(develop an acceptable solution for a file containing many quadratic equation records)

This project is inspired by Gunnar Morling's work 1BRC:

• https://www.morling.dev/blog/one-billion-row-challenge
• https://github.com/gunnarmorling/1brc

as well as some problems that I had to solve in the line of my own work.
However, it is not a canonical 1BCR implementation.
I was more interested in finding an acceptable solution for:

1. solving quadratic equations;
2. solving cubical equations;
3. executing some OHLCV related calculations, like VWAP or moving averages;

Mind that at the moment it is merely a storage of scripts, not ready for a distribution project.
There is ManyRecordsExplanation.pdf, telling all about the data, scripts and performance results. The folder QE is for Quadratic Equations.
The folder CE ofr Cubical Equations.

Begin by installing the requirements:

python3 -m pip install -r requirements.txt

There are two QnD scripts that help quickly create necessary data files: make-many-qe-records.py and make-many-qe-same-records.py

> python3 make-many-qe-records.py
Create data file data_1000000_.csv populated with '1_000_000' x 3' random numbers from -1000.0 to 1000.0
Just update the code if you want different dimensions...

Creating CSV input data_1000000.csv, 3 x 1000000...
generating 1000000 records CSV files: 100%|██████████████████████████████████████████| 10/10 [00:13<00:00,  1.38s/file]
Created data_1000000.csv in 13.858
File           : data_1000000.csv
Size (bytes)   : 261671487
Created        : 2024-17-23 16:11
Permissions    : 666
:)

> python make-many-qe-same-records.py
Creating CSV file(s), 3 x 1000...
Created data_1000_same.csv in 0.001
File           : data_1000_same.csv
Size (bytes)   : 21342
Created        : 2024-17-23 16:21
Permissions    : 666
:)

There are several scripts that demonstrates usage of different instruments for solving quadratic equations (QE-):

1. mr-qe-use-csv.py - simple 'pythonic' code for solving quadratic equations, using CSV module for reading and writing;
2. mr-qe-pandas.py - using Pandas DataFrame for reading and storing data;
3. mr-qe-polars.py - using Polars DataFrame for reading and storing data;

All scripts open the file qe_data_<number_of_records>_same.csv and write into qe_results.csv file.