elemental | A flexible and beautiful UI framework for React.js | User Interface library

It looks like you stopped following the pattern that you applied in the beginning. As you'll see, prior to line 310, you have used

• You can indeed deliver your streams directly from a MediaPackage end-point. However we recommend to use the MediaPackage end-point as an origin for a CDN like CloudFront because a CDN would cache the segments and manifests and deliver them to the end-users from the edge caches.

• This prevents the end-users (video players, devices) from hitting the origin i.e. MediaPackage over and over again for the same segment.

• For instance if you have 10,000 users spread across the globe playing the same stream without a CDN shielding the MediaPackage, all your users will try to retrieve the content from the origin

• Some of them might experience a higher latency depending upon their geographical location

• Having a CDN like CloudFront ensures that the users get the video segments from an edge cache closer to their location thereby improving latency and quality of experience for the users

For more benefits and advantages of using Amazon CloudFront please see the link

MediaConvert requires you to set the SDK to use a specific API input [1,2]

The JavaScript SDK docs [3] call out how to define and create a job in MeidaConvert using the JS SDK. In order to accomplish input clipping you would need to add the InputClippings option to your Input JSON block. An example is below:

Since there is an assignment file=filename between t_string and CHARACTER(len=*) there should be no problem in the call to open.

No such assignment is present. You are only using the specifier name to specify which argument of the statement you are passing (similar to keyword/named arguments in Python, but not the same). open is in fact not a procedure, it is a statement, but it also has its "arguments" (specifiers) distinguished by their names.

Hence no derived assignment shall be invoked. You must convert to character yourself.

Using lapply you can create list of dataframes.

Resources within a resource group need not always be deployed in the same location as the resource group. But there is a built-in Azure Policy available to audit this condition that one may choose to enable.

The resource group location serves two purposes:

• First: The resource group stores metadata about the resources. When you specify a location for the resource group, you're specifying where that metadata is stored. Now, for compliance reasons, you may need to ensure that your data is stored within a particular region.
• Second: If the resource group's region is temporarily unavailable, you can't update resources in the resource group because the metadata is unavailable. The resources in other regions will still function as expected, but you can't update them.

For knowing more about the factors to consider while defining your resrouce groups, check the Azure Resource Manager documentation.

The problem is that your read_json(....).text line returns a series, not a dataframe.

Adding a .to_frame() and referencing the column in the following line should fix it:

In order to use an index for resistances you need to declare an interface with an index like this and define resistances using it:

Do I need an generic interface for sum calling st_add?

You do need to add a specific function to the sum generic interface. It does not matter that much what exactly that function calls internally. It must be a function that works for the state type arrays, that is important.