Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Julia

635
674
+ 1
171
Python

246K
200.8K
+ 1
6.9K
Stan

64
27
+ 1
0
Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of Julia
Pros of Python
Pros of Stan
  • 25
    Fast Performance and Easy Experimentation
  • 22
    Designed for parallelism and distributed computation
  • 19
    Free and Open Source
  • 17
    Dynamic Type System
  • 17
    Calling C functions directly
  • 16
    Multiple Dispatch
  • 16
    Lisp-like Macros
  • 10
    Powerful Shell-like Capabilities
  • 10
    Jupyter notebook integration
  • 8
    REPL
  • 4
    String handling
  • 4
    Emojis as variable names
  • 3
    Interoperability
  • 1.2K
    Great libraries
  • 964
    Readable code
  • 847
    Beautiful code
  • 788
    Rapid development
  • 691
    Large community
  • 438
    Open source
  • 393
    Elegant
  • 282
    Great community
  • 273
    Object oriented
  • 221
    Dynamic typing
  • 77
    Great standard library
  • 60
    Very fast
  • 55
    Functional programming
  • 51
    Easy to learn
  • 46
    Scientific computing
  • 35
    Great documentation
  • 29
    Productivity
  • 28
    Easy to read
  • 28
    Matlab alternative
  • 24
    Simple is better than complex
  • 20
    It's the way I think
  • 19
    Imperative
  • 18
    Very programmer and non-programmer friendly
  • 18
    Free
  • 17
    Powerfull language
  • 17
    Machine learning support
  • 16
    Fast and simple
  • 14
    Scripting
  • 12
    Explicit is better than implicit
  • 11
    Ease of development
  • 10
    Clear and easy and powerfull
  • 9
    Unlimited power
  • 8
    Import antigravity
  • 8
    It's lean and fun to code
  • 7
    Print "life is short, use python"
  • 7
    Python has great libraries for data processing
  • 6
    Rapid Prototyping
  • 6
    Readability counts
  • 6
    Now is better than never
  • 6
    Great for tooling
  • 6
    Flat is better than nested
  • 6
    Although practicality beats purity
  • 6
    I love snakes
  • 6
    High Documented language
  • 6
    There should be one-- and preferably only one --obvious
  • 6
    Fast coding and good for competitions
  • 5
    Web scraping
  • 5
    Lists, tuples, dictionaries
  • 5
    Great for analytics
  • 4
    Easy to setup and run smooth
  • 4
    Easy to learn and use
  • 4
    Plotting
  • 4
    Beautiful is better than ugly
  • 4
    Multiple Inheritence
  • 4
    Socially engaged community
  • 4
    Complex is better than complicated
  • 4
    CG industry needs
  • 4
    Simple and easy to learn
  • 3
    It is Very easy , simple and will you be love programmi
  • 3
    Flexible and easy
  • 3
    Many types of collections
  • 3
    If the implementation is easy to explain, it may be a g
  • 3
    If the implementation is hard to explain, it's a bad id
  • 3
    Special cases aren't special enough to break the rules
  • 3
    Pip install everything
  • 3
    List comprehensions
  • 3
    No cruft
  • 3
    Generators
  • 3
    Import this
  • 3
    Powerful language for AI
  • 2
    Can understand easily who are new to programming
  • 2
    Should START with this but not STICK with This
  • 2
    A-to-Z
  • 2
    Because of Netflix
  • 2
    Only one way to do it
  • 2
    Better outcome
  • 2
    Batteries included
  • 2
    Good for hacking
  • 2
    Securit
  • 1
    Procedural programming
  • 1
    Best friend for NLP
  • 1
    Slow
  • 1
    Automation friendly
  • 1
    Sexy af
  • 0
    Ni
  • 0
    Keep it simple
  • 0
    Powerful
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of Julia
    Cons of Python
    Cons of Stan
    • 5
      Immature library management system
    • 4
      Slow program start
    • 3
      JIT compiler is very slow
    • 3
      Poor backwards compatibility
    • 2
      Bad tooling
    • 2
      No static compilation
    • 53
      Still divided between python 2 and python 3
    • 28
      Performance impact
    • 26
      Poor syntax for anonymous functions
    • 22
      GIL
    • 19
      Package management is a mess
    • 14
      Too imperative-oriented
    • 12
      Hard to understand
    • 12
      Dynamic typing
    • 12
      Very slow
    • 8
      Indentations matter a lot
    • 8
      Not everything is expression
    • 7
      Incredibly slow
    • 7
      Explicit self parameter in methods
    • 6
      Requires C functions for dynamic modules
    • 6
      Poor DSL capabilities
    • 6
      No anonymous functions
    • 5
      Fake object-oriented programming
    • 5
      Threading
    • 5
      The "lisp style" whitespaces
    • 5
      Official documentation is unclear.
    • 5
      Hard to obfuscate
    • 5
      Circular import
    • 4
      Lack of Syntax Sugar leads to "the pyramid of doom"
    • 4
      The benevolent-dictator-for-life quit
    • 4
      Not suitable for autocomplete
    • 2
      Meta classes
    • 1
      Training wheels (forced indentation)
      Be the first to leave a con

      Sign up to add or upvote consMake informed product decisions

      8.2K
      12.6K
      3.4K
      62.4K
      2.2M
      263
      419

      What is Julia?

      Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

      What is 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.

      What is Stan?

      A state-of-the-art platform for statistical modeling and high-performance statistical computation. Used for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Julia?
      What companies use Python?
      What companies use Stan?

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Julia?
      What tools integrate with Python?
      What tools integrate with Stan?

      Sign up to get full access to all the tool integrationsMake informed product decisions

      Blog Posts

      Sep 29 2020 at 7:36PM

      WorkOS

      PythonSlackG Suite+17
      6
      3179
      PythonDockerKubernetes+7
      3
      1170
      PythonDockerKubernetes+14
      12
      2664
      Oct 3 2019 at 7:13PM

      Ably Realtime

      JavaScriptPythonNode.js+8
      5
      3908
      Aug 28 2019 at 3:10AM

      Segment

      PythonJavaAmazon S3+16
      7
      2647
      JavaScriptPythonPubNub+4
      7
      1611
      What are some alternatives to Julia, Python, and Stan?
      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.
      MATLAB
      Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
      Rust
      Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
      Golang
      Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.
      NumPy
      Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
      See all alternatives