ppg | Python pixel glitcher -- disturbs image data to create cool | Computer Vision library

This XPath,

It's rather unclear what your expected output is, but it looks like you want something like this

What you refer to as a "uneven lists" is a "tuple" or a "row". And a set of tuples/rows with the same shape is called a "relation" or a "table".

Where each element is each element is 'weight', 'grain_name', 'ppg', 'deg_litner', 'grain_bill'

In SQL Server you would create tables like

You can use jq

It was kind of hard to understand your problem. But there's some things for you to try in order to find and solve your problem.

1. The object away you return from your your_details_view is a list. Lists or QuerySets do not carry a pk field. Only direct django Models have one. So the right way should be traversing that list with a for loop and access the pk field inside the loop. As you did in testing.html.

2. Some of the QuerySets you construct inside your_details_view use the values_list function. If you are going to need the pk field in your template, you must also include it in your values_list call. For example, in the list away_team_list1 only the actual_over_under_result_field will be preserved, but not the pk field.

BTW... QuerySets are iterable, so you do not really need to explicitly cast it to list to traverse it on the template.

Use this for accomplishing the task -

I think Kotlin is preferred.

But since this issue alone shouldn't block you for so long, I think you should be able to use Executors.

See the Room Basic Sample by Google:

Specially the Database initialization

Here executors.diskIO() is used to interact with the DataBase on a background thread

The executors are defined here.

You just need to put filter first and then values_list. This should work.

I just want to start by saying that there are many ways to do this, and what's considered the "best" approach is highly dependent on the specifics to your use case (and sometimes personal preferences).

The most important thing to remember is that the watch has very limited resources (battery, memory, CPU) compared to a typical phone.

Here are a few things to keep in mind no matter what your exact solution will look like:

1. Writing to a file is an expensive operation. Doing this for every data point you receive from a sensor is not ideal. Consider saving your data to a database using Room instead. An easier alternative, as long as you are OK potentially losing some data if the app crashes or the device reboots unexpectedly, is to keep it in memory. This can be done using a basic array or some sort of Map (timestamp and value) depending on exactly what data you need. You can also use a hybrid of the two approaches and save data in batches.

2. Sending data between the watch and the phone is also expensive. I highly suggest storing things on the watch itself and transfer it to the phone only when needed. This can be a manual trigger, daily at a certain time, when the watch is charging, or some other clever strategy to minimize the impact on the watch's battery life.

3. You can send your data to the phone using the Wearable Data Layer API. You will have to set up either a MessageClient or a ChannelClient depending on how much data you need to transfer. If you stick to data structures that are supported by Android (as opposed to creating your own one), sending them over should be fairly straight forward.

4. If you need to process or format your data in order for it to be easily analyzed in MATLAB, consider doing this on the phone rather than the watch. Simpler operations on reasonably sized data sets can of course be performed directly on the watch.

Exactly how you decide to get the file to your computer is outside of the scope of what I'm trying to answer here. There are plenty of well-documented ways to do this. The easiest being to manually transfer it via adb. This can be done directly from the watch too, so you don't even have to send data to the phone.