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The message is likely being redelivered by Azure Service Bus, due to the length of time required to consume the message.

On the receive endpoint, the MaxAutoRenewDuration is used to adjust the maximum time to renew the message lock, which is passed directly to the Azure client library. The default value is five minutes, which is the same as the default LockDuration. You can increase this time to the maximum expected time for the activity to complete.

Optionally, you can change the MaxDeliveryCount property to 1, so that Azure will only attempt to the deliver the message once, after which if the lock times out and is not renewed, it will move the message to the dead-letter queue for that receive endpoint.

UPDATE: If you're configuring this in an Activity Definition, you can do so as shown:

It looks like you have passed your list of tuples as parameters in the parameter grid of GridSearchCV. However, they would then be passed to XGBClassifier which does not support such a parameter.

You have to pass the list to the GridSearchCV as its cv parameter like so:

You might want to try and run nim c -d:release --genScript try1.nim. This will generate a compile_try1 script in the nimcache folder that should be able to compile the C sources generated by Nim.

looking over https://github.com/iancoleman/bip39 I found I had to specify the correct ravencoin network specifications (don't really understand what this object means) but once I did, it worked perfectly.

The for tick in p_ticker works like this: p_ticker is a list, and so can be iterated over. for tick does that - it takes the first thing and sets the value tick to it. Then in your next line, you have a brand new variable ticker that you are setting to p_ticker. But p_ticker is the whole list.

You want just the one value from it, which you already assigned to tick. So get rid of the ticker=p_ticker line, and in your scrape_string, use tick instead of ticker.

And then when it gets to the bottom of the loop, it comes back to the top, and sets tick to the next value in p_ticker and does it all again.

Also, your scrape_string line should be indented with everything else in the for-loop

Confusingly, there are two ways to do this, and they have almost identical names. The not recommended way to do this is the JCL command statement. The recommended way to do this is with the COMMAND statement.

Be advised that the command will be issued at conversion time, before the job runs.

Edit (1) to add...

The documentation for both IEFC452I and IEE122I indicate you have a JCL error somewhere. Wild guess: job has no steps?

You need to set the max-height: 100vh; to the .ModalSection2 class. Here is the working example :https://codesandbox.io/s/async-monad-xie2p?file=/src/Components/Modal.css:1653-1666

Weird. Here's what I'd try, in order:

1. Before you start training, use get_params/get_xgb_params() on your XGBRegressor model to make sure it actually used the random_state parameter you passed in. Ditto, look at the verbose log to make sure training used it.
2. Look at the target variable y. Is its distribution very weird, non-continuous? Please show us a plot or histogram? or at least some summary statistics (min, max, mean, median, sd, 1st and 3rd quartiles)? Is the un-stratified split affecting your training? (show the descriptive statistics before and after split, also on the eval set, these three sets shouldn't differ wildly). Is it easier to try to model log(y), sqrt(y), exp(y) or somesuch? Can you debug which rows are contributing to the CV error?
   • maybe eval_metric='rmse' and default objective reg:squarederror are very unsuitable to your target variable y. We should be able to tell from the plot of y, but try other [eval_metrics and objectives] (https://xgboost.readthedocs.io/en/latest/parameter.html#learning-task-parameters) like eval_metric=='logloss', 'mae', 'rmsle', etc. See that doc for full list of objective, eval_metric.
3. Also, for full determinism, set nthread parameter to 1 (single-core). The default is nthread==-1 (use all cores). Then rerun runs 1 and 2 and update the results in your question.
4. Fail all that, can you make a reproducible example (MCVE)? Either tell us where your dataset is publicly-available (source URL, not cloud link please), or make a reproducible example using any publicly-available dataset?

So as it turns out, in a completely different part of the code, a lambda was being called that looked like this: