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Elixir
Elixir
Paradigms	multi-paradigm: functional, concurrent, distributed, process-oriented
Designed by	José Valim
First appeared	25 May 2012; 13 years ago (2012-05-25)[1][2][3]
Stable release	1.19.5[4]  / 9 January 2026; 51 days ago (9 January 2026)
Typing discipline	dynamic, strong
Platform	Erlang
License	Apache License 2.0[5]
Filename extensions	.ex, .exs
Website	elixir-lang.org
Influenced by
Clojure, Erlang, Ruby
Influenced
Gleam, LFE

Elixir is a functional, concurrent, high-level general-purpose programming language that runs on the BEAM virtual machine, which is also used to implement the Erlang programming language.^[6] Elixir builds on top of Erlang and shares the same abstractions for building distributed, fault-tolerant applications. Elixir also provides tooling and an extensible design. The latter is supported by compile-time metaprogramming with macros and polymorphism via protocols.^[7]

The community organizes yearly events in the United States,^[8] Europe,^[9] and Japan,^[10] as well as minor local events and conferences.^[11][12]

José Valim created the Elixir programming language as a research and development project at Plataformatec. His goals were to enable higher extensibility and productivity in the Erlang VM while maintaining compatibility with Erlang's ecosystem.^[13][14]

Elixir is aimed at large-scale sites and apps. It uses features of Ruby, Erlang, and Clojure to develop a high-concurrency and low-latency language. It was designed to handle large data volumes. Elixir is also used in telecommunications, e-commerce, and finance.^[15]

In 2021, the Numerical Elixir effort was announced with the goal of bringing machine learning, neural networks, GPU compilation, data processing, and computational notebooks to the Elixir ecosystem.^[16]

• Compiles to bytecode for the BEAM virtual machine of Erlang.^[7] Full interoperability with Erlang code, without runtime impact.
• Scalability and fault-tolerance, thanks to Erlang's lightweight concurrency mechanisms^[7]
• Built-in tooling for managing dependencies, code compilation, running tests, formatting code, remote debugging and more.
• An interactive REPL inside running programs, including Phoenix web servers, with code reloading and access to internal state
• Everything is an expression^[7]
• Pattern matching^[7] to promote assertive code^[17]
• Type hints for static analysis tools
• Immutable data, with an emphasis, like other functional languages, on recursion and higher-order functions instead of side-effect-based looping
• Shared nothing concurrent programming via message passing (actor model)^[18]
• Lazy and async collections with streams
• Railway-oriented programming via the with construct^[19]
• Hygienic metaprogramming by direct access to the abstract syntax tree (AST).^[7] Libraries often implement small domain-specific languages, such as for databases or testing.
• Code execution at compile time. The Elixir compiler also runs on the BEAM, so modules that are being compiled can immediately run code which has already been compiled.
• Polymorphism via a mechanism called protocols. Dynamic dispatch, as in Clojure, however, without multiple dispatch because Elixir protocols dispatch on a single type.
• Support for documentation via Python-like docstrings in the Markdown formatting language^[7]
• Unicode support and UTF-8 strings

The following examples can be run in an iex shell or saved in a file and run from the command line by typing elixir <filename>.

Classic Hello world example:

iex> IO.puts("Hello World!")
Hello World!

Pipe operator:

iex> "Elixir" |> String.graphemes() |> Enum.frequencies()
%{"E" => 1, "i" => 2, "l" => 1, "r" => 1, "x" => 1}

iex> %{values: 1..5} |> Map.get(:values) |> Enum.map(& &1 * 2)
[2, 4, 6, 8, 10]

iex> %{values: 1..5} |> Map.get(:values) |> Enum.map(& &1 * 2) |> Enum.sum()
30

Pattern matching (a.k.a. destructuring):

iex> %{left: x} = %{left: 5, right: 8}
iex> x
5

iex> {:ok, [_ | rest]} = {:ok, [1, 2, 3]}
iex> rest
[2, 3]

Pattern matching with multiple clauses:

iex> case File.read("path/to/file") do
iex>   {:ok, contents} -> IO.puts("found file: #{contents}")
iex>   {:error, reason} -> IO.puts("missing file: #{reason}")
iex> end

List comprehension:

iex> for n <- 1..5, rem(n, 2) == 1, do: n*n
[1, 9, 25]

Asynchronously reading files with streams:

1..5
|> Task.async_stream(&File.read!("#{&1}.txt"))
|> Stream.filter(fn {:ok, contents} -> String.trim(contents) != "" end)
|> Enum.join("\n")

Multiple function bodies with guards:

def fib(n) when n in [0, 1], do: n
def fib(n), do: fib(n-2) + fib(n-1)

Relational databases with the Ecto library:

schema "weather" do
  field :city     # Defaults to type :string
  field :temp_lo, :integer
  field :temp_hi, :integer
  field :prcp,    :float, default: 0.0
end

Weather |> where(city: "Kraków") |> order_by(:temp_lo) |> limit(10) |> Repo.all

Sequentially spawning a thousand processes:

for num <- 1..1000, do: spawn fn -> IO.puts("#{num * 2}") end

Asynchronously performing a task:

task = Task.async fn -> perform_complex_action() end
other_time_consuming_action()
Task.await task

^{[citation needed]}

• Concurrent computing
• Distributed computing
• Parallel computing

• Simon St. Laurent; J. Eisenberg (22 December 2016). Introducing Elixir: Getting Started in Functional Programming 2nd Edition. O'Reilly Media. ISBN 978-1491956779.
• Sasa Juric (12 January 2019). Elixir in Action 2nd Edition. Manning Publications. ISBN 978-1617295027.