canon | Reusable React environment and components | Data Visualization library

I inherited an application with opencv, shiboken and pyside and my first task was to update to qt6, pyside6 and opencv 4.5.5. This has gone well so far, I can import the module and make class instances etc. However I have a crash when passing numpy arrays:

I am passing images in the form of numpy arrays through python to opencv and I am using pyopencv_to to convert from the array to cv::Mat. This worked in a previous version of opencv (4.5.3), but with 4.5.5 it seems to be broken.

When I try to pass an array through pyopencv_to, I get the exception opencv_ARRAY_API was nullptr. My predecessor solved this by directly calling PyInit_cv2(), which was apparently previously included via a header. But I cannot find any header in the git under the tag 4.5.3 that defines this function. Is this a file that is generated? I can see there is a pycompat.hpp, but that does not include the function either.

Is there a canonical way to initialize everything so that numpy arrays can be passed properly? Or a tutorial anyone can point me to? My searches have so far not produced any useful hints.

Thanks a lot in advance! :)

I need to calculate the square root of some numbers, for example √9 = 3 and √2 = 1.4142. How can I do it in Python?

The inputs will probably be all positive integers, and relatively small (say less than a billion), but just in case they're not, is there anything that might break?

Related

• Integer square root in python
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• Is there a short-hand for nth root of x in Python?
• Difference between **(1/2), math.sqrt and cmath.sqrt?
• Why is math.sqrt() incorrect for large numbers?
• Python sqrt limit for very large numbers?
• Which is faster in Python: x**.5 or math.sqrt(x)?
• Why does Python give the "wrong" answer for square root? (specific to Python 2)
• calculating n-th roots using Python 3's decimal module
• How can I take the square root of -1 using python? (focused on NumPy)
• Arbitrary precision of square roots

_{Note: This is an attempt at a canonical question after a discussion on Meta about an existing question with the same title.}

The operation pandas.DataFrame.lookup is "Deprecated since version 1.2.0", and has since invalidated a lot of previous answers.

This post attempts to function as a canonical resource for looking up corresponding row col pairs in pandas versions 1.2.0 and newer.

Some previous answers to this type of question (now deprecated):

1. Vectorized lookup on a pandas dataframe
2. Python Pandas Match Vlookup columns based on header values
3. Using DataFrame.lookup to get rows where columns names are a subset of a string
4. Python: pandas: match row value to column name/ key's value

Some Current Answers to this Question:

1. Reference DataFrame value corresponding to column header
2. Pandas/Python: How to create new column based on values from other columns and apply extra condition to this new column

Given the following DataFrame:

I was looking for the canonical implementation of MergeSort on Haskell to port to HOVM, and I found this StackOverflow answer. When porting the algorithm, I realized something looked silly: the algorithm has a "halve" function that does nothing but split a list in two, using half of the length, before recursing and merging. So I thought: why not make a better use of this pass, and use a pivot, to make each half respectively smaller and bigger than that pivot? That would increase the odds that recursive merge calls are applied to already-sorted lists, which might speed up the algorithm!

I've done this change, resulting in the following code:

I need to create a logger facility that outputs from different places of code to the same or different files depending on what the user provides. It should recreate a file for logging if it is not opened. But it must append to an already opened file.

This naive way such as

I've had a bit of a look around Stackoverflow and the wider Internet and identified that the most common causes for this error are conflation of declaration (int var = 1;) and definition (int var;), and including .c files from .h files.

My small project I just split from one file into several is not doing any of these things. I'm very confused.

I made a copy of the project and deleted all the code in the copy (which was fun) until I reached here:

On the pandas tag, I often see users asking questions about melting dataframes in pandas. I am gonna attempt a cannonical Q&A (self-answer) with this topic.

I am gonna clarify:

1. What is melt?

2. How do I use melt?

3. When do I use melt?

I see some hotter questions about melt, like:

• pandas convert some columns into rows : This one actually could be good, but some more explanation would be better.

• Pandas Melt Function : Nice question answer is good, but it's a bit too vague, not much expanation.

• Melting a pandas dataframe : Also a nice answer! But it's only for that particular situation, which is pretty simple, only pd.melt(df)

• Pandas dataframe use columns as rows (melt) : Very neat! But the problem is that it's only for the specific question the OP asked, which is also required to use pivot_table as well.

So I am gonna attempt a canonical Q&A for this topic.

I will have all my answers on this dataset of random grades for random people with random ages (easier to explain for the answers :D):

I have the following:

The following question seems very basic in programming with data.table, so my apologies if it's a duplicate. I spent time researching but could not find an answer.

I want to create a "user-defined function" that wraps around a data.table wrangling procedure. In this procedure, a new column is created, and I want to let the user set the name of that new column.

Consider the following code that works as-is. I want to wrap it inside a function.