CodeConvert AI - Convert code with a click of a button

How to use this tool?

This free online converter lets you convert code from Python to SAS in a click of a button. To use this converter, take the following steps -

Type or paste your Python code in the input box.
Click the convert button.
The resulting SAS code from the conversion will be displayed in the output box.

Examples

The following are examples of code conversion from Python to SAS using this converter. Note that you may not always get the same code since it is generated by an AI language model which is not 100% deterministic and gets updated from time to time.

Example 1 - Is String Palindrome

Program that checks if a string is a palindrome or not.

Python

SAS

Example 2 - Even or Odd

A well commented function to check if a number if odd or even.

Python

SAS

Key differences between Python and SAS

Characteristic	Python	SAS
Syntax	Python has a simple and easy-to-learn syntax that emphasizes readability and reduces the cost of program maintenance. It uses indentation to create blocks, and its syntax allows programmers to express concepts in fewer lines of code than languages like Java or C++.	SAS has a more complex syntax than Python, with a steeper learning curve. It uses a combination of statements, functions, and macros to perform data analysis and manipulation.
Paradigm	Python is a multi-paradigm language that supports object-oriented, functional, and procedural programming styles.	SAS is primarily a procedural language, although it does support some object-oriented programming concepts.
Typing	Python is dynamically typed, meaning that variable types are determined at runtime. This allows for more flexibility and faster development, but can lead to errors that are not caught until runtime.	SAS is statically typed, meaning that variable types are determined at compile time. This can lead to more errors being caught during development, but can also make development slower and more cumbersome.
Performance	Python is generally slower than SAS for data processing and analysis, but its performance can be improved through the use of libraries like NumPy and Pandas.	SAS is generally faster than Python for data processing and analysis, but its performance can be limited by the amount of memory available on the system.
Libraries and frameworks	Python has a large and active community that has developed many libraries and frameworks for data analysis, machine learning, and web development. Some popular libraries include NumPy, Pandas, and TensorFlow.	SAS has a smaller community than Python, but it has a large number of built-in functions and procedures for data analysis and manipulation.
Community and support	Python has a large and active community that provides support through forums, documentation, and open-source contributions.	SAS has a smaller community than Python, but it is supported by a large corporation (SAS Institute) that provides documentation, training, and technical support.
Learning curve	Python has a relatively low learning curve, especially for programmers who are already familiar with other scripting languages. Its simple syntax and large community make it easy to find resources and get help.	SAS has a steeper learning curve than Python, especially for programmers who are not familiar with statistical programming concepts. Its complex syntax and smaller community can make it more difficult to find resources and get help.

How to use this tool?

Examples

Key differences between Python and SAS

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