##### Problem Statement
Given a 2D grid of characters where 'S' represents the start position, 'T' represents the target, 'O' represents open spaces, and 'X' represents walls, find the shortest path from 'S' to 'T'. You can move up, down, left, or right.

##### Example
```plaintext
Input: grid = [
  ['S', 'O', 'X', 'O'],
  ['O', 'O', 'X', 'O'],
  ['X', 'O', 'O', 'T'],
  ['O', 'X', 'X', 'O']
]
Output: 5
Explanation: The shortest path is 5 steps.
```

##### Constraints
- The grid will have at most 1000 rows and columns.


#### Expected Challenge Output
When the function `findShortestPath` is called with the given example input, the expected output is:
- For the input grid, the output is `5`.

JavaScript

JavaScript is a high-level, dynamic, and interpreted programming language that is widely used for web development and beyond. It was created in the mid-1990s and has since become one of the most popular and widely used programming languages in the world. JavaScript allows developers to create interactive and dynamic websites, as well as build complex web applications and server-side programs. It is a versatile language that can run on any modern web browser, as well as server environments like Node.js, making it an essential tool for any full-stack web developer.

learn-javascript

Python

Python is a high-level, interpreted, general-purpose programming language. It was created in the late 1980s by Guido van Rossum and has since become one of the most popular programming languages in the world. Python is known for its simple and easy-to-read syntax, making it a great language for beginners to learn, and for experienced developers to write complex applications.

Python is used in a variety of applications, including web development, scientific computing, data analysis, artificial intelligence, and more. It has a large and active community of users and developers who have created many libraries and frameworks that make it easier to build complex applications quickly. Python is also known for its strong support for object-oriented programming and its dynamic typing, which makes it flexible and easy to use.

Overall, Python is a versatile and powerful language that can be used for a wide range of applications, making it a great choice for developers looking to build anything from simple scripts to complex applications.

learn-python

C++ Programming

C++ is a high-level, general-purpose programming language that was created as an extension of the C programming language. It is widely used for developing systems software, game development, and desktop and mobile applications. C++ is known for its performance, efficiency, and versatility, making it a popular choice for developing resource-intensive applications. It is also used in the development of other programming languages, as well as in various scientific and engineering applications. C++ is considered a mid-level language, as it contains both high-level and low-level programming concepts, and provides control over system resources through its use of pointers and manual memory management.

learn-cpp-programming

C Programming

This C fundamentals learning module is designed to teach individuals the basics of programming using the C programming language. The module typically covers the fundamentals of C programming, including topics such as data types, variables, control structures, functions, pointers, and memory management. The module may also cover more advanced topics, such as file handling, dynamic memory allocation, and multithreading.

learn-c-programming

Find Target in a Maze

find-target-in-a-maze

Tools & Setup

In this tutorial chapter, we'll go through the necessary steps to install and set up C programming tools on your computer. We will also delve into understanding the use of these tools to lay a solid foundation for your C programming journey. The key tools we will be focusing on are: a text editor to write your code, a compiler to translate your code into machine language, and a debugger to help find and fix mistakes in your code. 

**Text Editors**

A text editor is a tool that allows you to write and edit your code. There are many text editors available that can help you write C code easily. Some of them are:

* Sublime Text 
* Visual Studio Code
* Atom

Here is how you can install Visual Studio Code:

- Go to the Visual Studio official website.
- Download the setup file depending on your OS (ie. macOS, Windows, or Ubuntu).
- Execute the file and follow the on-screen instructions to complete the installation.
- After installation, open the editor and navigate to the ‘Extensions’ option on the left toolbar. Search for the 'C/C++' extension and click install.

Yet, it's important to note that you should choose a text editor based on your comfort and requirement.

**Compilers**

A C compiler is a program that converts the C code written in human-readable format to a machine-readable format. GCC (GNU Compiler Collection) is one such compiler which supports C, C++, and other languages. Let's see how to install GCC:

For Ubuntu: Open Terminal and type:

```
sudo apt-get update
sudo apt-get install build-essential
```

For Windows: You can install GCC on Windows by downloading MinGW. 

- Go to MinGW's official website.
- Download the MinGW Installation Manager.
- Once downloaded, run the installer.
- Select 'mingw32-base' and 'mingw32-gcc-g++' compilers in the list.
- Apply changes to start the installation.

For macOS: Xcode command line tools include a GCC compiler.

- Open Terminal
- Type xcode-select --install 

**Debugging Tools**

A debugger is a tool used to test and debug a program. With a debugger, you can also monitor the execution of your program line by line, so you can understand how your program operates.

GDB (GNU Debugger) is one of the most popular debugging tools in programming:

For Ubuntu:

```
sudo apt-get install gdb
```

For macOS:

```
brew install gdb
```

For Windows, you could use the debugger included in the Visual Studio.

From here out, you are equipped with the basic tools to carve your path in the vast world of C Programming. In the next chapters, we will delve deeper into understanding how to use these tools to create, analyse and improve your code.

Standard Template Library (STL)

The Standard Template Library (STL) is a powerful set of C++ template classes to provide general-purpose classes and functions with templates that implement many popular and commonly used algorithms and data structures like vectors, lists, queues, and stacks.

In every typical blockbuster movie, there are characters, actions, and twists that keep the film engaging. Similarly, the C++ STL encapsulates a wealth of features under its umbrella, such as containers, algorithms, and iterators. 

Starting with containers, these are used to manage collections of polymorphic objects. Some common containers include vector, list, deque, set, multiset, map, and multimap. The names may seem randomly crafted, just like movie character names, but those names are actually representative of their functionalities. 

Let's illustrate this with an example. Suppose we have a movie and we want to record the names of all characters in it. To serve this purpose, we can use an STL container, specifically, the vector container.

```cpp
#include<iostream>
#include<vector>
#include<string>
using namespace std;

int main()
{
    vector<string> movieCharacters;
    movieCharacters.push_back("Harry");
    movieCharacters.push_back("Hermione");
    movieCharacters.push_back("Ron");
    for(int i=0; i< movieCharacters.size(); i++)
    {
        cout<<movieCharacters[i]<<endl;
    }
    return 0;
}
```

In the code above, we used a vector of strings to keep track of the character names. The `push_back()` function is used to insert a character name at the end of the vector, while the `size()` function is used to determine the size of the vector. We then printed all the character names.

Next, we have the 'Algorithms'. In the movie-making process, algorithms are essentially instructions given to the characters: the path they should undertake and the actions they are supposed to take. Similarly in programming logic, the STL provides a set of common algorithms like searching, sorting, merging, etc.

For instance, suppose we have a list of the runtime (in minutes) of a series of movies in a franchise and we want them in increasing order to plan a movie marathon.

```cpp
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;

void printMovies(vector<int>& movies){
    for(auto movie: movies){
        cout << movie << " ";
    }
    cout << endl;
}

int main() {
    vector<int> movies = {142, 152, 161, 130, 157, 138};
    cout << "Movies runtime before sorting: ";
    printMovies(movies);
    sort(movies.begin(), movies.end());
    cout << "Movies runtime after sorting: ";
    printMovies(movies);
    return 0;
}
```

In this piece of code, we used the `sort()` algorithm to arrange the movie runtimes in ascending order. Note how the `sort()` function takes in two arguments: the beginning and the end of the vector to specify the range it should sort.

Lastly, we come across 'Iterators'. As the name suggests, they provide a way to access elements in a container sequentially without exposing the underlying details. They act like a bridge between containers and algorithms.

Let's look at an example. Say, you are making a sequel to a very successful movie, but you want to make sure your new movie is not exceeding a certain runtime. STL provides a `max_element` function that can help with just that. 

```cpp
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;

int main() {
    vector<int> movieLengths = {120, 155, 142, 180, 157};

    vector<int>::iterator maxElement;
    maxElement = max_element(movieLengths.begin(), movieLengths.end());

    cout << "The longest movie in the franchise is: " << *maxElement << " minutes long.";
    return 0;
}
```

In the code snippet above, we have a vector called `movieLengths` that contains the lengths of the movies. The `max_element` function sets the iterator `maxElement` to the location of the longest movie in the vector. 

To sum up, these are just a small portion of what the C++ Standard Template Library (STL) offers. It's like exploring a vast movie studio with different sets and characters. It can become your best friend in efficient coding once you get the hang of it. So, enjoy coding just like you enjoy watching a movie.

String Operations

Strings are a fundamental data type in JavaScript. They allow us to store text-based data in variables and manipulate it as needed. In this article, we'll take a look at some of the most commonly used string operations in JavaScript.

### 1. Concatenation
The first operation we're going to talk about is concatenation. This is the process of joining two or more strings together. We can use the + operator to concatenate strings.

For example, let's say we have two variables:
```js
var name = "John";
var lastName = "Smith";
```
If we want to join these two variables together, we can use the following code:
```js
var fullName = name + " " + lastName; // "John Smith"
```

### 2. Length
The next operation is getting the length of a string. The length property returns the number of characters in a string.

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "Hello, World!";
```
If we want to get the length of this string, we can use the following code:
```js
var len = message.length; // 13
```

### 3. Indexing
The next operation is getting a specific character from a string. We can use brackets to access characters at a specific index. The first character in a string has an index of 0, the second character has an index of 1, and so on.

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "Hello, World!";
```
If we want to get the third character in this string (which is an 'o'), we can use the following code:
```js
var char = message[2]; // "o"
```

### 4. Substring Extraction
The next operation is extracting a substring from a string. We can use the slice method to extract a portion of a string. This method takes two arguments: the starting index and the ending index (inclusive).

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "Hello, World!";
```
If we want to extract the substring 'llo Wo', we can use the following code:
```js
var substr = message.slice(0, 5) + " " + message.slice(6); // "llo Wo"
```

### 5. Replace
The next operation is replacing a specific substring with another string. We can use the replace method to achieve this. This method takes two arguments: the search value (what we want to replace) and the replacement value (what we want to replace it with).

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "Hello, World!";
```
If we want to replace the word 'World' with 'Earth', we can use the following code:
```js
var newMessage = message.replace("World", "Earth"); // "Hello, Earth!"
```

### 6. ToUpperCase and toLowerCase
The next two operations are converting a string to uppercase or lowercase. We can use the toUpperCase and toLowerCase methods to achieve this. These methods return a new string with all of its characters converted to uppercase or lowercase, respectively.

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "Hello, World!";
```
If we want to convert this string to uppercase, we can use the following code:
```js
var uppercase = message.toUpperCase(); // "HELLO, WORLD!"
```

### 7. Trimming
The next operation is removing whitespace from both ends of a string. We can use the trim method to achieve this. This method returns a new string with all whitespace (spaces, tabs, and line breaks) removed from both ends of the original string.

For example, let's say we have a variable called `message` that contains the following value:
```js
var message = "   Hello, World!  ";
```
If we want to remove all whitespace from both ends of this string, we can use the following code:
```js
var trimmed = message.trim(); // "Hello, World!"
```

In this article, we've gone over some of the most commonly used string operations in JavaScript. These operations are incredibly useful for manipulating and processing text-based data. Whether you're working with user input or building web applications, understanding these operations will help you write more efficient and effective code.

Recursion

Recursion is a programming paradigm that involves solving a problem by breaking it down into smaller sub-problems of the same kind. This approach can be highly effective when dealing with complex problems that require repeated calculations or processing. In JavaScript, recursion is implemented using functions that call themselves repeatedly until a base case is reached.

Recursion is not a new concept in programming, and it has been around for decades. However, the rise of JavaScript as a popular programming language has made it an increasingly popular method for solving complex problems. Recursive programming in JavaScript can be highly effective when dealing with large datasets or complex algorithms that require repeated calculations.

In this article, we will explore what recursion is and how to use it effectively in JavaScript. We will also cover some common use cases for recursion in JavaScript and provide examples of code to illustrate our points.

##### What is Recursion?

Recursion is the process of a function calling itself repeatedly until a base case is reached. A base case is a condition that causes the function to terminate without further calls to itself. The key idea behind recursion is that a complex problem can be broken down into smaller sub-problems that are easier to solve.

Recursion can be used in many different programming languages, including JavaScript. In JavaScript, a recursive function looks very similar to any other function, with the exception of one important difference: it calls itself. A common example of a recursive function is the factorial function.

##### The Factorial Function

The factorial function is a mathematical function that takes an integer as input and returns its factorial value. The factorial of a number n is defined as the product of all positive integers from 1 to n. For example, the factorial of 5 (written as 5!) is equal to 5 x 4 x 3 x 2 x 1 = 120.

To calculate the factorial of a number in JavaScript using recursion, we can define a function that takes an integer n and calls itself repeatedly until it reaches a base case:

```js
function factorial(n) {
  if (n === 0) {
    return 1; // base case: the factorial of 0 is 1
  } else {
    return n * factorial(n - 1); // recursive call
  }
}
```

In this code, we define a function called `factorial` that takes an integer as input. If the number is equal to 0 (the base case), we return 1. Otherwise, we use recursion to calculate the factorial of n - 1 and multiply it by n. This process continues until we reach the base case, at which point the function stops calling itself and returns the final result.

##### Another Example: Finding the Length of a List

Recursion can be used in many different ways to solve problems in JavaScript. For example, let's say we want to find the length of a list without using a for loop or any other iterative method. We could use recursion to calculate the length of the list by calling itself repeatedly until it reaches an empty array (the base case).

Here is an example of how to use recursion to find the length of a list in JavaScript:

```js
function length(arr) {
  if (arr.length === 0) { // base case: an empty array has a length of 0
    return 0;
  } else {
    return 1 + length(arr.slice(1)); // recursive call with sliced array
  }
}
```

In this code, we define a function called `length` that takes an array as input. If the array is empty (the base case), we return 0. Otherwise, we use recursion to calculate the length of the array by slicing off the first element and calling `length` on the remaining elements in the array. This process continues until we reach the base case, at which point the function stops calling itself and returns the final result.

##### Common Use Cases for Recursion in JavaScript

Recursion can be used to solve a wide variety of problems in JavaScript. Some common use cases for recursion include:

- Sorting algorithms: Many sorting algorithms, such as quicksort or mergesort, use recursion to divide the input data into smaller subsets that are easier to sort.
- Tree traversal: Recursion can be used to traverse trees and perform operations on each node in the tree.
- Depth-first search: Recursion is often used to implement depth-first search algorithms, which explore all possible paths in a graph or tree before backtracking.
- Generating Fibonacci numbers: The Fibonacci sequence can be generated using recursion by calling itself repeatedly with different arguments.

In conclusion, recursion is an important programming paradigm that can help us solve complex problems using functions that call themselves repeatedly until a base case is reached. While recursive programming can be more difficult to understand than iterative programming, it offers many advantages for solving certain types of problems in JavaScript. By mastering the art of recursion, we can become better programmers and tackle more challenging problems with ease.

In this tutorial, we will be exploring the basics of Python setup along with various Python tools that would help you get started with Python development. Python is a powerful, flexible, open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. 

To begin with Python programming, the first step is choosing an appropriate Integrated Development Environment (IDE) for writing and running your Python scripts. There are plenty of Python IDEs out there, but for beginners, it's recommended to start with IDLE (Python’s Integrated Development and Learning Environment), which comes with Python installation.

**Python Installation**

Python can be installed on Windows, Linux, and Mac. One needs to visit the Python's official website, https://www.python.org/, and download the appropriate version based on the operating system. Follow the instructions on the screen for a successful installation.

Your Python installation also comes bundled with IDLE; you can search for it in the Start menu.

However, for more extensive programming, and especially for data analysis purposes, more sophisticated environments like Jupyter notebook, Spyder, Visual Studio Code, PyCharm could be used. These tools come bundled with Anaconda installation.

**Anaconda Installation**

Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment.

To install Anaconda, visit https://www.anaconda.com/products/distribution, download the installer, and follow its instructions to install.

**Setting Up a Virtual Environment**

Creating a virtual environment is a good practice for keeping the dependencies required by different projects separate. It's like an isolated box where we install the specific versions of Python packages a project needs. We can have multiple such boxes (environments) for different projects.

Here's how to create a virtual environment using venv (Python 3.5 or later):

```py
# create a new virtual environment
python3 -m venv tutorial-env

# activate the virtual environment
source tutorial-env/bin/activate  # Linux or MacOS
.\tutorial-env\Scripts\activate   # Windows
```

With your virtual environment activated, you can now install packages without affecting your main Python installation.

**Python Tools**

For Python development, you will use a variety of tools to assist in your work. 

- **pip**: This is Python's official package installer, which allows you to install libraries and tools for your projects. 

   Install a package with pip:

```py
pip install numpy
```

- **Jupyter Notebook**: It provides a web-based Python development environment, which is great for data manipulation and visualization.

   Start a new notebook with Jupyter:

```py
jupyter notebook
```
   
- **Pytest**: It is a testing tool that allows you to write test codes for your applications and execute them.

   Run tests with pytest:

```py
pytest test_sample.py
```

That's a basic setup to start coding with Python. As you move in your journey, you will encounter, learn, and start using much more complex tools, libraries, and environments that Python community provides. Always remember, the right tool will not only save your time but also will make your work enjoyable.

Regular Expression

Regular expressions, also known as regex or regexp, serve as a powerful tool for manipulating text and data. They are a sequence of characters that form a search pattern, often used with string methods or in applications that require data extraction. In this chapter, we'll illuminate important concepts around regular expressions and their implementation in Python.

Python's built-in function `re` supports regular expressions operations like matching, searching, splitting, and replacing the strings. To use regular expressions in Python, you should import the `re` module using the import statement.

```python
import re
```
Let's start by understanding the basic regular expression syntax through various examples. Some of the commonly used metacharacters, which hold special meanings in regular expressions, include `. ^ $ * + ? { } [ ] \ | ( )`. In the context of regex, these characters can't be used literally.

An important operation in regex is pattern matching. Let's use `re.match()` function for this:

```python
import re
  
# Match the pattern at the start of the text
print(re.match('python', 'python is easy to learn'))

# Output: <re.Match object; span=(0, 6), match='python'>
```

Here, `re.match()` function returns a match object if the pattern is located at the beginning of the string. If matching fails, it returns None.

Now, let's discuss `re.search()`. `re.search(pat, str)` function searches the pattern pat in the string str and returns a match object if found, else it returns None.

```python
import re
  
# Search the pattern in the text
print(re.search('easy', 'python is easy to learn'))

# Output: <re.Match object; span=(9, 13), match='easy'>
```

`re.findall()` returns all non-overlapping matches of pattern in string, as a list of strings. Here’s an example:

```python
import re
  
# Find all occurrence of the pattern
print(re.findall('a', 'abcdaef'))

# Output: ['a', 'a']
```

In the example above, `re.findall()` returns a list containing all occurrences of 'a'.

Regular expressions also leverage metacharacters for more complex pattern searching. Square brackets `[ ]` in regular expressions are used to include a set of characters, any one of which can match.

```python
import re
  
# find words starting with 'a' and ending with 'd'
print(re.findall('[a-z]*d', 'abcd abc abd add'))

# Output: ['abcd', 'abd', 'add']
```
In this example, the pattern `[a-z]*d` matches words starting with any lowercase letter and ending with 'd'.

In summary, Python's `re` module, which provides full support for Perl-like regular expressions, is a potent weapon in any Python programmer's armory. It is crucial to understand and utilize it well in order to manipulate strings effectively and efficiently.

We’ve covered the basics of regular expression in Python, including various functions such as `re.match()`, `re.search()`, and `re.findall()`. As you practice these and dive deeper into Python, remember to experiment with different patterns and functions. Keep practicing for solid mastery over regular expressions.

Find Target in a Maze

Challenge Instructions

Problem Statement

Example

Constraints

Expected Challenge Output

Test Cases