sample-data | Samples of OCDS data , to show what OCDS data looks | JSON Processing library

I am just beginning with Blazor and I am attempting to make an external API call that's very similar to the starter WeatherForcast API call. However, the difference is the external API call does not have the JSON objects wrapped in an array. I am just wondering what I would need to change to get it to work. I did confirm if I wrap it in an array it works. I copied the api results into the sample weather.json with the same results.

As an example the template generated code has

In https://numpy.org/doc/stable/reference/generated/numpy.einsum.html

optimize{False, True, ‘greedy’, ‘optimal’}, optional Controls if intermediate optimization should occur. No optimization will occur if False and True will default to the ‘greedy’ algorithm. Also accepts an explicit contraction list from the np.einsum_path function. See np.einsum_path for more details. Defaults to False.

It seems to me the optimize flag is to choose the order in multiple contractions. E.g.,

We have a software package that performs tasks by assigning the batch of files a job number. Batches can have any number of files in them. The files are then stored in a directory structure similar to this:

I'm trying to run a procedure/function when a table gets updated (insert/delete/update), however, the function doesn't appear to get run when the trigger occurs or the trigger doesn't get triggered on an insert.

Function and Trigger:

I'm working on a dataframe consisting of 528 column and 2,643,246 rows. Eight of these are character-variables, and the rest integers. In total, this adds up to 11.35 GiB of data, with my available RAM being at 164 GiB.

I now wanted to run a pivot_longer on said dataframe, having one row for each column + two ID variables (year and institution). There are a total of 671,370 institutions over 76 years. So atm the data are structured such as this:

Where I would like to change it so the structure becomes:

To achieve this I attempted the following code:

I am trying to decorrelate this correlated query:

I have a piece of code that checks if there is an element that is displayed using p then it shows a dialog box but if it can't find it then it checks for another element and if that is displays another dialog box and if that element is not available, then it runs a piece of code.

The code is here.

I have multiple queries that I want to combine into a 9 table join (probably a bad idea?) to get 4 specific columns from the tables. But I'm unsure what is the best way to do this.

I want to get the total number of genres watched by each country name.

So the columns I want are:

name from the category table

country from the country table

and a newly created column num_rentals integer

https://www.postgresqltutorial.com/postgresql-sample-database/

I'm unsure how I would approach this. Should I join all the other tables into the rental table and perform a groupby/count to get the number of rentals for that country?

After looking through the tables I see that they all tie into each other with one attribute...such as country_id in city, city_id in address, address_id in customer, customer_id in rental