Alternatives to Clojure logo

Alternatives to Clojure

Scala, Haskell, Common Lisp, Elixir, and Julia are the most popular alternatives and competitors to Clojure.
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What is Clojure and what are its top alternatives?

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.
Clojure is a tool in the Languages category of a tech stack.
Clojure is an open source tool with 10K GitHub stars and 1.5K GitHub forks. Here’s a link to Clojure's open source repository on GitHub

Top Alternatives to Clojure

  • Scala
    Scala

    Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them. ...

  • Haskell
    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. ...

  • Common Lisp
    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] ...

  • Elixir
    Elixir

    Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain. ...

  • Julia
    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. ...

  • Erlang
    Erlang

    Some of Erlang's uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems. ...

  • Golang
    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. ...

  • Kotlin
    Kotlin

    Kotlin is a statically typed programming language for the JVM, Android and the browser, 100% interoperable with Java ...

Clojure alternatives & related posts

Scala logo

Scala

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7.3K
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A pure-bred object-oriented language that runs on the JVM
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PROS OF SCALA
  • 187
    Static typing
  • 178
    Pattern-matching
  • 177
    Jvm
  • 172
    Scala is fun
  • 138
    Types
  • 95
    Concurrency
  • 88
    Actor library
  • 86
    Solve functional problems
  • 83
    Open source
  • 80
    Solve concurrency in a safer way
  • 44
    Functional
  • 24
    Fast
  • 23
    Generics
  • 18
    It makes me a better engineer
  • 17
    Syntactic sugar
  • 13
    Scalable
  • 10
    First-class functions
  • 10
    Type safety
  • 9
    Interactive REPL
  • 8
    Expressive
  • 7
    SBT
  • 6
    Implicit parameters
  • 6
    Case classes
  • 4
    Used by Twitter
  • 4
    JVM, OOP and Functional programming, and static typing
  • 4
    Rapid and Safe Development using Functional Programming
  • 4
    Object-oriented
  • 3
    Functional Proframming
  • 2
    Spark
  • 2
    Beautiful Code
  • 2
    Safety
  • 2
    Growing Community
  • 1
    DSL
  • 1
    Rich Static Types System and great Concurrency support
  • 1
    Naturally enforce high code quality
  • 1
    Akka Streams
  • 1
    Akka
  • 1
    Reactive Streams
  • 1
    Easy embedded DSLs
  • 1
    Mill build tool
  • 0
    Freedom to choose the right tools for a job
CONS OF SCALA
  • 11
    Slow compilation time
  • 7
    Multiple ropes and styles to hang your self
  • 6
    Too few developers available
  • 4
    Complicated subtyping
  • 2
    My coworkers using scala are racist against other stuff

related Scala posts

Shared insights
on
JavaJavaScalaScalaApache SparkApache Spark

I am new to Apache Spark and Scala both. I am basically a Java developer and have around 10 years of experience in Java.

I wish to work on some Machine learning or AI tech stacks. Please assist me in the tech stack and help make a clear Road Map. Any feedback is welcome.

Technologies apart from Scala and Spark are also welcome. Please note that the tools should be relevant to Machine Learning or Artificial Intelligence.

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Marc Bollinger
Infra & Data Eng Manager at Thumbtack · | 5 upvotes · 624.9K views

Lumosity is home to the world's largest cognitive training database, a responsibility we take seriously. For most of the company's history, our analysis of user behavior and training data has been powered by an event stream--first a simple Node.js pub/sub app, then a heavyweight Ruby app with stronger durability. Both supported decent throughput and latency, but they lacked some major features supported by existing open-source alternatives: replaying existing messages (also lacking in most message queue-based solutions), scaling out many different readers for the same stream, the ability to leverage existing solutions for reading and writing, and possibly most importantly: the ability to hire someone externally who already had expertise.

We ultimately migrated to Kafka in early- to mid-2016, citing both industry trends in companies we'd talked to with similar durability and throughput needs, the extremely strong documentation and community. We pored over Kyle Kingsbury's Jepsen post (https://aphyr.com/posts/293-jepsen-Kafka), as well as Jay Kreps' follow-up (http://blog.empathybox.com/post/62279088548/a-few-notes-on-kafka-and-jepsen), talked at length with Confluent folks and community members, and still wound up running parallel systems for quite a long time, but ultimately, we've been very, very happy. Understanding the internals and proper levers takes some commitment, but it's taken very little maintenance once configured. Since then, the Confluent Platform community has grown and grown; we've gone from doing most development using custom Scala consumers and producers to being 60/40 Kafka Streams/Connects.

We originally looked into Storm / Heron , and we'd moved on from Redis pub/sub. Heron looks great, but we already had a programming model across services that was more akin to consuming a message consumers than required a topology of bolts, etc. Heron also had just come out while we were starting to migrate things, and the community momentum and direction of Kafka felt more substantial than the older Storm. If we were to start the process over again today, we might check out Pulsar , although the ecosystem is much younger.

To find out more, read our 2017 engineering blog post about the migration!

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Haskell logo

Haskell

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1.2K
506
An advanced purely-functional programming language
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PROS OF HASKELL
  • 89
    Purely-functional programming
  • 66
    Statically typed
  • 59
    Type-safe
  • 39
    Open source
  • 38
    Great community
  • 30
    Built-in concurrency
  • 29
    Composable
  • 29
    Built-in parallelism
  • 23
    Referentially transparent
  • 19
    Generics
  • 14
    Intellectual satisfaction
  • 14
    Type inference
  • 11
    If it compiles, it's correct
  • 7
    Flexible
  • 7
    Monads
  • 4
    Proposition testing with QuickCheck
  • 4
    Great type system
  • 3
    Purely-functional Programming
  • 3
    One of the most powerful languages *(see blub paradox)*
  • 2
    Highly expressive, type-safe, fast development time
  • 2
    Reliable
  • 2
    Kind system
  • 2
    Pattern matching and completeness checking
  • 2
    Better type-safe than sorry
  • 2
    Type classes
  • 2
    Great maintainability of the code
  • 2
    Fun
  • 2
    Best in class thinking tool
  • 0
    Orthogonality
  • 0
    Predictable
CONS OF HASKELL
  • 8
    Error messages can be very confusing
  • 8
    Too much distraction in language extensions
  • 4
    Libraries have poor documentation
  • 3
    No best practices
  • 3
    No good ABI
  • 2
    Sometimes performance is unpredictable
  • 2
    Poor packaging for apps written in it for Linux distros
  • 1
    Slow compilation

related Haskell posts

Vadim Bakaev
Shared insights
on
HaskellHaskellScalaScala

Why I am using Haskell in my free time?

I have 3 reasons for it. I am looking for:

Fun.

Improve functional programming skill.

Improve problem-solving skill.

Laziness and mathematical abstractions behind Haskell makes it a wonderful language.

It is Pure functional, it helps me to write better Scala code.

Highly expressive language gives elegant ways to solve coding puzzle.

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Common Lisp logo

Common Lisp

189
242
143
The modern, multi-paradigm, high-performance, compiled, ANSI-standardized descendant of the long-running family of Lisp programming languages
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143
PROS OF COMMON LISP
  • 24
    Flexibility
  • 21
    High-performance
  • 17
    Comfortable: garbage collection, closures, macros, REPL
  • 13
    Stable
  • 12
    Lisp
  • 7
    Code is data
  • 6
    Can integrate with C (via CFFI)
  • 6
    Multi paradigm
  • 5
    Lisp is fun
  • 4
    Easy Setup
  • 4
    Macros
  • 3
    Parentheses
  • 3
    Purelly functional
  • 3
    Open source
  • 3
    Elegant
  • 1
    DSLs
  • 1
    Clean semantics
  • 1
    Can implement almost any feature as a library
  • 1
    CLOS/MOP
  • 1
    Powerful
  • 1
    Simple syntax
  • 1
    Best programming language
  • 1
    Will still be relevant 100 years from now
  • 1
    Still decades ahead of almost all programming languages
  • 1
    Generic functions
  • 1
    Multiple values
  • 1
    Formal specification, multiple implementations
CONS OF COMMON LISP
  • 4
    Too many Parentheses
  • 2
    Standard did not evolve since 1994
  • 1
    No hygienic macros
  • 1
    Small library ecosystem

related Common Lisp posts

Elixir logo

Elixir

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1.3K
Dynamic, functional language designed for building scalable and maintainable applications
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PROS OF ELIXIR
  • 171
    Concurrency
  • 158
    Functional
  • 132
    Erlang vm
  • 111
    Great documentation
  • 104
    Great tooling
  • 85
    Immutable data structures
  • 80
    Open source
  • 76
    Pattern-matching
  • 61
    Easy to get started
  • 58
    Actor library
  • 31
    Functional with a neat syntax
  • 29
    Ruby inspired
  • 24
    Homoiconic
  • 24
    Erlang evolved
  • 22
    Beauty of Ruby, Speed of Erlang/C
  • 17
    Fault Tolerant
  • 14
    Simple
  • 13
    High Performance
  • 10
    Good lang
  • 10
    Doc as first class citizen
  • 10
    Pipe Operator
  • 9
    Stinkin' fast, no memory leaks, easy on the eyes
  • 8
    Fun to write
  • 7
    Resilient to failure
  • 7
    OTP
  • 5
    GenServer takes the guesswork out of background work
  • 4
    Not Swift
  • 4
    Pattern matching
  • 4
    Idempotence
  • 4
    Fast, Concurrent with clean error messages
  • 3
    Easy to use
  • 2
    Error isolation
  • 2
    Dynamic Typing
CONS OF ELIXIR
  • 11
    Fewer jobs for Elixir experts
  • 7
    Smaller userbase than other mainstream languages
  • 5
    Elixir's dot notation less readable ("object": 1st arg)
  • 4
    Dynamic typing
  • 1
    Difficult to understand
  • 1
    Not a lot of learning books available

related Elixir posts

Kamil Kowalski
Lead Architect at Fresha · | 28 upvotes · 2M views

When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.

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Sebastian Gębski

Another major decision was to adopt Elixir and Phoenix Framework - the DX (Developer eXperience) is pretty similar to what we know from RoR, but this tech is running on the top of rock-solid Erlang platform which is powering planet-scale telecom solutions for 20+ years. So we're getting pretty much the best from both worlds: minimum friction & smart conventions that eliminate the excessive boilerplate AND highly concurrent EVM (Erlang's Virtual Machine) that makes all the scalability problems vanish. The transition was very smooth - none of Ruby developers we had decided to leave because of Elixir. What is more, we kept recruiting Ruby developers w/o any requirement regarding Elixir proficiency & we still were able to educate them internally in almost no time. Obviously Elixir comes with some more tools in the stack: Credo , Hex , AppSignal (required to properly monitor BEAM apps).

See more
Julia logo

Julia

484
641
166
A high-level, high-performance dynamic programming language for technical computing
484
641
+ 1
166
PROS OF JULIA
  • 24
    Fast Performance and Easy Experimentation
  • 21
    Designed for parallelism and distributed computation
  • 18
    Free and Open Source
  • 17
    Dynamic Type System
  • 16
    Multiple Dispatch
  • 16
    Calling C functions directly
  • 16
    Lisp-like Macros
  • 10
    Powerful Shell-like Capabilities
  • 9
    Jupyter notebook integration
  • 8
    REPL
  • 4
    String handling
  • 4
    Emojis as variable names
  • 3
    Interoperability
CONS OF JULIA
  • 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

related Julia posts

Erlang logo

Erlang

757
722
327
A programming language used to build massively scalable soft real-time systems with requirements on high availability
757
722
+ 1
327
PROS OF ERLANG
  • 60
    Concurrency Support
  • 60
    Real time, distributed applications
  • 56
    Fault tolerance
  • 35
    Soft real-time
  • 31
    Open source
  • 21
    Functional programming
  • 20
    Message passing
  • 15
    Immutable data
  • 13
    Works as expected
  • 5
    Facebook chat uses it at backend
  • 4
    Practical
  • 4
    Knowledgeable community
  • 3
    Bullets included
CONS OF ERLANG
    Be the first to leave a con

    related Erlang posts

    Sebastian Gębski

    Another major decision was to adopt Elixir and Phoenix Framework - the DX (Developer eXperience) is pretty similar to what we know from RoR, but this tech is running on the top of rock-solid Erlang platform which is powering planet-scale telecom solutions for 20+ years. So we're getting pretty much the best from both worlds: minimum friction & smart conventions that eliminate the excessive boilerplate AND highly concurrent EVM (Erlang's Virtual Machine) that makes all the scalability problems vanish. The transition was very smooth - none of Ruby developers we had decided to leave because of Elixir. What is more, we kept recruiting Ruby developers w/o any requirement regarding Elixir proficiency & we still were able to educate them internally in almost no time. Obviously Elixir comes with some more tools in the stack: Credo , Hex , AppSignal (required to properly monitor BEAM apps).

    See more

    Hello everyone, I plan on building a platform that supports 100s of forums out of the box, it would give the user the ability to create forums, where other users can comment, post images, and videos (the size of videos would be limited). Each forum would have the ability to trend. I have been doing a lot of research and I have arrived at Golang and Erlang as the backend languages and PostgreSQL as the DB. Erlang would be used for the routing of chats and messages, while Go would be used to manage the forums. We would also be implementing a one on one chat system like WhatsApp chat, where users can add contacts.

    Please I would like to know if the languages picked are appropriate for this project. Suggestions would be appreciated.

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    Golang logo

    Golang

    15.1K
    13.3K
    3.2K
    An open source programming language that makes it easy to build simple, reliable, and efficient software
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    PROS OF GOLANG
    • 538
      High-performance
    • 392
      Simple, minimal syntax
    • 359
      Fun to write
    • 299
      Easy concurrency support via goroutines
    • 271
      Fast compilation times
    • 193
      Goroutines
    • 179
      Statically linked binaries that are simple to deploy
    • 150
      Simple compile build/run procedures
    • 136
      Backed by google
    • 134
      Great community
    • 52
      Garbage collection built-in
    • 45
      Built-in Testing
    • 43
      Excellent tools - gofmt, godoc etc
    • 39
      Elegant and concise like Python, fast like C
    • 37
      Awesome to Develop
    • 26
      Used for Docker
    • 25
      Flexible interface system
    • 24
      Deploy as executable
    • 24
      Great concurrency pattern
    • 20
      Open-source Integration
    • 17
      Easy to read
    • 17
      Fun to write and so many feature out of the box
    • 16
      Go is God
    • 14
      Its Simple and Heavy duty
    • 14
      Powerful and simple
    • 14
      Easy to deploy
    • 13
      Best language for concurrency
    • 12
      Concurrency
    • 11
      Rich standard library
    • 11
      Safe GOTOs
    • 10
      Clean code, high performance
    • 10
      Easy setup
    • 9
      Simplicity, Concurrency, Performance
    • 9
      High performance
    • 8
      Hassle free deployment
    • 8
      Single binary avoids library dependency issues
    • 7
      Simple, powerful, and great performance
    • 7
      Cross compiling
    • 7
      Used by Giants of the industry
    • 6
      Gofmt
    • 6
      Garbage Collection
    • 5
      Very sophisticated syntax
    • 5
      Excellent tooling
    • 5
      WYSIWYG
    • 4
      Kubernetes written on Go
    • 4
      Widely used
    • 4
      Keep it simple and stupid
    • 2
      No generics
    • 1
      Looks not fancy, but promoting pragmatic idioms
    • 1
      Operator goto
    CONS OF GOLANG
    • 41
      You waste time in plumbing code catching errors
    • 25
      Verbose
    • 23
      Packages and their path dependencies are braindead
    • 15
      Dependency management when working on multiple projects
    • 15
      Google's documentations aren't beginer friendly
    • 10
      Automatic garbage collection overheads
    • 8
      Uncommon syntax
    • 6
      Type system is lacking (no generics, etc)
    • 3
      Collection framework is lacking (list, set, map)
    • 2
      Best programming language

    related Golang posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 42 upvotes · 6.3M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Nick Parsons
    Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 1.9M views

    Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

    We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

    We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

    Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

    #FrameworksFullStack #Languages

    See more
    Kotlin logo

    Kotlin

    12.3K
    10.4K
    645
    Statically typed Programming Language targeting JVM and JavaScript
    12.3K
    10.4K
    + 1
    645
    PROS OF KOTLIN
    • 73
      Interoperable with Java
    • 55
      Functional Programming support
    • 50
      Null Safety
    • 46
      Official Android support
    • 44
      Backed by JetBrains
    • 37
      Concise
    • 36
      Modern Multiplatform Applications
    • 28
      Expressive Syntax
    • 27
      Target to JVM
    • 26
      Coroutines
    • 24
      Open Source
    • 19
      Statically Typed
    • 19
      Practical elegance
    • 17
      Type Inference
    • 17
      Android support
    • 14
      Readable code
    • 13
      Powerful as Scala, simple as Python, plus coroutines <3
    • 12
      Better Java
    • 10
      Pragmatic
    • 9
      Lambda
    • 8
      Target to JavaScript
    • 8
      Expressive DSLs
    • 8
      Better language for android
    • 6
      Used for Android
    • 6
      Less boilerplate code
    • 5
      Fast Programming language
    • 5
      Less code
    • 4
      Friendly community
    • 4
      Functional Programming Language
    • 4
      Less boiler plate code
    • 3
      Official Google Support
    • 3
      Native
    • 2
      Spring
    • 2
      Latest version of Java
    • 1
      Well-compromised featured Java alternative
    • 0
      Well-compromised featured Java alternative
    CONS OF KOTLIN
    • 7
      Java interop makes users write Java in Kotlin
    • 4
      Frequent use of {} keys
    • 2
      Hard to make teams adopt the Kotlin style
    • 2
      Nonullpointer Exception
    • 1
      Friendly community
    • 1
      Slow compiler
    • 1
      No boiler plate code

    related Kotlin posts

    Shivam Bhargava
    AVP - Business at VAYUZ Technologies Pvt. Ltd. · | 22 upvotes · 533.5K views

    Hi Community! Trust everyone is keeping safe. I am exploring the idea of building a #Neobank (App) with end-to-end banking capabilities. In the process of exploring this space, I have come across multiple Apps (N26, Revolut, Monese, etc) and explored their stacks in detail. The confusion remains to be the Backend Tech to be used?

    What would you go with considering all of the languages such as Node.js Java Rails Python are suggested by some person or the other. As a general trend, I have noticed the usage of Node with React on the front or Node with a combination of Kotlin and Swift. Please suggest what would be the right approach!

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    Jakub Olan
    Node.js Software Engineer · | 17 upvotes · 447.3K views

    In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.

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