Watson | Enumerate missing KBs and suggest exploits | DNS library

Those images are encoded as base64 strings so you don't need to download them, you can simply save them as follows:

You can get more detailed log by set the DEBUG=botium-* env variable. So in commandline it should look like this:

What you have done is appreciated, I've done some changes in your code

• $lookup to join collections. I have started form Flim collection
• $unwind to deconstruct the array
• $group to reconstruct the array that we already deconstructed, this will
• Since we have nested array we need to use $map to loop over them to collect the first name and lastname
• The above stage will end up with again nested array, so we use $reduce to loop again and remove inner arrays using $setUnion

remove some duplicate entries, depends on your requirements

Here is the code

It is importing the DecisionTreeClassifier, no problem there. But by default, sklearn prints only the parameters that were given to estimator with non-default values, from this function.

But if you want to see the "full" output, you can set the configuration of print_changed_only to False via sklearn._config.set_config like so:

The problem is like the python error message says. Python can't find the element with index 4 because the array only has 4 elements and array indices start with 0. So to access the last element in the array you would have to use

This is correct the 8 seconds limit is still in effect. It will most likely change in the future

Make sure to not substitue the old full path with just the base URI. See the API docs for IBM Watson Natural Language Understanding for the base URI and the path for the individual API function.

Thus, this URI:

You can use

Well sometimes we can say it is not possible, but often times it is just not the main goal of that package. Nonetheless, let's see if we can solve the problem.

I am taking the liberty of assuming that other packages besides pygame are allowed, but that the end result should be visible in pygame. In order to create the blooming / glowing effect I use the packages opencv-python (cv2) and numpy (np).

The first part of the solution will talk about creating a glowing border and some glowing text. The second part will talk about how this can be rendered upon a pygame surface.

TL;DR; Skip to the Summary part below and copy the code in their respective files.

In order to get some nice glowing borders and text, we can use the blurring functionality of opencv, which is also called smoothing. Since we want to create varying intensity of glowing, we first apply the GaussianBlur, to create some random blurriness around the image, and then extend that blurriness with the normal blur.