي. وفي الوقت نفسه ، يتم منح المستخدمين المحترفين و PLES مسارات واضحة للاشتراك. مع توسع وكلاء Codex إلى ما وراء واجهة مستخدم ChatGPT ، يعمل Openai على مستويات الاستخدام الجديدة ونموذج تسعير أكثر مرونة قد يسمح بخطط تستند إلى الاستهلاك خارج تكامل API.

لم يوفر Openai جدولًا زمنيًا نهائيًا عند حدوث GPT-5 أو الإهمال الكامل لأسماء النماذج الحالية ، على الرغم من أنه من المتوقع أن تصاحب التغييرات الداخلية للرسائل وتصميم الواجهة الإصدار. في الوقت الحالي ، يمكن للمستخدمين الذين يتفاعلون مع Codex من خلال ChatGPT أو CLI توقع تحسينات الأداء مع تطور إمكانيات النموذج تحت الهوية المبسطة لـ GPT-5.المذكورة في هذه المقالةنشر في: الذكاء الاصطناعى ، التكنولوجياأحدث ألفا تقرير السوق

[ritikay]

Streamlining Power Platform Development with Git Integration: A Guide to Modern ALM

As organizations increasingly adopt Microsoft Power Platform comprising Power Apps, Power Automate, Power BI, and Power Virtual Agents ensuring efficient collaboration, code quality, and deployment becomes critical. This is where Git integration offers immense value by introducing modern Application Lifecycle Management (ALM) practices into low-code environments.

Git, the world’s leading version control system, enhances Power Platform development by enabling change tracking, version history, branching, and team collaboration. Integrating Git with Power Platform helps developers manage app and workflow source files more effectively, streamline deployments, and minimize errors during updates or rollbacks.

The guide begins by outlining why Git integration is essential for Power Platform users. In environments where multiple stakeholders are working on frequent updates, Git helps maintain order by supporting collaboration, tracking changes, and enabling automated build and deployment pipelines through CI/CD.

Git integration works by exporting Power Platform solutions, unpacking them into readable source files using the Power Platform CLI, and managing them within Git repositories (like GitHub or Azure DevOps). Teams can track, merge, and review changes efficiently aligning low-code development with DevOps practices.

To get started, developers must:

Export a solution from Power Platform.

Unpack it using the Power Platform CLI.

Initialize a Git repository.

Commit and push changes to a remote repository.

The ALM Accelerator, a Microsoft-supported open-source tool, further simplifies Git integration by automating solution export/import, syncing changes, and triggering deployment pipelines based on Git actions. This significantly reduces manual effort and fosters consistent delivery practices.

The benefits of Git integration in Power Platform are clear:

Enhanced collaboration and traceability

Faster, automated deployments

Improved quality through version control and reviews

Easier error recovery via rollback features

However, the guide also acknowledges challenges such as managing binary formats, training teams in Git workflows, and handling solution dependencies.

In conclusion, integrating Git with Power Platform transforms how organizations manage low-code development by embedding agility, structure, and collaboration into the entire lifecycle from development to deployment.

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How to set up an EMR studio in AWS? Standards for EMR Studio

To ensure users can access and use the environment properly, Amazon EMR Studio setup involves many steps. Once you meet prerequisites, the process begins.

Setting up an EMR studio

Setup requirements for EMR Studio Before setting up, you need:

An AWS account

Establishing and running an EMR Studio.

A dedicated Amazon S3 bucket for EMR Studio notebook and workspace backups.

Five subnets and an Amazon VPC are recommended for Git repositories and connecting to Amazon EMR on EC2 or EKS clusters. EMR Studio works with EMR Serverless without VPC.

Setup steps Setup often involves these steps:

Choose an Authentication Mode: Choose IAM Identity Centre or IAM for your studio. User and permission management is affected by this decision. AWS IAM authenticates and IAM Identity Centre stores identities. Like IAM authentication or federation, IAM mode is compatible with many identity providers and straightforward to set up for identity management. IAM Identity Centre mode simplifies user and group assignment for Amazon EMR and AWS beginners. SAML 2.0 and Microsoft Active Directory integration simplifies multi-account federation.

Create the EMR Studio Service Role: An EMR Studio needs an IAM service role to create a secure network channel between Workspaces and clusters, store notebook files in Amazon S3, and access AWS Secrets Manager for Git repositories. This service role should describe all Amazon S3 notebook storage and AWS Secrets Manager Git repository access rights.

This role requires a trust policy from AWS to allow elasticmapreduce.amazonaws.com to play:AWS:SourceArn and SourceAccount settings for confused deputy prevention. After trust policy creation, you link an IAM permissions policy to the role. This policy must include permissions for Amazon EC2 tag-based access control and specific S3 read/write operations for your assigned S3 bucket. If your S3 bucket is encrypted, you need AWS KMS permissions. Some policy claims concerning tagging network interfaces and default security groups must remain unaltered for the service role to work.

Set EMR Studio user permissions: Set up user access policies to fine-tune Studio user access.

Create an EMR Studio user role to leverage IAM Identity Centre authentication. Sts:SetContext and AssumeRole allow elasticmapreduce.amazonaws.com to assume this role's trust relationship policy. You assign EMR Studio session policies to this user role before assigning users. Session policies provide Studio users fine-grained rights like creating new EMR clusters. The final permissions of a user depend on their session policy and EMR Studio user role. If a person belongs to multiple Studio groups, their permissions are a mix of group policies.

IAM authentication mode grants studio access via ABAC and IAM permissions policies. Allowing elasticmapreduce:CreateStudioPresignedUrl in a user's IAM permissions policy lets you use ARN or ABAC tags to limit the user to a Studio.

You specify one or more IAM permissions policies to describe user behaviours regardless of authentication mode. Workspace creation, cluster attachment and detachment, Git repository management, and cluster formation are basic, intermediate, and advanced rules with different authority. Clusters set data access control rights, not Studio user permissions.

(Optional) Create custom security groups to handle EMR Studio network traffic. If no custom security groups are selected, Studio uses defaults. When using custom security groups, specify a Workspace security group for outgoing access to clusters and Git repositories and an engine security group for inbound access.

Create an EMR Studio using the AWS CLI or Amazon EMR console. The interface creates an EMR Serverless application and offers simple configurations for interactive or batch workloads. ‘Custom’ gives full control over settings. Custom parameters include studio name, S3 location, workspace count, IAM or IAM Identity Centre authentication, VPC, subnets, and security groups. IAM authentication for federated users can include an IdP login URL and RelayState parameter name.

You must select EMR Studio Service and User Roles for IAM Identity Centre authentication. For speedier sign-on, enable trusted identity propagation. The AWS CLI tool create-studio requires programmatic creation options based on authentication method.

After building an EMR Studio, you may assign users and groups. Approach depends on authentication mode.

In IAM authentication mode, user assignment and permissions may require your identity provider. Limiting Studio access with ARN or ABAC tags and configuring the user's IAM rights policy to allow CreateStudioPresignedUrl does this.

The AWS CLI or Amazon EMR administration console can handle IAM Identity Centre authentication mode users. The console lets you assign users or groups from the Identity Centre directory. The AWS CLI command create-studio-session-mapping requires the Studio ID, identity name, identity type (USER or GROUP), and ARN of the session policy to associate. At assignment, you set a session policy. Altering the session policy lets you adjust user permissions later.