Elixir (programming language)

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. 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. 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. == Features ==

• Compiles to bytecode for the BEAM virtual machine of Erlang. • 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) • Lazy and async collections with streams • Railway-oriented programming via the with construct • Hygienic metaprogramming by direct access to the abstract syntax tree (AST). 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 • Unicode support and UTF-8 strings == Examples ==

The following examples can be run in an iex shell or saved in a file and run from the command line by typing elixir ''''. 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 Asynchronously reading files with streams: 1..5 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 IO.puts("#{num * 2}") end Asynchronously performing a task: task = Task.async fn -> perform_complex_action() end other_time_consuming_action() Task.await task == See also ==