Nim: Efficient, Expressive, and Underrated

April 11, 2026 43 min read Software Development

nimsystems-programmingmetaprogrammingasynccompiledprogramming-languages

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There is a language that gives you Python’s syntax, C’s performance, Lisp’s macro power, and Rust-quality binary output — all in a single compiler with no runtime dependency. Most engineers have never used it. Some have never heard of it. That language is Nim.

Nim is not a research project or a toy. It compiles to C, C++, or JavaScript. The resulting binaries are small, fast, and have no dependency on a Nim runtime. It has shipped in production at companies like Status (the Ethereum client), in the game engine Godot (via GDScript’s design influence), in network tools, CLI utilities, and embedded systems. Nim 2.0 shipped in 2023, marking the language’s first major stability milestone — breaking changes are no longer on the table without strong justification.

This guide is for engineers who already know at least one systems language or Python and want a rigorous, honest understanding of what Nim actually is, how it works, and when it deserves a slot on your shortlist.

1. What Nim Is — And Where It Fits

Nim was created by Andreas Rumpf, with the first public release in 2008 and version 1.0 landing in 2019. The 2.0 release in September 2023 brought a new default memory management model (ORC), improved generics, better JavaScript backend support, and a commitment to long-term API stability.

The design philosophy has three axes: efficiency, expressiveness, and elegance. These are not marketing words — they map to real design choices:

Efficiency: Nim compiles to C and then lets your C compiler (gcc, clang, msvc) do the heavy lifting. You get inlining, autovectorization, link-time optimization, and every other optimization your C compiler provides. Nim does not insert a runtime — there is no JVM, no Node.js, no interpreter. The resulting binary can be statically linked to a single file.
Expressiveness: The metaprogramming system is Nim’s crown jewel. Templates and macros operate on the abstract syntax tree at compile time, letting you build DSLs, async systems, and test frameworks as library code — not special language syntax. The standard async/await you write in Nim is implemented in a Nim library using macros. It is not baked into the compiler.
Elegance: The syntax is Python-inspired. Significant whitespace, optional semicolons, readable identifiers. But the type system is strong and static. This is the combination Python programmers dream about.

How Nim Differs from Python

Python and Nim share surface syntax but are architecturally opposite:

Aspect	Python	Nim
Execution	Interpreted (CPython), bytecode	Compiled to C/machine code
Typing	Dynamic, runtime	Static, compile-time
Memory	GC (reference counting + cyclic GC)	ORC / ARC / refc (compile-time choice)
Startup time	30–100ms typical	<5ms typical
Dependency	Python runtime required	No runtime, single binary
GIL	Yes (CPython)	No
Metaprogramming	Decorators, `__dunder__`	Full AST macros

Python code that runs at “good enough” speed becomes a liability when you need sub-millisecond latency, a statically linked binary for a container, or a program that embeds into a C project. Nim fills that gap without abandoning Python’s readability.

How Nim Differs from Zig

Zig positions itself as a C replacement with explicit allocators and no hidden control flow. Nim and Zig share some goals but diverge philosophically:

Zig has no macros by design — everything is comptime-evaluated code, not AST manipulation. Nim has full macro support.
Zig requires explicit allocators everywhere. Nim’s standard library uses the default allocator internally; you opt into explicit allocation.
Zig targets C-level programmers who want safety guarantees. Nim targets programmers who want Python-level productivity with C-level output.
Zig’s comptime is powerful but operates on values. Nim’s macros operate on the AST, enabling syntactic extension.

Both are excellent for embedded and systems work. Choose Zig if you want maximum control over every allocation. Choose Nim if you want expressive, high-level code that compiles small.

How Nim Differs from Crystal

Crystal is the most direct comparison: Python-like syntax, compiles to native code, static typing. The key differences:

Crystal uses LLVM directly; Nim uses C as an intermediate. Nim’s C backend means you can target environments where LLVM is unavailable or too heavy.
Crystal has Ruby-inspired syntax (not Python). Nim is closer to Python.
Crystal’s metaprogramming is limited to macros over types and methods. Nim’s macros can transform arbitrary syntax.
Crystal compiles only to native binaries. Nim compiles to JavaScript too, enabling code sharing between server and browser.
Nim’s ecosystem is older and has more systems-programming-oriented packages. Crystal skews more toward web services.

2. Core Language

Syntax and Significant Whitespace

Nim uses indentation to delimit blocks — no braces, no begin/end. Blocks are introduced by a colon, and indentation (spaces, not tabs by convention) determines scope.

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# hello.nim
proc greet(name: string): string =
  let greeting = "Hello, " & name & "!"
  return greeting

when isMainModule:
  echo greet("World")

Compile and run:

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nim c -r hello.nim
# Compiles to C, then invokes gcc, then runs the binary

The when isMainModule guard is Nim’s equivalent of Python’s if __name__ == "__main__". It is evaluated at compile time — the block is only included when this file is the main compilation unit.

Variables: `let`, `var`, `const`

Nim has three variable declaration keywords with distinct semantics:

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const Pi = 3.14159          # Compile-time constant — no runtime allocation
let radius = 5.0            # Runtime immutable — assigned once, cannot change
var circumference = 0.0     # Runtime mutable

circumference = 2 * Pi * radius
echo circumference          # 31.4159...

# let x = 10
# x = 20   # Error: cannot assign to 'x', it is immutable

const values are evaluated entirely at compile time. You can write surprisingly complex compile-time computations:

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const
  MaxSize = 1024
  TableSize = MaxSize * 2
  DefaultName = "unnamed"
  Mask = 0xFF_FF_00_00'u32   # Underscores in numeric literals for readability

Type Inference

Nim infers types but you can always annotate explicitly:

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let x = 42            # inferred: int
let y = 3.14          # inferred: float
let s = "hello"       # inferred: string
let b = true          # inferred: bool

# Explicit annotation
let count: int = 0
let ratio: float32 = 1.5
let name: string = "Nim"

Tuples and Named Tuples

Nim tuples are value types (stack-allocated) and support optional field naming:

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# Anonymous tuple
let point = (10, 20)
echo point[0]   # 10
echo point[1]   # 20

# Named tuple — fields accessible by name
let person = (name: "Alice", age: 30)
echo person.name   # Alice
echo person.age    # 30

# Tuple type annotation
type Point = tuple[x: int, y: int]

proc distance(a, b: Point): float =
  let dx = float(b.x - a.x)
  let dy = float(b.y - a.y)
  sqrt(dx*dx + dy*dy)

let origin: Point = (x: 0, y: 0)
let target: Point = (x: 3, y: 4)
echo distance(origin, target)   # 5.0

Object Types

For more complex data structures, use object types:

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type
  Color = enum
    Red, Green, Blue, Alpha

  Pixel = object
    r, g, b: uint8
    a: uint8

  # Ref object — heap-allocated, reference semantics
  Node = ref object
    value: int
    left, right: Node   # Recursive — only possible with ref

proc newPixel(r, g, b: uint8, a: uint8 = 255): Pixel =
  Pixel(r: r, g: g, b: b, a: a)

let px = newPixel(255, 128, 0)
echo px.r   # 255
echo px.a   # 255 (default)

The distinction between object (value type, stack-allocated) and ref object (reference type, heap-allocated) is explicit and meaningful. Python hides this — everything is a reference. Nim makes you choose.

Case Statements and Pattern Matching

Nim’s case is exhaustive (the compiler warns about uncovered branches) and supports ranges and sets:

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proc classify(n: int): string =
  case n
  of 0:
    "zero"
  of 1..9:
    "single digit"
  of 10..99:
    "double digit"
  of 100..999:
    "triple digit"
  else:
    "large"

echo classify(7)    # single digit
echo classify(42)   # double digit
echo classify(1000) # large

Case on enums with exhaustiveness checking:

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type
  Direction = enum
    North, South, East, West

proc opposite(d: Direction): Direction =
  case d
  of North: South
  of South: North
  of East:  West
  of West:  East
  # No `else` needed — compiler verifies all cases are covered
  # Adding a new enum value will cause a compile error here — intentional

Range Types and Distinct Types

Range types constrain a value to a subset of its base type:

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type
  Percentage = range[0..100]
  Port = range[1..65535]

var p: Percentage = 50
# p = 150   # Compile error: value 150 is out of range for type Percentage

proc bindToPort(port: Port) =
  echo "Binding to port ", port

bindToPort(8080)
# bindToPort(0)   # Error: 0 is out of range for type Port

Distinct types create a new type from an existing one with no implicit conversions. This is a zero-cost abstraction for type safety:

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type
  Meters = distinct float
  Seconds = distinct float
  MetersPerSecond = distinct float

proc `+`(a, b: Meters): Meters = Meters(float(a) + float(b))
proc `/`(d: Meters, t: Seconds): MetersPerSecond =
  MetersPerSecond(float(d) / float(t))

let distance = Meters(100.0)
let time = Seconds(9.58)
let speed = distance / time

# let wrong = distance + time  # Type error at compile time!
echo float(speed), " m/s"   # 10.438... m/s

This is the same problem Rust solves with newtypes, but Nim’s syntax is lighter.

3. The Type System

Generics

Nim generics use square brackets and work at compile time — they generate specialized code per type, similar to C++ templates but without the error message horror:

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proc max[T](a, b: T): T =
  if a > b: a else: b

echo max(3, 7)         # 7 — T inferred as int
echo max(3.14, 2.71)   # 3.14 — T inferred as float
echo max("apple", "banana")  # banana — T inferred as string

# Generic container
type Stack[T] = object
  data: seq[T]

proc push[T](s: var Stack[T], item: T) =
  s.data.add(item)

proc pop[T](s: var Stack[T]): T =
  result = s.data[^1]
  s.data.setLen(s.data.len - 1)

proc isEmpty[T](s: Stack[T]): bool =
  s.data.len == 0

var intStack: Stack[int]
intStack.push(1)
intStack.push(2)
intStack.push(3)
echo intStack.pop()   # 3
echo intStack.pop()   # 2

Concepts (Type Classes)

Concepts let you constrain generics to types that satisfy a structural interface — similar to Rust traits or Haskell typeclasses, but defined by what operations the type supports (structural typing):

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type
  Printable = concept x
    echo(x)   # x is Printable if echo(x) compiles

  Addable = concept x, y
    x + y is type(x)   # Addable if + returns same type

proc printAll[T: Printable](items: seq[T]) =
  for item in items:
    echo item

printAll(@[1, 2, 3])
printAll(@["a", "b", "c"])

A more practical concept for a numeric type constraint:

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type
  Number = concept x
    x + x is type(x)
    x - x is type(x)
    x * x is type(x)
    x / x is float

proc average[T: Number](values: seq[T]): float =
  var sum = T(0)
  for v in values:
    sum = sum + v
  result = sum / T(values.len)

echo average(@[1, 2, 3, 4, 5])   # 3.0

Option[T] and Result

Nim’s standard library provides std/options for nullable values:

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import std/options

proc findUser(id: int): Option[string] =
  case id
  of 1: some("Alice")
  of 2: some("Bob")
  else: none(string)

let user = findUser(1)
if user.isSome:
  echo "Found: ", user.get()

# Safer with pattern-style access
let name = findUser(99).get("anonymous")
echo name   # anonymous

# Using map/flatMap style
let upperName = findUser(2).map(proc(s: string): string = s.toUpperAscii())
echo upperName   # Some("BOB")

For error handling, the std/results package (and the popular results Nimble package) provides a Result[T, E] type:

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# Using the results package (nimble install results)
import results

type ParseError = object
  message: string

proc parseInt(s: string): Result[int, ParseError] =
  try:
    ok(s.parseInt())
  except ValueError:
    err(ParseError(message: "Not a valid integer: " & s))

let r1 = parseInt("42")
let r2 = parseInt("not-a-number")

if r1.isOk:
  echo "Parsed: ", r1.value   # 42

case r2.isErr:
of true:
  echo "Error: ", r2.error.message
of false:
  discard

Nim also supports exception-based error handling via try/except/finally/raise, similar to Python. The community is split between exceptions and Result — Result gives you compile-time-enforced error handling, exceptions give you less boilerplate.

Variance and Generics

Nim generics are invariant by default. The type system is nominal for objects and structural for concepts. This avoids common footguns from covariant generics while remaining practical.

4. Memory Management

Memory management is where Nim 2.0 made its most significant change. Understanding the options is essential for writing performant Nim code.

ORC: The Nim 2.0 Default

ORC stands for Ownership, Reference Counting with cycle collection. It is Nim’s default memory management strategy as of version 2.0.

ORC works by:

Tracking object lifetimes through reference counting
Automatically detecting and collecting reference cycles using a separate cycle collector
Enabling move semantics — when a value is moved into a new location, no copy or reference count update is needed

The key advantage over a traditional GC: deterministic destruction. When an object’s reference count hits zero, it is freed immediately — not at some future GC pause. This matters for RAII patterns, file handles, network connections, and real-time systems.

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# --mm:orc is the default in Nim 2.0
# This example demonstrates deterministic cleanup

type
  Resource = ref object
    name: string

proc `=destroy`(r: Resource) =
  echo "Destroying: ", r.name   # Called deterministically when ref count hits 0

proc useResource() =
  let r = Resource(name: "connection-pool")
  echo "Using: ", r.name
  # r goes out of scope here — destructor called immediately

useResource()
# Output:
# Using: connection-pool
# Destroying: connection-pool

ARC vs ORC vs refc

Nim gives you compile-time control over the memory model:

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# ARC: Automatic Reference Counting, no cycle collection
nim c --mm:arc myprogram.nim

# ORC: ARC + cycle collection (default in Nim 2.0)
nim c --mm:orc myprogram.nim

# refc: Traditional tracing GC (Nim 1.x default, still available)
nim c --mm:refc myprogram.nim

# No GC at all — for bare-metal/embedded
nim c --mm:none myprogram.nim

When to use each:

ORC (default): For most programs. Handles cycles, deterministic, low overhead.
ARC: When you know there are no reference cycles and want slightly less overhead. The compiler will warn you about potential cycles.
refc: Legacy code, or if you need the older behavior. Not recommended for new code.
none: Embedded systems, kernels, or when you want 100% manual control. You handle all allocation manually.

Manual Memory Management

Even with ORC, you can drop to manual allocation for hot paths:

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import std/system

# Manual allocation
let size = 1024
let buf = cast[ptr UncheckedArray[byte]](alloc(size))

# Use the buffer
for i in 0..<size:
  buf[i] = byte(i mod 256)

echo buf[100]   # 100

# Must manually free
dealloc(buf)

For arrays and objects without the GC:

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# Allocate a single object manually
let node = cast[ptr int](alloc0(sizeof(int)))
node[] = 42
echo node[]   # 42
dealloc(node)

# Using createShared/freeShared for thread-safe allocation
import std/system
let shared = createShared(int)
shared[] = 99
freeShared(shared)

Comparison to Rust’s Borrow Checker

Rust enforces memory safety through the borrow checker at compile time — no reference counting overhead at all. A single owner, explicit borrows, lifetimes that the compiler tracks. If it compiles, there are no use-after-free, no data races, no double-free.

Nim’s ORC takes a different approach: reference counting with runtime cycle detection. This is:

Less restrictive to write: No lifetime annotations, no borrow checker fights. Code that would be awkward in Rust (self-referential structs, complex graph structures) is natural in Nim.
Slightly more overhead: Each reference-counted object pays for the atomic increment/decrement (though Nim’s --mm:arc uses non-atomic counting in single-threaded code). Cycle detection adds a small periodic cost.
Less provably safe: The compiler does not prove the absence of memory errors at compile time the way Rust does. You can still write unsafe Nim.

For most programs, the difference in overhead is negligible. For extremely allocation-heavy hot paths or programs where you need formal memory safety guarantees, Rust’s model is stronger. For everything else, Nim’s model is significantly more ergonomic.

5. Metaprogramming — Nim’s Killer Feature

Nim’s metaprogramming system is the most compelling reason to choose it over alternatives. Understanding it requires distinguishing between three levels:

Generic code — type-parameterized, standard in most statically-typed languages
Templates — hygienic code substitution that runs at compile time
Macros — full AST manipulation at compile time, can generate arbitrary code

Templates

A template is a compile-time code substitution. Unlike C macros, Nim templates are hygienic — they respect scoping, and names in the template body don’t accidentally capture names from the call site.

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# A simple template that measures execution time
import std/times

template benchmark(name: string, code: untyped): untyped =
  let start = now()
  code
  let elapsed = now() - start
  echo name, ": ", elapsed.inMilliseconds(), "ms"

# Usage — looks like a built-in language feature
benchmark("sorting"):
  var data = @[5, 3, 1, 4, 2]
  data.sort()
  echo data

Templates can also define operators and control structures:

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template `not in`[T](item: T, collection: openArray[T]): bool =
  not (item in collection)

let fruits = @["apple", "banana", "cherry"]
echo "mango" not in fruits   # true
echo "apple" not in fruits   # false

# Template for retry logic
template retry(attempts: int, code: untyped): bool =
  var success = false
  for attempt in 1..attempts:
    try:
      code
      success = true
      break
    except:
      if attempt == attempts:
        echo "All ", attempts, " attempts failed"
  success

Macros: Full AST Manipulation

Macros in Nim receive the abstract syntax tree of their arguments and return a new AST. This is more powerful than C preprocessor macros (text substitution) and comparable to Lisp macros.

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import std/macros

# A macro that prints what expression is being evaluated
macro debugExpr(expr: untyped): untyped =
  let exprStr = toStrLit(expr)   # Convert AST back to string
  result = quote do:
    let val = `expr`
    echo `exprStr`, " = ", val
    val

let x = 5
let y = 10
debugExpr(x + y)
# Output: x + y = 15

dumpAstGen — Exploring the AST

When writing macros, dumpAstGen is your best friend. It shows the AST representation of any code:

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import std/macros

dumpAstGen:
  let x = 42
  if x > 0:
    echo "positive"

This outputs the Nim AST nodes, which you can use as a template when constructing ASTs in macros. The output looks like:

StmtList
  LetSection
    IdentDefs
      Ident "x"
      Empty
      IntLit 42
  IfStmt
    ElifBranch
      Infix
        Ident ">"
        Ident "x"
        IntLit 0
      StmtList
        Call
          Ident "echo"
          StrLit "positive"

quote do: — Ergonomic AST Construction

The quote do: block lets you write Nim syntax directly as AST construction, with backtick interpolation for splicing in values:

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import std/macros

macro memoize(fn: untyped): untyped =
  # fn is the AST of the function definition
  let fnName = fn.name
  let cacheIdent = ident(fnName.strVal & "Cache")

  result = quote do:
    var `cacheIdent` {.global.} = initTable[auto, auto]()
    `fn`
    # Wrapping logic would go here in a real implementation

Practical Macro Example: A Simple Test Framework

Here is a simplified test framework built entirely using macros — no compiler magic needed:

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import std/macros, std/strformat

var testsPassed = 0
var testsFailed = 0

macro test(description: string, body: untyped): untyped =
  result = quote do:
    block:
      try:
        `body`
        inc testsPassed
        echo fmt"  PASS: {`description`}"
      except AssertionDefect as e:
        inc testsFailed
        echo fmt"  FAIL: {`description`}"
        echo fmt"    {e.msg}"
      except Exception as e:
        inc testsFailed
        echo fmt"  ERROR: {`description`}: {e.msg}"

macro suite(name: string, body: untyped): untyped =
  result = quote do:
    echo "Suite: ", `name`
    `body`
    echo fmt"Results: {testsPassed} passed, {testsFailed} failed"

# Usage:
suite("String operations"):
  test("concatenation"):
    assert "hello" & " " & "world" == "hello world"

  test("length"):
    assert "nim".len == 3

  test("intentional failure"):
    assert 1 == 2, "one should equal two"

Macro Example: A Simple DSL for HTTP Routes

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import std/macros, std/tables, std/strutils

type
  HttpMethod = enum GET, POST, PUT, DELETE
  Handler = proc(path: string): string

var routes = initTable[string, Handler]()

macro route(meth: HttpMethod, path: string, body: untyped): untyped =
  let handlerName = ident("handler_" & path.strVal.replace("/", "_").replace("-", "_"))
  result = quote do:
    proc `handlerName`(reqPath: string): string =
      `body`
    routes[`path`] = `handlerName`

# Usage looks like a declarative DSL
route(GET, "/health"):
  "OK"

route(GET, "/version"):
  "v2.0.0"

route(POST, "/echo"):
  reqPath   # In a real impl, would access request body

How Nim Macros Compare to Rust Proc Macros and Lisp Macros

vs Rust proc macros: Rust proc macros operate on a TokenStream — a flat stream of lexical tokens. You parse them yourself, manipulate them, and return a new TokenStream. Nim macros operate on a typed, structured AST. Nim’s approach is more ergonomic: the quote do: syntax lets you write Nim code directly rather than constructing token streams manually. Rust’s macro system is more isolated (proc macros are separate crates in a special compilation mode).

vs Lisp macros: Lisp macros are the gold standard — because Lisp’s syntax is its AST (s-expressions), macro input and output are identical in form. Nim’s AST is richer than s-expressions (it has typed nodes for if-statements, loops, etc.) which makes some transformations more structured but also more verbose. Lisp macros require no separate compilation phase distinction — everything is one pass. Nim macros run in a distinct compile-time phase, which is cleaner for most use cases but prevents some of the more wild Lisp-style code-walking.

The practical upshot: Nim macros are the most ergonomic AST-level metaprogramming in any compiled, statically-typed language that ships today.

6. Async/Await

Nim’s async system is one of the most interesting implementations in any language: it is implemented entirely as a library using macros, not baked into the compiler. The async and await keywords you use are Nim macros that transform your sequential-looking code into a state machine.

Basic Async with asyncdispatch

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import std/asyncdispatch, std/asyncnet, std/strutils

proc fetchPage(host: string, path: string): Future[string] {.async.} =
  let socket = await asyncnet.dial(host, Port(80))
  await socket.send("GET " & path & " HTTP/1.0\r\nHost: " & host & "\r\n\r\n")
  result = await socket.recvAll()
  socket.close()

proc main() {.async.} =
  let page = await fetchPage("example.com", "/")
  echo page[0..200]

waitFor main()

The {.async.} pragma triggers the async macro transformation. await suspends the current coroutine and returns control to the event loop.

Future[T] and asyncCheck

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import std/asyncdispatch, std/asynchttpclient

proc downloadUrls(urls: seq[string]) {.async.} =
  let client = newAsyncHttpClient()
  defer: client.close()

  # Launch all requests concurrently
  var futures: seq[Future[AsyncResponse]]
  for url in urls:
    futures.add(client.get(url))

  # Wait for all to complete
  let responses = await all(futures)

  for i, resp in responses:
    echo urls[i], " -> ", resp.status

proc main() {.async.} =
  await downloadUrls(@[
    "https://httpbin.org/get",
    "https://httpbin.org/status/200",
  ])

waitFor main()

asyncCheck runs a Future without awaiting it, logging errors if they occur:

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import std/asyncdispatch

proc backgroundWork() {.async.} =
  await sleepAsync(1000)
  echo "Background task done"

proc main() {.async.} =
  asyncCheck backgroundWork()   # Fire and forget
  echo "Continuing immediately..."
  await sleepAsync(1500)         # Wait long enough for background to finish

waitFor main()

Async HTTP Client Example

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import std/asyncdispatch, std/asynchttpclient, std/json, std/strformat

type
  GithubUser = object
    login: string
    name: string
    publicRepos: int

proc getGithubUser(username: string): Future[GithubUser] {.async.} =
  let client = newAsyncHttpClient()
  client.headers = newHttpHeaders({"User-Agent": "nim-example"})
  defer: client.close()

  let response = await client.getContent(
    fmt"https://api.github.com/users/{username}"
  )
  let data = parseJson(response)

  result = GithubUser(
    login: data["login"].getStr(),
    name: data["name"].getStr(""),
    publicRepos: data["public_repos"].getInt()
  )

proc main() {.async.} =
  let user = await getGithubUser("nim-lang")
  echo fmt"Login: {user.login}"
  echo fmt"Name: {user.name}"
  echo fmt"Public repos: {user.publicRepos}"

waitFor main()

How the Async Macro Works

When you write:

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proc myProc(): Future[string] {.async.} =
  let x = await someOtherFuture()
  return x & " done"

The macro transforms this into roughly:

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proc myProc(): Future[string] =
  var retFuture = newFuture[string]("myProc")

  proc continuation(someOtherFuturePar: Future[string]) {.closure.} =
    if someOtherFuturePar.failed:
      retFuture.fail(someOtherFuturePar.error)
      return
    let x = someOtherFuturePar.read()
    retFuture.complete(x & " done")

  let fut = someOtherFuture()
  fut.addCallback(continuation)
  return retFuture

This is callback-based concurrency wrapped in a sequential syntax — identical to what Node.js, Python’s asyncio, and Rust’s async/await do internally. The difference is that in Nim, this transformation is in the standard library as a macro, not a language primitive. You could write a different async runtime (and people have).

Chronos: The Modern Async Alternative

chronos is a third-party async library used by Status (the Ethereum client team) that addresses several limitations of asyncdispatch:

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nimble install chronos

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import chronos, chronos/apps/http/httpclient

proc fetchJson(url: string): Future[string] {.async.} =
  let session = HttpSessionRef.new()
  defer: await session.closeWait()

  let response = await session.fetch(parseUri(url))
  return string.fromBytes(response.data)

proc main() {.async.} =
  let data = await fetchJson("https://httpbin.org/json")
  echo data

waitFor(main())

Key differences from asyncdispatch:

Better cancellation support
Stricter Future semantics
Better suited for long-running production services
Used by nimbus-eth2 (Ethereum consensus client) in production

7. Compilation to C and the Benefits

The Compilation Pipeline

.nim source
     ↓  nim compiler (semantic analysis, macro expansion, code gen)
.c source files  (in ~/.cache/nim/ or nimcache/)
     ↓  C compiler (gcc, clang, msvc, tcc)
native binary / .o files / .js

This two-stage pipeline is a feature, not a limitation:

Portability: If a C compiler exists for a target, Nim can target it. This includes RISC-V microcontrollers, WebAssembly via Emscripten, old MIPS routers, and anything else with a C99 compiler.
Optimization: The C compiler performs all its optimizations on the generated C. Link-time optimization, PGO, and vectorization all work.
Interoperability: The generated C can be inspected, audited, or linked with other C code without any special FFI machinery.
Trust: On security-sensitive platforms, some organizations require C code review. Nim generates readable C that can be reviewed.

Compile Commands

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# Compile to binary (uses gcc by default)
nim c myprogram.nim

# Compile and run immediately
nim c -r myprogram.nim

# Release build (enables optimizations, disables assertions)
nim c -d:release myprogram.nim

# Danger mode (disables all safety checks — absolute maximum performance)
nim c -d:danger myprogram.nim

# Compile to C++ (for C++ interop)
nim cpp myprogram.nim

# Compile to JavaScript
nim js myprogram.nim

# Cross-compile for arm64 Linux (from x86_64)
nim c --cpu:arm64 --os:linux --cc:gcc \
  --arm64.linux.gcc.exe:aarch64-linux-gnu-gcc \
  --arm64.linux.gcc.linkerexe:aarch64-linux-gnu-gcc \
  myprogram.nim

# Show the generated C code location
nim c --nimcache:/tmp/nimcache myprogram.nim
ls /tmp/nimcache/

Linking with C Libraries

Nim makes C interop frictionless. Use pragmas to declare C functions directly:

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# Linking with a C library — no .h file needed for simple bindings
proc c_printf(fmt: cstring): cint {.importc: "printf", header: "<stdio.h>", varargs.}
proc c_strlen(s: cstring): csize_t {.importc: "strlen", header: "<string.h>".}

let msg = "Hello from C!\n"
discard c_printf(msg)
echo c_strlen(msg)   # 15

For a complete library binding example — wrapping SQLite:

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# sqlite3 wrapper (simplified)
{.passL: "-lsqlite3".}

type
  Sqlite3 = ptr object
  Sqlite3Stmt = ptr object

const SQLITE_OK = 0
const SQLITE_ROW = 100

proc sqlite3_open(filename: cstring, ppDb: ptr Sqlite3): cint
  {.importc, header: "<sqlite3.h>".}

proc sqlite3_close(db: Sqlite3): cint
  {.importc, header: "<sqlite3.h>".}

proc sqlite3_exec(
  db: Sqlite3,
  sql: cstring,
  callback: pointer,
  arg: pointer,
  errmsg: ptr cstring
): cint {.importc, header: "<sqlite3.h>".}

proc sqlite3_prepare_v2(
  db: Sqlite3,
  sql: cstring,
  nBytes: cint,
  ppStmt: ptr Sqlite3Stmt,
  pzTail: ptr cstring
): cint {.importc, header: "<sqlite3.h>".}

proc sqlite3_step(stmt: Sqlite3Stmt): cint
  {.importc, header: "<sqlite3.h>".}

proc sqlite3_column_text(stmt: Sqlite3Stmt, col: cint): cstring
  {.importc, header: "<sqlite3.h>".}

proc sqlite3_finalize(stmt: Sqlite3Stmt): cint
  {.importc, header: "<sqlite3.h>".}

# Usage
proc queryDb(dbPath: string, sql: string) =
  var db: Sqlite3
  if sqlite3_open(dbPath, addr db) != SQLITE_OK:
    echo "Failed to open database"
    return
  defer: discard sqlite3_close(db)

  var stmt: Sqlite3Stmt
  var tail: cstring
  discard sqlite3_prepare_v2(db, sql, -1, addr stmt, addr tail)
  defer: discard sqlite3_finalize(stmt)

  while sqlite3_step(stmt) == SQLITE_ROW:
    echo sqlite3_column_text(stmt, 0)

Inline C with

When you need to drop to raw C for a specific operation:

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proc getCPUCycles(): uint64 =
  {.emit: """
    #ifdef _MSC_VER
      `result` = __rdtsc();
    #else
      uint32_t lo, hi;
      asm volatile ("rdtsc" : "=a"(lo), "=d"(hi));
      `result` = ((uint64_t)hi << 32) | lo;
    #endif
  """.}

echo getCPUCycles()

The backtick syntax inside {.emit.} interpolates Nim variables into the C code. result is Nim’s implicit return variable.

Header-Only Declarations

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# Import an entire C struct
type
  TimeSpec {.importc: "struct timespec", header: "<time.h>".} = object
    tv_sec: clong
    tv_nsec: clong

proc clock_gettime(clkId: cint, tp: ptr TimeSpec): cint
  {.importc, header: "<time.h>".}

const CLOCK_MONOTONIC = 1.cint

var ts: TimeSpec
discard clock_gettime(CLOCK_MONOTONIC, addr ts)
echo "Seconds: ", ts.tv_sec
echo "Nanoseconds: ", ts.tv_nsec

8. The Standard Library

Nim’s standard library (std/) covers most day-to-day needs. Here is a practical tour of the modules you will use most.

std/strutils — String Operations

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import std/strutils

let s = "  Hello, World!  "

echo s.strip()                     # "Hello, World!"
echo s.toLowerAscii()              # "  hello, world!  "
echo s.toUpperAscii()              # "  HELLO, WORLD!  "
echo s.contains("World")           # true
echo s.replace("World", "Nim")     # "  Hello, Nim!  "
echo s.split(",")                  # @["  Hello", " World!  "]
echo "42".parseInt()               # 42
echo "3.14".parseFloat()           # 3.14
echo 255.toHex()                   # "FF"
echo "  ".isEmptyOrWhitespace()    # true
echo "hello world".capitalizeAscii()  # "Hello world"

# Joining
let parts = @["one", "two", "three"]
echo parts.join(", ")    # "one, two, three"
echo parts.join(" | ")   # "one | two | three"

# Checking content
echo "nim123".allCharsInSet({'a'..'z', '0'..'9'})   # true
echo "Nim".startsWith("Ni")    # true
echo "Nim".endsWith("im")      # true

std/sequtils — Sequence Operations

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import std/sequtils

let nums = @[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# Functional operations
echo nums.filter(proc(x: int): bool = x mod 2 == 0)
# @[2, 4, 6, 8, 10]

echo nums.map(proc(x: int): int = x * x)
# @[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

echo nums.foldl(a + b)          # 55 (sum)
echo nums.foldl(a * b)          # 3628800 (product)

# Using sugar for lambda syntax
import std/sugar
echo nums.filter(x => x > 5)   # @[6, 7, 8, 9, 10]
echo nums.map(x => x * 2)      # @[2, 4, 6, 8, 10, 12, 14, 16, 18, 20]

# Other useful functions
echo nums.any(x => x > 9)      # true
echo nums.all(x => x > 0)      # true
echo nums.count(x => x mod 2 == 0)  # 5

let nested = @[@[1, 2], @[3, 4], @[5, 6]]
echo nested.concat()            # @[1, 2, 3, 4, 5, 6]

echo toSeq(1..5)                # @[1, 2, 3, 4, 5]
echo zip(@[1,2,3], @["a","b","c"])  # @[(1, "a"), (2, "b"), (3, "c")]

std/tables — Hash Maps

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import std/tables

# Table[K, V] — regular hash table
var scores = initTable[string, int]()
scores["alice"] = 95
scores["bob"] = 87
scores["carol"] = 92

echo scores["alice"]              # 95
echo scores.getOrDefault("dave", 0)  # 0

# Iterate
for name, score in scores:
  echo name, ": ", score

# OrderedTable preserves insertion order
var ordered = initOrderedTable[string, int]()
ordered["first"] = 1
ordered["second"] = 2
ordered["third"] = 3

# CountTable for frequency counting
import std/strutils
let words = "the quick brown fox jumps over the lazy dog the".split(" ")
var freq = toCountTable(words)
echo freq["the"]    # 3
freq.sort()
echo freq.largest() # ("the", 3)

std/sets — Hash Sets

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import std/sets

var s1 = toHashSet([1, 2, 3, 4, 5])
var s2 = toHashSet([3, 4, 5, 6, 7])

echo s1 * s2    # Intersection: {3, 4, 5}
echo s1 + s2    # Union: {1, 2, 3, 4, 5, 6, 7}
echo s1 - s2    # Difference: {1, 2}

echo 3 in s1    # true
echo 6 in s1    # false

s1.incl(6)
s1.excl(1)
echo s1    # {2, 3, 4, 5, 6}

std/json — JSON Parsing and Generation

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import std/json

# Parsing
let jsonStr = """
{
  "name": "Nim",
  "version": 2,
  "features": ["fast", "expressive", "metaprogramming"],
  "stable": true,
  "maintainer": {"name": "Andreas Rumpf", "active": true}
}
"""

let data = parseJson(jsonStr)
echo data["name"].getStr()                     # Nim
echo data["version"].getInt()                  # 2
echo data["features"][0].getStr()              # fast
echo data["stable"].getBool()                  # true
echo data["maintainer"]["name"].getStr()       # Andreas Rumpf

# Building JSON
let obj = %*{
  "host": "localhost",
  "port": 8080,
  "debug": false,
  "tags": ["web", "api"]
}
echo obj.pretty()
echo obj["port"].getInt()   # 8080

# Serialization with json_serialization (via jsony package or std)
import std/json

type Config = object
  host: string
  port: int
  debug: bool

proc toConfig(j: JsonNode): Config =
  Config(
    host: j["host"].getStr("localhost"),
    port: j["port"].getInt(8080),
    debug: j["debug"].getBool(false)
  )

let cfg = toConfig(obj)
echo cfg.host   # localhost
echo cfg.port   # 8080

std/strformat — Format Strings

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import std/strformat

let name = "Nim"
let version = 2.0
let fast = true

# f-string style (fmt prefix)
echo fmt"Language: {name}"
echo fmt"Version: {version:.1f}"
echo fmt"Is fast: {fast}"
echo fmt"Hex: {255:#x}"
echo fmt"Padded: {name:>10}"   # Right-aligned in 10 chars
echo fmt"Pi: {3.14159:.2f}"   # Pi: 3.14

# Multi-line format
let report = fmt"""
  Language: {name}
  Version: {version}
  Performance: {"excellent"}
"""
echo report

std/os — File System and Process

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import std/os, std/paths

# Path manipulation
let p = "/home/user/documents/report.txt"
echo p.splitFile()           # (dir: "/home/user/documents", name: "report", ext: ".txt")
echo p.parentDir()           # /home/user/documents
echo p.extractFilename()     # report.txt
echo p.changeFileExt(".pdf") # /home/user/documents/report.pdf

# Directory operations
for entry in walkDir("/tmp"):
  echo entry.kind, ": ", entry.path

for f in walkFiles("/tmp/*.log"):
  echo f

# Environment
echo getEnv("HOME", "/root")
echo getCurrentDir()

# Process
let (output, exitCode) = gorgeEx("echo hello")
echo output    # hello
echo exitCode  # 0

std/re — Regular Expressions

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import std/re

let text = "The price is $19.99 and the discount is $5.00"

# Match
if text =~ re"(\$[\d.]+)":
  echo matches[0]   # $19.99

# Find all
for m in findAll(text, re"\$[\d.]+"):
  echo m   # $19.99, then $5.00

# Replace
echo text.replace(re"\$[\d.]+", "PRICE")
# "The price is PRICE and the discount is PRICE"

# Split
echo "one,two,,three".split(re",+")   # @["one", "two", "three"]

9. Nimble Package Manager

Nimble is Nim’s package manager — similar to pip or cargo but simpler.

Basic Commands

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# Install a package globally
nimble install jester

# Install a specific version
nimble install jester@0.5.0

# Update all packages
nimble update

# Search for packages
nimble search web

# List installed packages
nimble list --installed

# Create a new project
nimble init myproject
cd myproject
nimble build
nimble run
nimble test

.nimble File

A .nimble file defines a package, its dependencies, and its tasks:

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# myproject.nimble
version = "0.1.0"
author = "Your Name"
description = "A sample Nim project"
license = "MIT"

# Runtime dependencies
requires "nim >= 2.0.0"
requires "jester >= 0.5.0"
requires "norm >= 2.5.0"

# Dev dependencies (not installed by users of your library)
when defined(dev):
  requires "unittest2 >= 0.0.4"

# Custom tasks
task build_release, "Build release binary":
  exec "nim c -d:release -o:bin/myproject src/myproject.nim"

task docker, "Build Docker image":
  exec "docker build -t myproject:latest ."

task lint, "Run linter":
  exec "nim check src/myproject.nim"

Key Ecosystem Packages

Jester — Web framework (Sinatra/Flask-style):

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import jester

router myRouter:
  get "/":
    resp "Hello from Nim!"

  get "/hello/@name":
    resp "Hello, " & @"name" & "!"

  post "/data":
    let body = request.body
    resp Http200, body

let settings = newSettings(port = Port(8080))
var jester = initJester(myRouter, settings = settings)
jester.serve()

norm — ORM for SQLite and PostgreSQL:

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import norm/sqlite

type User {.tableName: "users".} = object
  id {.pk, autoIncrement.}: int
  name: string
  email: string
  active: bool

withDb(SqliteDb.init("mydb.sqlite3")):
  db.createTables(User())

  # Insert
  var user = User(name: "Alice", email: "alice@example.com", active: true)
  db.insert(user)
  echo user.id    # 1 (auto-assigned)

  # Query
  let users = db.selectAll(User())
  for u in users:
    echo u.name, ": ", u.email

  # Conditional query
  var activeUsers: seq[User]
  db.select(activeUsers, "active = ?", true)

nimpy — Python interop (call Python from Nim and vice versa):

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# Call Python from Nim
import nimpy

let np = pyImport("numpy")
let arr = np.array(@[1.0, 2.0, 3.0, 4.0, 5.0])
let mean = arr.mean()
echo mean.to(float)   # 3.0

let pd = pyImport("pandas")
let df = pd.DataFrame({"a": @[1,2,3], "b": @[4,5,6]}.toTable)
echo df.describe().to(string)

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# Call Nim from Python — compile as a shared library
import nimpy

proc addNumbers(a, b: int): int {.exportpy.} =
  a + b

proc greet(name: string): string {.exportpy.} =
  "Hello from Nim, " & name & "!"

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nim c --app:lib --out:mynim.so mynim.nim

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# Python side
import mynim
print(mynim.addNumbers(3, 4))   # 7
print(mynim.greet("World"))     # Hello from Nim, World!

pixie — 2D graphics:

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import pixie

let image = newImage(200, 200)
image.fill(rgba(255, 255, 255, 255))

let ctx = image.newContext()
ctx.fillStyle = rgba(0, 0, 255, 255)
ctx.fillRect(rect(50, 50, 100, 100))

ctx.fillStyle = rgba(255, 0, 0, 200)
ctx.fillCircle(circle(vec2(100, 100), 40))

image.writeFile("output.png")

10. Real-World Use Cases and Performance

Where Nim Is Deployed

Status/Nimbus — Status.im built their Ethereum 2.0 consensus client (nimbus-eth2) entirely in Nim. It is one of the four production Ethereum consensus clients and handles billions of dollars in staked ETH. The choice was deliberate: Nim’s ability to compile to a small binary with deterministic memory behavior is critical for validators running on resource-constrained hardware.

Fauna (formerly) — Used Nim for latency-sensitive backend services where GC pauses were unacceptable.

Game tooling — Several game studios use Nim for build tooling, asset processors, and scripting layers where they need C extension compatibility without C’s ergonomic friction.

CLI tools — Nim produces self-contained binaries with fast startup, making it competitive with Go for CLI tools. A typical Nim CLI binary is 500KB–2MB, starts in <10ms, and has no external runtime dependency.

Performance Characteristics

A realistic mental model:

Raw performance ceiling:
  C/C++/Zig    ≈ 1.0x  (baseline)
  Nim          ≈ 1.0x–1.1x  (equivalent to C, sometimes slightly behind due to abstractions)
  Rust         ≈ 1.0x–1.05x
  Go           ≈ 1.5x–2x slower (GC pauses, less optimization)
  Java/JVM     ≈ 1.5x–3x slower (JIT warms up, then fast)
  Python       ≈ 50x–100x slower (CPython)
  PyPy         ≈ 5x–15x slower than C

Startup time:
  Nim binary   <5ms
  Go binary    5–20ms
  JVM          100–500ms
  Python       30–100ms

Binary size (hello world, statically linked):
  Nim          ~250KB (with musl)
  Go           ~1.5MB
  Rust         ~300KB (with musl, optimized)
  C            ~15KB

Nim can approach C performance because:

The compiler generates C that a mature C compiler optimizes
--mm:arc eliminates reference counting on non-aliased values
{.inline.} pragma for hot paths
Value types (objects, not ref objects) avoid heap allocation

Benchmark: CPU-bound Task (Fibonacci)

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# fib.nim — run with: nim c -d:release -r fib.nim
proc fib(n: int): int =
  if n <= 1: n
  else: fib(n-1) + fib(n-2)

import std/times
let start = cpuTime()
echo fib(42)
echo "Time: ", (cpuTime() - start) * 1000, "ms"

On the same machine, the equivalent Python code is typically 50–80x slower. The equivalent Go code is within 2x. Rust is roughly equivalent.

Scripting-Heavy Workflows

Nim’s strongest use case against Python is scripting that needs speed. Consider a log processing tool:

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# logparser.nim
import std/strutils, std/sequtils, std/tables, std/os, std/times

type LogEntry = object
  timestamp: DateTime
  level: string
  message: string

proc parseLine(line: string): LogEntry =
  let parts = line.split(" ", maxsplit=3)
  if parts.len < 4:
    return LogEntry(level: "UNKNOWN", message: line)
  LogEntry(
    timestamp: parse(parts[0] & " " & parts[1], "yyyy-MM-dd HH:mm:ss"),
    level: parts[2],
    message: parts[3]
  )

proc analyzeLog(path: string) =
  var levelCounts = initCountTable[string]()
  var errorMessages: seq[string]

  for line in lines(path):
    if line.isEmptyOrWhitespace: continue
    let entry = parseLine(line)
    levelCounts.inc(entry.level)
    if entry.level == "ERROR":
      errorMessages.add(entry.message)

  echo "Log analysis for: ", path
  for level, count in levelCounts:
    echo "  ", level, ": ", count
  echo "\nFirst 5 errors:"
  for msg in errorMessages[0..min(4, errorMessages.high)]:
    echo "  ", msg

when isMainModule:
  if paramCount() < 1:
    echo "Usage: logparser <logfile>"
    quit(1)
  analyzeLog(paramStr(1))

This processes a 1GB log file in roughly the same time as an equivalent Go program, and 20–30x faster than Python.

11. Honest Assessment

Community Size

Nim’s community is small. The GitHub repository for the Nim compiler has around 16,000 stars — compared to Go’s 120,000, Rust’s 95,000, or Python’s 60,000. The Nim forum is active but thin. The Discord server has a few thousand members.

This matters practically:

Fewer Stack Overflow answers — you will hit problems that require reading source code or asking in Discord/forum
Fewer blog posts and tutorials — learning resources beyond the official documentation are sparse
Fewer library maintainers — some packages are maintained by one person

The flip side: the community is experienced and responsive. Questions get answered. The compiler team is reachable. Bug reports get triaged. For an open-source project of this size, the responsiveness is unusually good.

Ecosystem Gaps

Compared to Python: the gap is large. Python has decades of libraries for every conceivable domain. Machine learning, scientific computing, data analysis, image processing, NLP — Python’s ecosystem here is unmatched. Nim can call Python libraries via nimpy, which is a practical workaround but not a replacement.

Compared to Rust: Rust’s crates.io has 140,000+ packages. Nim’s Nimble has roughly 2,000. Many categories that Rust covers well (async runtimes, web frameworks, cryptography, database drivers) have Nim equivalents but fewer options.

Compared to Go: Go’s ecosystem for cloud-native tooling (Kubernetes clients, gRPC, cloud SDKs) is vastly deeper. Nim does not have first-class cloud SDK support.

The Nim 2.0 Stability Milestone

Nim 1.x had a reputation for occasional breaking changes and rough edges in the module system. Nim 2.0 addressed this by:

Making ORC the default (replacing the older reference-counting GC)
Stabilizing the module system import rules
Cleaning up the generic type resolution
Improving error messages
Committing to backward compatibility for 2.x

For production use, 2.0 is the first release where “we’ll upgrade when there’s a Nim 3.0” is a comfortable statement rather than a gamble. Before 2.0, some teams on Nim 1.6 were hesitant to upgrade because of breakage. That hesitation is largely gone.

Where Nim Genuinely Wins

Scripting that needs speed: You have a Python script that processes large files or does CPU-heavy work. Rewriting it in Nim gets you near-C performance with Python-like readability. The rewrite is smaller than the equivalent Rust or C++ rewrite.

DSL authoring: If you need an embedded domain-specific language — a configuration format, a query language, a test DSL — Nim’s macro system lets you build it as a library without forking the compiler or writing a parser. This is the use case where Nim genuinely has no peer among compiled languages.

C interop without FFI friction: Wrapping a C library in Nim is significantly less ceremony than doing the same in Rust or Go. The {.importc.} pragma, {.header.} pragma, and {.emit.} escape hatch give you a gradual path from pure C to pure Nim.

Single-binary deployment: Nim produces small, self-contained binaries. No runtime, no JVM, no Node. For CLI tools, edge deployments, and container images, this matters.

Embedded and constrained environments: --mm:none gives you a language with Python-like syntax and zero runtime overhead — appropriate for microcontrollers and kernels.

Prototyping with a performance ceiling: Write Python-style code first. When it needs to be fast, add type annotations and compile. The transition is smaller than between Python and Rust.

Where Nim Loses

Hiring: Finding engineers who know Nim is extremely difficult. For team projects, this is often the decisive factor. Go, Python, TypeScript, and Rust all have much larger hiring pools.

Tooling maturity: The Nim language server (nimlangserver) works but has rough edges compared to rust-analyzer or gopls. IDE support in VS Code and JetBrains is functional but not polished. Debugger integration requires more setup than Go or Python.

Library breadth: For data science, machine learning, cloud infrastructure, and mobile — Nim is not the right choice. You will spend time building or porting what already exists in Python or Go.

Error messages: Nim’s compiler error messages have improved substantially in 2.0 but still lag behind Rust’s famously helpful errors. Macro-heavy code produces errors that are genuinely hard to interpret.

Async ecosystem maturity: asyncdispatch has known limitations (error propagation, cancellation). chronos is better but less documented. Neither matches the maturity of Go’s goroutines or Rust’s Tokio ecosystem.

Package discoverability: With only ~2,000 Nimble packages, you may find yourself either wrapping C libraries directly or going without.

The Verdict

Nim is a language worth knowing. It occupies a real niche: the space between Python (easy but slow) and Rust (fast but demanding) where you want readable, high-level code that compiles to an efficient binary. The 2.0 release makes it a credible production choice for the right problems.

Use Nim when you control the stack, performance matters, and the problem fits one of Nim’s strengths: CLI tools, network services, scripting, C library wrappers, or embedded DSLs. Do not use Nim when you need a large hiring pool, a rich ecosystem, or mature cloud-native tooling.

The tragedy of Nim is not that it is bad — it is that it is genuinely excellent in ways that rarely get the spotlight because the ecosystem around it did not grow proportionally to the language quality. That may change slowly. The 2.0 release is a signal that the language is committed to the long haul.

Getting Started

Install Nim via choosenim (the Nim version manager, analogous to rustup):

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# Install choosenim
curl https://nim-lang.org/choosenim/init.sh -sSf | sh

# Install the latest stable Nim
choosenim stable

# Verify
nim --version
# Nim Compiler Version 2.x.x

# Create your first project
mkdir myproject && cd myproject
nimble init  # Interactive setup

Your first complete program:

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# src/main.nim
import std/strformat, std/sequtils, std/sugar, std/algorithm

type
  Task = object
    id: int
    title: string
    done: bool

proc newTask(id: int, title: string): Task =
  Task(id: id, title: title, done: false)

proc complete(t: var Task) =
  t.done = true

proc `$`(t: Task): string =
  let status = if t.done: "[x]" else: "[ ]"
  fmt"{status} ({t.id}) {t.title}"

var tasks = @[
  newTask(1, "Learn Nim syntax"),
  newTask(2, "Understand the type system"),
  newTask(3, "Write a macro"),
  newTask(4, "Build something useful"),
]

tasks[0].complete()
tasks[1].complete()

echo "=== Task List ==="
for task in tasks:
  echo task

let remaining = tasks.filter(t => not t.done)
echo fmt"\n{remaining.len} tasks remaining:"
for task in remaining:
  echo "  - ", task.title

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nim c -r src/main.nim

Output:

=== Task List ===
[x] (1) Learn Nim syntax
[x] (2) Understand the type system
[ ] (3) Write a macro
[ ] (4) Build something useful

2 tasks remaining:
  - Write a macro
  - Build something useful