Python DSLs: Tailored Solutions for Specialized Domains

When we write the program, we find that the problems we solve belong to the specific areas, also called as domains, such as:

• A banking system needs to describe transactions, interest rates.
• A web application needs to define the routes, templates and responses.

By using the General Purpose Language (GPL) like Python or Java, we can solve these problems, but the code becomes too detailed and repetitive. Hence, we will use the DSL (Domain Specific Language.

DSL - Domain Specific Language

The Domain Specific Language is a programming or specification language dedicated to the particular domain. It is different from the general purpose language (GPL like Python, C++ or Java). They are of two types:

• External DSL − It is completely a new language with its own syntax and compiler
• Internal DSL (Embedded DSL) − A DSL built inside ther host language, using its syntax and constructs.

External DSL

For working with the databases, we use the SQL, instead of writing loops to scan data manually, we simply write:

SELECT name FROM users WHERE age > 10;

For designing the webpages, we use the HTML, Instead of managing the strings of text anf positions manually, we simply declare:

<h1>Welcome To Tutorialspoint</h1>

Internal DSL

In Python, the domain specific language is built on the top of the Python syntax. Frameworks like flask or Pandas are the examples of DSL- like libraries that helps to express the problems clearly.

@app.route('/home')
def home():
 return "Hello...!"

Why DSLs in Python

Python is the best choice for the DSL because:

• Its syntax is simple and expressive.
• It allows the functions and classes to be used as building blocks.

For example, the testing frameworks like pytest or web frameworks like Flask are DSL-like. Instead of writing the low-level logic, they let to write the expressive commands.

Let's dive into the example, to learn more abou the domain specific language.

Example 1

Let's look at the following example, where we are going to the abstract the language of the math into the named functions.

def add(x, y):
 return x + y
def multiply(x, y):
 return x * y
print(add(multiply(1, 3), multiply(2, 4)))

Following is the output of the above program -

11

Example 2

Consider the following example, where we are going to use the DSL in the configuration files.

class demo:
 def __init__(self):
 self.settings = {}
 def set(self, key, value):
 self.settings[key] = value
 return self
 def get(self, key):
 return self.settings.get(key)
result = demo()
result.set("host", "Welcome").set("port", 1231)
print(result.get("host")) 

The output of the above program is -

Welcome

Example 3

In the following example, we are going to observe the DSL for querying data using the SQL syntax inside the Python.

class demo:
 def __init__(x, dataset):
 x.dataset = dataset
 def where(x, condition):
 x.dataset = [item for item in x.dataset if condition(item)]
 return x
 def select(x, selector):
 return [selector(item) for item in x.dataset]
users = [
 {"name": "Ram", "age": 10},
 {"name": "Ravi", "age": 24},
 {"name": "Rahul", "age": 19},
]
result = demo(users).where(lambda u: u["age"] > 18).select(lambda u: u["name"])
print(result)

Following is the output of the above program -

['Ravi', 'Rahul']