juicy | A fast JSON parser for Elixir with some extra features | Parser library

I guess databricks file loader doesn't seem to recognize the absolute path /tmp/. you can try the following work around.

1. Read the file using path using Pandas Dataframe
2. Pass the pandas dataframe to Spark using CreateDataFrame function

Code :

The Arc smart pointer gives you read-only access to its pointee. So you cannot modify something which is behind an Arc, at least not directly.

Given that you are using Arc which is a thread-safe reference counted pointer, I assume that this would be used across threads. In that case you should wrap your SlaveRepository in some synchronization primitive, such as Mutex or RWLock (note that in async context you should use the async versions of those primitives, instead of the ones from std):

I have not worked with VB for many years and it was .net, so, if this solution is incorrect, let me know.

You can create an array or a list containing all your toggle buttons, loop them and perform the operation you need for each of them. This will make sure that the logic above would be implemented exactly once rather than duplicated, yet, you still need to build your collections with the buttons.

You can create a subclass for your toggle buttons and make sure that every toggle button in question will be of that class. And then you can create a static List for the class. In the constructor of each toggle button you append that button to the shared list in the class. And then you can create a shared method that loops the list and performs the logic you need.

P.S. Sorry for not writing code, I no longer remember the syntax of the language.

In your code you only check if the strings are present in the respective lists, you don't check if the corresponding line numbers match. But even if you would check, your code is likely to produce an erroneous output because of how .index works. To quote from here:

list.index(x[, start[, end]])

Return zero-based index in the list of the first item whose value is equal to x. Raises a ValueError if there is no such item.

...

You only get the first index. So, if there's no line number match for the respective first finds, you'd be stuck.

If you're only interested in if there's a match then you could do something like this instead:

In your config file

So it turns out, this is due to us having to migrate our project over from our old Amplify project due to it ending up in an unrecoverable state. It didn't connect correctly to our cognito user pools and so all the needed information wasn't being provided in aws-exports.js

I'm not quite sure why it wasn't working with a new project and a new amplify project but it's working now.

I was missing the aws_user_pools_id and the aws_user_pools_web_client_id fields. Providing them manually resolved the issue.

This isn't linked to data.table.

sub relies on internal C code call:

markdown-it-vue's contents can be styled with CSS, so you can apply your own dark theme to the Markdown contents. Vuetify sets the .theme--dark class on the app root element, and the markdown-it-vue's element has the .markdown-body class.

On .theme--dark .markdown-body, apply a color with !important to override Vuetify's theme:

A better approach would be to use set intersection (assuming you're trying to count unique matches, i.e., you're not interested in how many times "apple" is mentioned in a review, only that it is mentioned, period).

This should get you what you want, again, assuming you want to count unique matches and assuming your lemmatized column values are indeed lists of strings: