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Common Lisp vs R: What are the differences?

Introduction

In this Markdown code, we will discuss the key differences between Common Lisp and R. Both languages have their own unique features and are commonly used in different domains. Below are the main differences explained in detail.

  1. Syntax: The syntax of Common Lisp and R differ significantly. Common Lisp follows a prefix notation called S-expressions, which uses parentheses to separate functions and arguments. On the other hand, R has a more traditional infix notation, where functions and arguments are separated by commas or parentheses are optional. The syntax of Common Lisp can be more complex and explicit, while R's syntax is simpler and more concise.

  2. Functional Programming: Common Lisp is a versatile language that supports both procedural and functional programming paradigms, while R is primarily designed for statistical computing and data analysis, with a strong focus on functional programming. R provides powerful tools and libraries specifically geared towards statistical modeling, while Common Lisp offers a broader set of features for general-purpose programming.

  3. Packages and Libraries: R has a vast collection of packages and libraries available through the Comprehensive R Archive Network (CRAN) and other sources. These packages provide specialized functions and tools for various statistical and data analysis tasks. Common Lisp also has libraries available, but the ecosystem is not as extensive as that of R for statistical computing. Common Lisp's libraries are more focused on general-purpose programming and application development.

  4. Community and Adoption: R has gained significant popularity in the field of data analysis and is widely adopted in academia, research, and industry. There is a large community of R users and developers who actively contribute to the language and its ecosystem. Common Lisp, while being a powerful and flexible language, has a smaller community and is less commonly used in mainstream applications. However, Common Lisp has a dedicated following and is often favored by enthusiasts who appreciate its expressiveness and extensibility.

  5. Metaprogramming: Common Lisp provides powerful metaprogramming capabilities through the use of macros. Macros allow for code generation and transformation, enabling the programmer to extend the language and create domain-specific languages. R, on the other hand, does not have native support for macros and metaprogramming. While R's functional capabilities provide some flexibility, it does not offer the same level of metaprogramming and language extension as Common Lisp.

  6. Development Environment and Tooling: R has a rich ecosystem of development tools and integrated development environments (IDEs) specifically tailored for statistical computing and data analysis, such as RStudio. These tools provide features like code completion, debugging, and data visualization. Common Lisp also has some development environments available but may not offer the same level of specialized tooling for statistical computing as R. Common Lisp's tools are more focused on general-purpose programming and application development.

In summary, Common Lisp and R differ in terms of syntax, programming paradigms, available libraries, community adoption, metaprogramming capabilities, and development tooling. While R is designed for statistical computing and has a strong focus on functional programming, Common Lisp is a more versatile language with a broader set of features for general-purpose programming.

Decisions about Common Lisp and R Language

MACHINE LEARNING

Python is the default go-to for machine learning. It has a wide variety of useful packages such as pandas and numpy to aid with ML, as well as deep-learning frameworks. Furthermore, it is more production-friendly compared to other ML languages such as R.

Pytorch is a deep-learning framework that is both flexible and fast compared to Tensorflow + Keras. It is also well documented and has a large community to answer lingering questions.

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Pros of Common Lisp
Pros of R Language
  • 24
    Flexibility
  • 22
    High-performance
  • 17
    Comfortable: garbage collection, closures, macros, REPL
  • 13
    Stable
  • 12
    Lisp
  • 8
    Code is data
  • 6
    Can integrate with C (via CFFI)
  • 6
    Multi paradigm
  • 5
    Lisp is fun
  • 4
    Macros
  • 4
    Easy Setup
  • 3
    Parentheses
  • 3
    Open source
  • 3
    Purelly functional
  • 3
    Elegant
  • 1
    DSLs
  • 1
    Multiple values
  • 1
    CLOS/MOP
  • 1
    Clean semantics
  • 1
    Will still be relevant 100 years from now
  • 1
    Still decades ahead of almost all programming languages
  • 1
    Best programming language
  • 1
    Simple syntax
  • 1
    Powerful
  • 1
    Generic functions
  • 1
    Can implement almost any feature as a library
  • 1
    Formal specification, multiple implementations
  • 84
    Data analysis
  • 63
    Graphics and data visualization
  • 54
    Free
  • 45
    Great community
  • 38
    Flexible statistical analysis toolkit
  • 27
    Easy packages setup
  • 27
    Access to powerful, cutting-edge analytics
  • 18
    Interactive
  • 13
    R Studio IDE
  • 9
    Hacky
  • 7
    Shiny apps
  • 6
    Shiny interactive plots
  • 6
    Preferred Medium
  • 5
    Automated data reports
  • 4
    Cutting-edge machine learning straight from researchers
  • 3
    Machine Learning
  • 2
    Graphical visualization
  • 1
    Flexible Syntax

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Cons of Common Lisp
Cons of R Language
  • 4
    Too many Parentheses
  • 3
    Standard did not evolve since 1994
  • 2
    Small library ecosystem
  • 2
    No hygienic macros
  • 1
    Inadequate community infrastructure
  • 1
    Ultra-conservative community
  • 6
    Very messy syntax
  • 4
    Tables must fit in RAM
  • 3
    Arrays indices start with 1
  • 2
    Messy syntax for string concatenation
  • 2
    No push command for vectors/lists
  • 1
    Messy character encoding
  • 0
    Poor syntax for classes
  • 0
    Messy syntax for array/vector combination

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What is Common Lisp?

Lisp was originally created as a practical mathematical notation for computer programs, influenced by the notation of Alonzo Church's lambda calculus. It quickly became the favored programming language for artificial intelligence (AI) research. As one of the earliest programming languages, Lisp pioneered many ideas in computer science, including tree data structures, automatic storage management, dynamic typing, conditionals, higher-order functions, recursion, and the self-hosting compiler. [source: wikipedia]

What is R Language?

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

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What companies use Common Lisp?
What companies use R Language?
See which teams inside your own company are using Common Lisp or R Language.
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What tools integrate with Common Lisp?
What tools integrate with R Language?

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Aug 28 2019 at 3:10AM

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What are some alternatives to Common Lisp and R Language?
Clojure
Clojure is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system.
Haskell
It is a general purpose language that can be used in any domain and use case, it is ideally suited for proprietary business logic and data analysis, fast prototyping and enhancing existing software environments with correct code, performance and scalability.
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
Racket
It is a general-purpose, multi-paradigm programming language based on the Scheme dialect of Lisp. It is designed to be a platform for programming language design and implementation. It is also used for scripting, computer science education, and research.
Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!
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