polo | Polo travels through your database and creates sample | SQL Database library

Answer based on @a_horse_with_no_name comment: splitStatements=false can be used to solve this issue.

Declaration for SQL changelog: --changeset name:id splitStatements:false

Additionally:

1. If you have several functions to declare you have to do it in separate changesets;
2. You may do it without replacing '$body$' with ' when using splitStatements=false.

Make sure you have enabled the PDP feature urn:ow2:authzforce:feature:pdp:core:xpath-eval as mentioned in the documentation on PDP properties.

Then you need to fix a few things in the PolicySet:

1. Specify the XPath version in a Policy(Set)Defaults / XPathVersion element. I strongly recommend XPath 2.0: http://www.w3.org/TR/2007/REC-xpath20-20070123
2. Specify the XML namespace for the prefix md in the XPath with xmlns:md="..."
3. [UPDATE 2022-03-14] Change the AttributeSelector Path to "/md:record/md:parentGuardian/md:parentGuardianId/text()" (add a slash at the very start) or more simply "//md:parentGuardianId/text()".

Here is what the fixed PolicySet looks like:

It's a collection. You can use these methods :

• groupBy method groups the collection's items by a given key
• map method iterates through the collection and passes each value to the given callback
• pluck method retrieves all of the values for a given key, and
• toJson method converts the collection into a JSON serialized string

Eventually after a bit of searching on internet I came across this page and this one line of code resolved everything!!

The problem you've encountered here is due to recycling (not the eco-friendly kind). When applying an operation to two vectors that requires them to be the same length, R often automatically recycles, or repeats, the shorter one, until it is long enough to match the longer one. Your unexpected results are due to the fact that R recycles the vector c("p", "o") to be length 4 (length of the larger vector) and essentially converts it to c("p", "o", "p", "o"). If we compare c("p", "o", "p", "o") and c("p", "o", "l", "o") we can see we get the unexpected results of above:

As far as I know, you could retrain your model using your new data examples, but instead of starting from a blank model, you would now start from your existing model.

In order to achieve this, it will first remove the following line from your train_spacy method, and may be receives the model as a parameter:

You have marked all the fields in your Album class as required just make them nullable so that is API returns something null then class can handle that as well. Make following changes to your class

The tab20c colorbar only has 20 colors which is smaller than your number of categories. One thing you could do though is to concatenate several colormaps together and use it for your plot. I used the approach from this and applied it to your situation. You can find the code below: