Writing a programming language can be a daunting task, but with determination and a clear roadmap, it is achievable. In this blog post, I will be sharing my experience of creating a programming language named Jojo, which is compatible with generative AI and current world events.
Step 1: Define the Syntax
The first step in creating a programming language is defining the syntax. The syntax is the set of rules that dictate how code is written in the language. For Jojo, I wanted to create a language that was easy to read and write, but also powerful enough to handle complex tasks. I settled on a syntax that is similar to Python, with a focus on readability and simplicity.
Step 2: Create the Lexer and Parser
Once the syntax was defined, I moved on to creating the lexer and parser. The lexer is responsible for breaking down the code into individual tokens, such as keywords, operators, and variables. The parser then takes these tokens and turns them into a tree-like structure called an abstract syntax tree (AST).
Here's the Python code that shows how the lexer and parser work:
class Lexer:
def __init__(self, code):
self.code = code
self.tokens = []
def tokenize(self):
# Code to tokenize the code string
class Parser:
def __init__(self, lexer):
self.lexer = lexer
self.ast = None
def parse(self):
# Code to parse the tokens into an AST
Step 3: Implement the Interpreter
The interpreter is the heart of the programming language. It takes the AST and executes the code. For Jojo, I wanted to make sure that the interpreter was fast and efficient, so I chose to implement it in C++. Here's how the interpreter works:
class Interpreter {
public:
void visit(VariableNode* node) {
// Code to retrieve the value of the variable
}
void visit(AssignmentNode* node) {
// Code to assign a value to a variable
}
void visit(FunctionCallNode* node) {
// Code to call a function
}
// Other visit methods for each AST node type
};
Step 4: Add Support for Generative AI
Jojo is designed to be compatible with generative AI. To achieve this, I added a built-in library for working with neural networks. Here's how I used Jojo to create a simple neural network using Python:
import jojo.nn as nn
model = nn.Sequential(
nn.Linear(784, 128),
nn.ReLU(),
nn.Linear(128, 10),
nn.Softmax()
)
# Code to train and use the model
Step 5: Make Jojo Relevant to Current World Events
Jojo is designed to be a modern programming language that is relevant to current world events. To achieve this, I added built-in libraries for working with data related to current events. For example, you can use Jojo to retrieve and analyze COVID-19 data using Python:
import jojo.covid as covid
data = covid.get_data()
# Code to analyze the data
In conclusion, creating a programming language is no easy feat, but with the right approach and mindset, it is achievable. Jojo is a powerful programming language that is designed to be compatible with generative AI and relevant to current world events. With its simple syntax, efficient interpreter, and built-in libraries, Jojo is a great choice for anyone looking to create innovative applications. Thank you and nice building!