Very small article today, just to introduce recraft.ai (thanks Pierre for the tip) which is an image generation tool assisted by AI.

Unlike other tools like Bing image creator (the one I used to illustrate my articles), recraft.ai can produce the same image but using some variations (using the fine-tune or the variate feature).

Using the editor, we can do some rotation, add text, resize the image, ...

And adding words like Realistic photo will generate images as if they were photos.

If you're a self-respecting programmer, you can't develop without code analysis tools. For PHP programmers, you already know a lot of them (rector, phpstan, phan, phpcs, ...). See my previous articles Rector 1.0.0, my friend, my coach and Docker image that provides static analysis tools for PHP f.i.

What about Python?

Be careful, it's a bomb. Docker has revolutionised the world; let's not be afraid to say it loud and clear, and most probably Dagger.io, created by the same people as Docker, will follow in its footsteps.

Dagger.io aims to be a tool that lets you execute steps of a workflow in exactly the same way as a CI/CD (Continuous Integration / Continuous Development) system like the ones of GitHub, GitLab, Jenkins, ... does.

But what is a CI? It's a step carried out by your server once you've pushed a new version of your project. During a CI, you can validate the syntax of your code, make sure it conforms (e.g. to formating rules), run code quality analysis tools such as checking that you don't have any undeclared or untyped variables or dead code (e.g. a function you no longer use).

During a CI, you can also launch your unit tests and run them each time you push out a new version of your project.

The aim of the CI is to ... crash as soon as something isn't in the expected state; e.g. you've forgotten a ;, you've got a violation (spaces used instead of tabs), a unit test no longer works, etc. So the aim of CI is to guarantee that your code is excellent.

Recently a good friend has notified me about a new tool from Microsoft: an utility for converting PDF and MS Office files (like .docx or .xlsx) to Markdown.

By looking at the repo on Github (https://github.com/microsoft/markitdown/), it seems really interesting since, they said, "it converts pdf, PowerPoint, word, excel, images, audio, html, text-based formats like csv, json or xml and even zip file (iterates over contents)". It's a lovely promise!

So, because it's always good to be able to quickly convert some docx files written by colleagues who don't speak Markdown, I was really interested to test it.

In very exceptional situations, you may need to be able to run Docker commands from a Docker container. Wait? What?

Imagine this situation: you're running a PHP container, everything is fine and you wish to run a code quality tool like, let's start easy, phplint (see this article for deeper info). You don't want to install phplint because you know a very cool Docker image who already contains it (think to jakzal/phpqa)

So, you're inside a container and you wish to run another container.

Another example: you're still inside a container and you wish to access to the list of running containers, already installed Docker images, volumes, ... (think to portainer)

Let's see in this article how to create your own Docker image, running as root or not, and configure it to allow Docker-in-Docker requests.

Pydot is a diagram as code generator i.e. you write lines of code and thanks to a magic process, you can render the code as an image.

For guys just like me who are terrible at visuals, this is gold.

Let's say you have to describe an IT process such as ETL (data is loaded, one or other transformation rule is applied and the result is loaded into a database, for example), you can easily imagine to draw some rectangles using a tool like https://app.diagrams.net/ (formerly known as draw.io) or use a smarter way to do it.

Let's see how in this article.

See also Markdown - Convert Excel ranges to Markdown tables.

Next to my XLS2MD script, you can also convert CSV file to Markdown very easily.

Just copy/paste your CSV content like the one below on the main text area appearing on Markdown - Convert CSV to Markdown tables and enjoy.

Column 1 Header,Column 2 Header
Row 1-1,Row 1-2
Row 2-1,Row 2-2

See also Markdown - Convert CSV to Markdown tables.

I'm a big fan of Markdown for my documentation, and from time to time I have to convert a range in Excel into a table to copy and paste into my documentation.

Years ago, I've found this repo https://github.com/jonmagic/copy-excel-paste-markdown and it's was the trigger for creating an online application in VueJS to make the magic happens.

In practical terms, I open my Excel file, select a range (a series of columns and rows) f.i. $A$1:$J:$50, press CTRL+C on the keyboard, switch to my Markdown - Convert Excel ranges to Markdown tables website, press CTRL+V and the table is converted.

You've two or more files and you wish to merge them. For instance, a list of employees and their salary for 2020 up to 2024. Or a list of cost centers and their budget/expenses. Or a list of students and their evaluation score. Or ...

Let's look at an example: a list of employees and their salaries.

We've many files, one by year, with this structure:

id;first_name;last_name;salary
0;Gina;Andrade;6040
1;Adam;Rowe;3866
2;Michael;Martinez;6913

And our need is to merge yearly files and generate a merged one with employees and their salary across years so, at the end, we wish to obtain this:

id;first_name;last_name;salary_2020;salary_2021;salary_2022;salary_2023;salary_2024
0;Gina;Andrade;6040;4413;7773;6208;7363
1;Adam;Rowe;3866;3678;2726;5425;7570
2;Michael;Martinez;6913;6493;5664;4902;4657

Using Pandas will make this piece of cake...

Nothing to install, nothing to configure, nothing to create first.

Here is how to use VSCode and Docker to create a ready-to-user Python environment, whatever if you're under Windows, Linux or Mac.

The only prerequisites are: we should have Docker installed on your system, you should have Visual Studio Code and you've installed the Docker for Visual Studio Code addon in VSCode.