orca | Orchestration engine | BPM library

I'm only going to post a minimal example since you seem knowledgeable enough to tweak it to fit your needs! It should be fairly responsive, but I'll let you test it fully.

It uses Cards and Typography

For the collision detection functions like pygame.sprite.spritecollide the rect attribute of the pygame.sprtie.Sprite objects is used. Therefore you need to make sure that the position of the sprite is set in the rect attribute of the Enemy

self.rect = img[i].get_rect()

Is my snippet the solution to your question? I wasn't completely sure if I understood it.

If I did: Create a container for your impression and vector and make sure to set the container to position: relative;. Then give the impression a width of 100%. Give the vector a position: absolute; and calculate how to position it in the middle and how what the distance should be from the bottom of the container.

from the doc

When using layout='fill', the parent element must have position: relative

This is necessary for the proper rendering of the image element in that layout mode.

What can you do is :

CSS :

add relative to the landingImage class and remove margin auto

note that a package name is in url of Google Play, an id param...

https://play.google.com/store/apps/details?id=com.android.chrome&hl=en

you can probably list all package names from device in some "advanced" settings or just find an app for that in Play Store

This solves fine (), but is indeed a complex solve mainly due to:

• underspecification
• lack of modularization

This particular environment specification ends up installing well over 300 packages. And there isn't a single one of those that are constrained by the specification. That is a huge SAT problem to solve and Conda will struggle with this. Mamba will help solve faster, but providing additional constraints can vastly reduce the solution space.

At minimum, specify a Python version (major.minor), such as python=3.9. This is the single most effective constraint.

Beyond that, putting minimum requirements on central packages (those that are dependencies of others) can help, such as minimum NumPy.

I assume the name "devenv" means this is a development environment. So, I get that one wants all these tools immediately at hand. However, Conda environment activation is so simple, and most IDE tooling these days (Spyder, VSCode, Jupyter) encourages separation of infrastructure and the execution kernel. Being more thoughtful about how environments (emphasis on the plural) are organized and work together, can go a long way in having a sustainable and painless data science workflow.

The environment at hand has multiple red flags in my book:

• conda-build should be in base and only in base
• snakemake should be in a dedicated environment
• notebook (i.e., Jupyter) should be in a dedicated environment, co-installed with nb_conda_kernels; all kernel environments need are ipykernel

I'd probably also have the linting/formatting packages separated, but that's less an issue. The real killer though is snakemake - it's just a massive piece of infrastructure and I'd strongly encourage keeping that separated.

Been a while since I looked at this, I'll just point you to two previous answers.

Important!: You should always avoid post-processing the MSI if you can. You can create an MST (transform) to add this to the MSI during installation or set it as a property at the command line. See this old answer: Transforms and PUBLIC PROPERTIES: heavy-weight and light-weight customization of MSI installers and from section "Customizing Silent Install" onwards.

VBScript: There is a VBScript WiRunSQL.vbs - which is part of the Windows SDK - just search your SDK folder if you have Visual Studio installed.

You can use this and a batch file to post-process an MSI (sample here):

The accessible name computation is how accessibility labels are computed.

You're using aria-label too much, and the result may be difficult to listen to or outright confusing for human visitors using assistive technologies.

The first rule of ARIA is don't use ARIA unless you really have to.

• It is appropriate to use aria-label on the

  and elements. Keep that.

• I can't think of any good reason to use aria-label on a

  element. I'd recommend removing that.

  • Using aria-label on anchor elements is normally unnecessary and should be approached with caution. Unless you have a really good reason, you probably shouldn't be presenting different content to visitors using assistive technology.

  • I would also recommend removing aria-label from your images. This is exactly what alt text is for.

  If you really want to use aria-label on anchor elements, WCAG has some guidance:

  Per the Accessible Name and Description Computation and the HTML to Platform Accessibility APIs Implementation Guide, the aria-label text will override the text supplied within the link. As such the text supplied will be used instead of the link text by AT. Due to this it is recommended to start the text used in aria-label with the text used within the link. This will allow consistent communication between users.

  https://www.w3.org/WAI/WCAG21/Techniques/aria/ARIA8.html#description

  Don't give up on NVDA just yet. I also found the default speech settings too fast and difficult to understand. You just need to adjust the settings. The voice can also be changed out for better ones. It takes a bit of work to configure, but in my opinion NVDA is the best free screen reader available today. VoiceOver is also very nice if you have access to Mac/iOS products.

Yeah. I also fought with this initially when I learned patching and mocking and know how frustrating it is as you seem to be doing everything right, but it does not work. I sympathise with you!

This is actually how mocking of imported stuff works, and once you realise it, it actually makes sense.

The problem is that import works in the way that it makes the imported module available in the context of where your import is.

Lets' assume your code.py module is in 'my_package' folder. Your code is available then as my_package.code. And once you use from dag_common.connections import get_conn in code module - the imported get_conn becomes available as .... my_package.code.get_conn

And in this case you need to patch my_package.code.get_conn not the original package you imported get_conn from.

Once you realise this, patching becomes much easier.