This is a reminder for me or a task if anyone wants :P

Basically, The last two questions aren't really regex's questions.

To do:

• Move said questions to correct place.
• Add new regex questions (Python related!)?
• Maybe add a new ## Regex section, as it is a valuable skill

Right now, the validation error message is in the Example Usage box, which is what SSDT does

There's support for validation for input boxes, so it would be nicer for the error message to show up with the associated input box like this:
![image](https://user-images.githubusercontent

The https://github.com/nccgroup/ScoutSuite/blob/master/ScoutSuite/providers/gcp/rules/findings/iam-lack-of-service-account-key-rotation.json finding should only flag USER_MANAGED keys (https://cloud.google.com/iam/docs/reference/rest/v1/projects.serviceAccounts.keys), as SYSTEM_MANAGED keys are "managed and rotated by Google"

1. All the functions in ResourceRegistry should start with AzureRM, some are missing the RM part (which clarifies that we support the "Azure Resource Manager" terraform resources). These functions' files are also missing the "RM" in their RFunc: NewAzureMariaDBServer function names.
2. The ResourceRegistry and the FreeResources lists should be sorted alphabetically to make it easier for

Hello,

Do you plan to support Terraform scans with OpenStack in the future ?

Regards

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Hi, I read example command here https://docs.microsoft.com/en-us/cli/azure/container?view=azure-cli-latest#examples

and I found wrong command on "Create a container in a container group that runs Windows, with 2 cores and 3.5Gb of memory." Section.

Here your command
az container create -g MyResourceGroup --name myapp --image myimage:latest --ip-address public --ports 8081 --protocol UDP

Summary

The Event Hubs client library is instrumented using the .NET EventSource mechanism for logging. When instrumenting or diagnosing issues with applications that consume the library, it is often helpful to have access to the Event Hubs logs.

Though EventSource instrumentation is

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?