Update with cleanup

CMakeLists.txt

@@ -57,13 +57,6 @@ find_package(xeus ${xeus_REQUIRED_VERSION} REQUIRED)
 find_package(cppzmq REQUIRED CONFIG)
 find_package(pugixml REQUIRED)
 
-#find_package(LLVM REQUIRED CONFIG PATHS "${LLVM_CONFIG_EXTRA_PATH_HINTS}" NO_DEFAULT_PATH)
-#find_package(Clang REQUIRED CONFIG PATHS "${LLVM_CONFIG_EXTRA_PATH_HINTS}/lib/cmake/clang/" NO_DEFAULT_PATH)
-find_package(LLVM ${llvm_REQUIRED_VERSION} REQUIRED CONFIG PATHS "${LLVM_CONFIG_EXTRA_PATH_HINTS}")
-find_package(Clang REQUIRED CONFIG PATHS "${LLVM_BINARY_DIR}/lib/cmake/clang/" "${LLVM_CONFIG_EXTRA_PATH_HINTS}/lib/cmake/clang/" NO_DEFAULT_PATH)
-include_directories(SYSTEM ${LLVM_INCLUDE_DIRS} ${CLANG_INCLUDE_DIRS})
-link_directories(${LLVM_LIBRARY_DIR})
-
 #CppInterOp
 #TODO: Make CppInterOp cmake package and use find_package
 #find_package(CppInterOp REQUIRED CONFIG PATHS "${CPPINTEROP_DIR}")
@@ -75,6 +68,8 @@ message(STATUS "CppInterOp Imported location: ${CPPINTEROP_DIR}/lib/libclangCppI
 message(STATUS "CppInterOp include location: ${CPPINTEROP_DIR}/../include")
 
 
+###
+
 # Before including llvm suppress the option() honors normal variables warning.
 if(POLICY CMP0077)
   cmake_policy(SET CMP0077 NEW)

docs/FAQ.rst

@@ -4,6 +4,13 @@ FAQ
 -   **What is Xeus-Clang-REPL?**
     Xeus-Clang-REPL is an interactive programming environment that allows you to 
     execute C++ code in a Jupyter Notebook using the Clang-REPL interpreter.
+
+    - Xeus: Xeus is part of the Jupyter ecosystem, which is known for creating 
+      interactive notebooks that can include code, visualizations, and narrative text.
+    - Clang: Clang is a C/C++ compiler front-end that is part of the LLVM project.
+      It's known for its fast compilation times and high-quality diagnostics.
+    - REPL: REPL stands for Read-Eval-Print Loop. It's an interactive programming
+      environment.
 
 -   **How do I install and build from source the Xeus-Clang-REPL?**
     Installation instructions can typically be found in the project's documentation.
@@ -12,14 +19,23 @@ FAQ
 -   **What are the benefits of using Xeus-Clang-REPL?**
     You can interactively run and debug C++ code in a Jupyter notebook.
     You can use xeus-clang-repl to prototype C++ code quickly and easily.
+    - Rapid Prototyping: Quickly prototype and experiment with C++ code without
+      the need to create a full project or compile an entire codebase. 
+    - Immediate Feedback: As a REPL, Xeus-Clang provides instant feedback as you
+      write and execute code. This helps catch errors early.
+    - Interactive Learning: Xeus-Clang-REPL allows learners to interactively
+      explore C++ concepts and practice coding in a controlled environment.
+    - Debugging: By isolating and testing specific pieces of code, you can more
+      easily identify and fix issues in small code snippets.
+
 
 -   **How do I create a new session?**
-    To create a new Xeus-Clang-REPL session, you would open Jupyter Notebook,
+    To create a new Xeus-Clang-REPL session, you simply open Jupyter Notebook,
     select the appropriate kernel, and create a new notebook file.
 
 -   **Where can I find documentation and examples for Xeus-Clang-REPL?**
-    Documentation, tutorials, and references can be found on this Documentation 
-    itself, :doc:`Documentation <DevelopersDocumentation>`.
+    Documentation, tutorials, and references can other directories of current 
+    documentation, i.e :doc:`Documentation <DevelopersDocumentation>`.
 
 -   **How do I contribute to the project?**
     Instructions for reporting issues and contributing to the project are

docs/UsingXeus-Clang-REPL.rst

@@ -1,15 +1,36 @@
 Using xeus-clang-repl
 ---------------------
 
-- With xeus-clang-repl, you can write and execute C++ code interactively, seeing
-  the results immediately. This REPL nature allows you to iterate quickly
-  without the overhead of compiling and running separate C++ programs.
+- Rapid Iteration:
+  With xeus-clang-repl, you can write and execute C++ code interactively, seeing 
+  the results immediately. This REPL nature allows you to iterate quickly without 
+  the overhead of compiling and running separate C++ programs.
 
-- To achieve C++ and Python integration within a Jupyter environment we can use
-  xeus-clang-repl. Thereby you can write and execute C++ code interactively in
-  this environment.
+- Python-C++ Binding:
+  To achieve C++ and Python integration within a Jupyter environment, we can use 
+  xeus-clang-repl. Thereby, you can write and execute C++ code interactively in this
+  environment.
 
-- Jupyter notebooks support magic commands (**%%python**) and inline code
-  execution for different languages. We use these features to run Python and C++
-  code in separate cells to achieve interactive communication between them.
+- Magic Commands:
+  Jupyter notebooks support magic commands (%%python) and inline code execution 
+  for different languages. We use these features to run Python and C++ code in 
+  separate cells to achieve interactive communication between them.
 
+- Learning and Teaching:
+  C++ enthusiasts can use it to explain and experiment with C++ concepts in a live,
+  interactive manner. Students can follow along and test code snippets in real-time,
+  improving their understanding of C++. This also applies to C++ workshops and 
+  coding boot camps.
+
+- Exploring C++ Libraries:
+  You can explore the vast set of C++ libraries and frameworks without having to
+  create a complete project. This allows you to quickly assess whether a library
+  suits your needs by experimenting with its functions and classes.
+
+- Collaborative Coding:
+  Xeus-clang-repl can act as a shared environment where team members can experiment,
+  debug, and discuss code in real-time.
+
+- Debugging and Testing:
+  You can isolate problematic code segments, experiment with multiple inputs, and
+  interactively walk through your code to identify and fix the issues.

docs/reference.rst

@@ -1,5 +1,5 @@
-Reference
----------
+References
+----------
 
 1. `Xeus-cling <https://github.com/jupyter-xeus/xeus-cling>`_
     Xeus-cling offers a similar interactive experience as xeus-clang-repl but uses 

docs/tutorials.rst

@@ -1,12 +1,12 @@
 Tutorials
------------
+---------
 
 This tutorial emphasises the abilities and usage of Xeus-Clang-REPL. Let's get
 started! The tutorial demonstrates examples of C++ and C++-python integration
 on Jupyter kernels.
 
-1. Install the xeus-clang-repl using conda forge (from source) or run it using the
-Dockerfile.
+1. Install the xeus-clang-repl using conda forge (from source) or run it using 
+   the Dockerfile.
 
 2. Launch the Jupyter Notebook with C++-14, C++-17 kernels available.
 
@@ -49,6 +49,27 @@ in python which have been initialised in C++. In the following context, we have
 tried the vice versa as well of using the variables in Python (`new_python_var`)
 which have been defined in C++.
 
+.. image:: integration-demo.png
+   :width: 200px
+   :height: 100px
+   :scale: 400 %
+   :align: center
+
+We are taking another example of working with functions that can be used in
+to call functions defined in C++ in python code with help of magic commands.
+
+.. code-block:: bash
+
+   In[1] #include <iostream>
+
+   In[2] void Cpp() {
+         std::cout << "Hello World C++!" << std::endl;
+         }
+
+   In[3] %%python
+
+   In[4] Cpp()
+
 The project is under development and is subject to changes as C++-Python integration
 within the same Jupyter cell is quite challenging. Please ensure that you have
 xeus-clang-repl and your Jupyter environment set up before attempting to run C++