shares | Just a little test Roo app

Issue found: Invalid Data safety section We reviewed your app's Data safety section in Play Console and found discrepancies between it and how the app collects and shares user data. All apps are required to complete an accurate Data safety section that discloses their data collection and sharing practices - this is a requirement even if your app does not collect any user data.

We detected user data transmitted off device that you have not disclosed in your app's Data safety section as user data collected.

Issue details

We found an issue in the following area(s):

SPLIT_BUNDLE 2: Policy Declaration for Play Safety Label: Device Or Other IDs Data Type - Device Or Other IDs (some common examples may include Advertising ID, Android ID, IMEI, BSSID)**

On the localhost module, lazy loading is working fine, showing meta tags and HTML content in in the view page source, but it is not showing on the live server. On the live server, I can only see meta tags and HTML contents of components that are direct children of AppModule but lazy loaded modules components are not showing meta tags and HTML. This weird behavior is only on the live server.

app.server.module.ts

I have a set of solutions, but I'm trying to parse them down to make them more different from one another by using a max overlap. Here's the solution set (and a view of the zero's and one's - they're binary variables indicating whether or not things A-F are chosen), and my pseudocode attempt to solve it (more details below the code):

(My first StackFlow question)

My goal is to improve the ETL process for identifying which NetApp file shares are related to which AD permission distribution groups. Currently an application named 'TreeSize' scans a number of volumes and outputs a number of large .CSV files (35mb+). I want to merge this data and remove all permission information where each group (or named user) doesn't start with a capital G or D ('^[GD]'). With over 700,000 rows to process, it's currently taking me over 24hr to run. I hope there is a better way to process this data more efficiently to drastically cut that time down.

Here is test data which resembles actual data once all files have been merged. Use rownum to adjust size of data. (Real data 700000+)

Test Data

I am trying to use ImageMagick 7 to detect if a specific channel in an image is largely pure black and pure white (plus a little antialiasing, and there's a chance the image could be pure black). This is to distinguish from another kind of image that shares a naming convention but has photographic-like image data in the r/g/b channels.

(Basically both image types are specular maps from different engines. The one I'm trying to differentiate here is more modern and has the metallic map in the blue channel; the other is much older and just has the specular colour in the RGB channels and the gloss map in the alpha.)

Currently I'm comparing the channel to a clone of itself that has had a 50% threshold applied, using the AE metric to see if it's largely the same apart from a small amount of antialiasing, and a fuzz of 1% to account for occasional aberration from pure black/white. This command works, but of course at the moment it only returns the number of distorted pixels:

How do you size the axes of a marginal plot to match the size of a non-square central plot using matplotlib?

In the image, you'll see that the top marginal plot is too wide, even though it shares the x-axis labels.

Context: I'm trying to create a joint plot like in Seaborn, but with a non-square heatmap at center and bar graphs as the marginal plots. JointGrids isn't designed to work with heatmaps (which is okay, on to matplotlib!). Merging a matplotlib heatmap with subplot barplots gets me close, but I find one bargraph's axis is larger than the central heatmap even when I share axes.

Minimum working example:

I'm getting data from using print command but in Pandas DataFrame throwing result as : Empty DataFrame,Columns: [],Index: [`]

I have a block that appears after scrolling 200px on the page

To start off with, I have checked all resources I could for examples but was not able to find one that brought me close enough so i can resolve this query (simple as it may seem). I've also seen there is a question that is the same but never resolved here: Get allDirectories() in Laravel and create a tree I'll also just use the same sample data cause it's the exact same scenario.

I basically get an output from laravel's AllDirectories() function which output's something like this: