wild | wonderful immersive language directory | Augmented Reality library

I have a for loop doing something I would have thought relatively straight forward on Python 3

I have no trouble with Get-ChildItem using * as a wildcard, but I wonder if it can be made to work with more refined wild cards. Given a file like C:\Folder\journal.0001.txt I would want to use the wildcard C:\Folder\journal.####.txt to get all "regular" journal files, but skip the ones named with this format journal.0000.worker1.log. Using the wildcard in the path throws an error that the path doesn't exist, and replacing the file bit with a simple * and the using journal.####.txt as a filter or include doesn't work. I do see that journal.????.txt works, but that would potentially grab journal.ABCD.txt should it exist. And I haven't even started playing with character sets.

My script is:

I have a file with two fields separated with :, both fields are varying length, second field can have all sort of characters(user input). I want the first field to be right padded with spaces to fixed length of 15 characters, for first field I have a working regex @.[A-Z0-9]{4,12}.

sample:

So I was writing a script that used random.randint() in python, but it doesn't really matter since I think most mainstream languages have this "problem". It's like this: I set i to a random number and then add a random number 1 million times and then divide it by two. The outputs vary wildly, sometimes it's close to 0, sometimes close to 1, but by logic the output should pretty much be 0.5. What is causing this change.

Data frame dat includes a set of numeric ids in a vector called code_num. Some of these ids end with one or more zeros. Others do not. Here are the first three lines:

I am using a Python POST request to geocode the addresses of my company's branches, but I'm getting wildly inaccurate results.

I looked at this answer, but the problem is that some results aren't being processed. My problem is different in that all of my results are inaccurate, even ones with Confidence="High". And I do have an enterprise account.

Here's the documentation that shows how to create a geocode Job and upload data:
https://docs.microsoft.com/en-us/bingmaps/spatial-data-services/geocode-dataflow-api/create-a-geocode-job-and-upload-data

here's a basic version of my code to upload:

I am currently using statsmodels (although I would also be happy to use Scikit) to create a linear regression. On this particular model I am finding that when adding more than one factor to the model, the OLS algorithm spits out wild coefficients. These coefficients are both extremely high and low, which seems to optimise the algorithm by averaging out. It results in all of the factors being statistically insignificant. I am just wondering if there is a way that I can put an upper or lower limit on the coefficients such that the OLS has to optimize within these new boundaries?

I have array of Objects which is look like this