[SnakeData] {create_template( ), run_script( ), cd( )}

    The functions in the article title are with relatively short syntax and that's why I decided to write a single article for all three of them instead of having one small article per function. So, let's begin!

    create_template(temp_name, var_list) - this function generates a csv file that contains desired list of variables to be extracted from csv data files in folder "data". temp_name argument should be replaced by the template file name (e.g. "all.csv") when calling the function. var_list needs to be replaced by a list of strings containing the names of all variables we need (e.g. ["q1","q2","q4"]). Syntax below:

A pinch of bash

    The word "bash" may sound funnny in some languages (and especially in Bulgarian it is quite often used in the meaning of "exactly") but in the computer world it stands for "Bourne again shell". This is in fact the scripting language that contains all commands used in a Linux shell. Each command can be written separately in the console or multiple/a lot of commands can be collected in
one file which can be executed when needed, this is providing huuuuuuge potential for automating wide variety of tasks. As mentioned in this article I use bash scripting to automate my work in Python and now I will provide a simple example of how it works. Below is the full script I use at my FormBuilder project:

How to convert .py to .exe

    Have you ever wondered how to convert your .py file with code into independent program that can run when Python isn't installed on the PC/laptop? Well, there are a couple of ways to do that and my modest advise is to try all of them and decide which one fits your way of work best. Right now I will share the way I transform .py into .exe.

[SnakeData]create_db()

    This functon was built to create new database node and has just one argument - the name of the database we aim to create /create_db(db_name)/. To call the function just type the desired db name in quotations in place of db_name argument:

I am using the setup of this usecase to illustrate functionallity of create_db( ). Full code can be seen on the printscreen below.

[SnakeData]Usecase - How to perform simple data validations

    Now we will step slightly aside of the straight-forward function and file overviews and we'll see an example of possible application of the SnakeData system. For that purpose I have prepared 3 csv data sets representing 3 separate waves of an imaginary study with intensional logic errors in one of the sets. Csv data files & data generator file /data generator file was made on Libreoffice's Calc but it should be compatible with Excel/ and case1 main system.

    In many online studies we have the below question:

How do I run Python?

    There are a couple of ways to run Python on your PC/laptop and there is no better or worse way to do so - just the one that is most convenient to you. Python itself comes with integrated IDE /Integrated Development Environment/ called IDLE and it is good enough for beginners to learn the basics of this programming language. There are also lots of other very well developed IDEs available online - Spyder /part of Anaconda platform/, Jupyter Notebook /very useful for data science and data science/, PyCharm, Visual Studio Code... And there is no single answer which one is best.

[SnakeData]The terminal

   Hey there, the first post related to SnakeData will be dedicated to the console.py file and some basix functionalities of the standalone terminal /console.exe/. The entire code is on the printscreen below: