calculus | A ruby parser for TeX equations | Parser library

I'm trying to understand how different chunking schemas can speed up or slow down my computation using xarray and dask.
I have read dask and xarray guides but I might have missed something to understand this.

I have 2 storage with the same content but chunked differently.
Both contains a data variable tasmax and the necessary coordinate variables and metadata for it to be opened with xarray. tasmax shape is

The first storage is a zarr store zarr_init which I made from netCDF files, 1 file per year, 10 .nc files. When opening it with xarray I get a chunking schema of chunksize=(366, 256, 512), thus 1 year per chunk, same as the initial netCDF storage. Each chunk is around 191MB.

The second storage, zarr_time_opti is also a zarr store but, there is no chunking on time dimension. When I open it with xarray and inspect tasmax, it's chunking schema is chunksize=(3660, 114, 115). Each chunk is around 191MB as well.

Naively, I would expect spatially independent computations to run much faster and to generate much fewer tasks on zarr_time_opti than on zarr_init. However, I observe the complete opposite:

When computing the same calculus based on groupby("time.month"), I get 2370 tasks with zarr_time_opti and only 570 tasks with zarr_init. As you can see with the MRE below, this has nothing to do with zarr itself as I'm able to reproduce the issue with only xarray and dask.

So my questions are:

• What is the mechanism with xarray or dask which create that many tasks ?
• Then, what would be the strategy to find the best chunking schema ?

I have two dataframes (df1, df2), df1 contains the list of topics and df2 contains the topics in df1 with its cluster or group.

Here is a sample input dataframe:

I am working on a project in Lambda-calculus and i am trying to code polymorphe couple with coqide but a have a problem coding the constructor that respect the type pprod

I have a Python code that is creating HTML Tables and then turning it into a PDF file. This is the output that I am currently getting

This image is taken from PDF File that is being generated as result (and it is zoomed out at 55%)

I want to make this look better. Something similar to this, if I may

This image has 13 columns, I don't want that. I want to keep 5 columns but my major concern is the size of the td in my HTML files. It is too small in width and that is why, the text is also very stacked up in each td. But if you look at the other image, text is much more visible and boxes are much more bigger width wise. Moreover, it doesn't suffer from height problems either (the height of the box is in such a way that it covers the whole of the PDF Page and all the tds don't look like stretched down)

I have tried to play around the height and width of my td in the HTML File, but unfortunately, nothing really seemed to work for me.

Edit: Using the code provided by onkar ruikar, I was able to achieve very good results. However, it created the same problem that I was facing previously. The question was asked here: Horizontally merge and divide cells in an HTML Table for Timetable based on the Data in Python File

I changed up the template.html file of mine and then ran the same code. But I got this result,

As you can see, that there were more than one lectures in the First Slot of Monday, and due to that, it overlapped both the courses. It is not reading the

The modified template.html file has this code,

Please note this question is an extension of this previously asked question: How to make Images/PDF of Timetable using Python

I am working on a program that generates randomized Timetable based on an algorithm. For the Final Output of that program, I require a Timetable to be stored in a PDF File.

There are multiple sections and each section must have its own timetable/schedule. Each Section can have multiple Courses whose lectures will be allocated on different slots from Monday to Friday by the algorithm. For my timetable,

• There are 5 days in total (Monday to Friday)
• Each day will have 5 slots (0 to 4 in indexes. With a "Lunch" Break between 3rd and 4th slot)

As an Example, I have created below a dictionary where key represents the Section and the items have a 2D Array of size 5x5. Each Index of that 2D array contains the course details for which the lecture will take place in that slot.

I'm currently writing a function for substitution (Lambda Calculus) based in Haskell.

I am trying to encode a small lambda calculus with algebraic datatypes in Scheme. I want it to use lazy evaluation, for which I tried to use the primitives delay and force. However, this has a large negative impact on the performance of evaluation: the execution time on a small test case goes up by a factor of 20x.

While I did not expect laziness to speed up this particular test case, I did not expect a huge slowdown either. My question is thus: What is causing this huge overhead with lazy evaluation, and how can I avoid this problem while still getting lazy evaluation? I would already be happy to get within 2x the execution time of the strict version, but faster is of course always better.

Below are the strict and lazy versions of the test case I used. The test deals with natural numbers in unary notation: it constructs a sequence of 2^24 sucs followed by a zero and then destructs the result again. The lazy version was constructed from the strict version by adding delay and force in appropriate places, and adding let-bindings to avoid forcing an argument more than once. (I also tried a version where zero and suc were strict but other functions were lazy, but this was even slower than the fully lazy version so I omitted it here.)

I compiled both programs using compile-file in Chez Scheme 9.5 and executed the resulting .so files with petite --program. Execution time (user only) for the strict version was 0.578s, while the lazy version takes 11,891s, which is almost exactly 20x slower.

I am experimenting a bit with julia, since I've heard that it is suitable for scientific calculus and its syntax is reminiscent of python. I tried to write and execute a program to count prime numbers below a certain n, but the performances are not the ones hoped. Here I post my code, with the disclaimer that I've literally started yesterday in julia programming and I am almost sure that something is wrong:

I'm trying to create a flow with coroutines but it's not giving to me the expected result. What I'd like to have is giving an expiration time (doesn't matter if it's in millis, seconds, etc..) when the time arrives to 0 it stops the countdown. What I have now is :