Janet

Janet Style Guide

This skill guides the generation of idiomatic Janet code covering functional patterns, performance tradeoffs, common gotchas, and Janet-specific idioms.

Core Principles

Functional Style by Default

• Always prefer functional style unless there is a clear performance penalty or tradeoff
• Use imperative/mutable approaches only when performance demands it (large collections, hot paths, string building)
• When mutation is used for performance, document why and keep scope limited

Prefer let Over Sequential def

Use let to group related bindings instead of sequential def statements:

# Good - let groups bindings clearly
(defn process [data]
  (let [items (data :items)
        count (length items)
        filtered (filter valid? items)]
    (map transform filtered)))

# Avoid - sequential defs
(defn process [data]
  (def items (data :items))
  (def count (length items))
  (def filtered (filter valid? items))
  (map transform filtered))

Reserve def for top-level definitions and cases where bindings are interspersed with side effects or control flow that makes let awkward.

Prefer Immutability (When Practical)

• Use def for immutable bindings instead of var
• Favor pure functions without side effects
• When mutation is necessary, limit scope and make it explicit

Embrace Higher-Order Functions

Use Janet's rich set of functional primitives:

• map, filter, reduce for collection transformations
• keep, keep-indexed for filtering with transformation
• mapcat for flat-mapping operations
• partition, take, drop for sequence manipulation
• comp, partial, complement for function composition
• juxt for parallel application

Favor Expressions Over Statements

• Use if, cond, case as expressions that return values
• Prefer when for single-branch conditionals with side effects
• Use ->> and -> threading macros for pipeline clarity
• Chain operations rather than using intermediate variables

Use Destructuring

Destructure function parameters and let bindings for clarity:

# Good - destructuring
(defn process [{:name name :age age}]
  (string name " is " age))

# Avoid - manual extraction
(defn process [person]
  (def name (person :name))
  (def age (person :age))
  (string name " is " age))

Common Functional Patterns

Collection Transformation Pipelines

# Good - functional pipeline
(->> data
     (filter some-pred?)
     (map transform)
     (reduce combine init))

# Avoid - procedural loops
(var result init)
(each item data
  (when (some-pred? item)
    (set result (combine result (transform item)))))

Building Data Structures

# Good - expression-based construction
(def users
  (map (fn [{:name n :age a}]
         {:name n :adult? (>= a 18)})
       raw-data))

# Avoid - imperative building
(var users @[])
(each person raw-data
  (array/push users
    {:name (person :name)
     :adult? (>= (person :age) 18)}))

Conditional Logic

# Good - cond expression
(def status
  (cond
    (< score 60) :fail
    (< score 80) :pass
    :excellent))

# Avoid - nested ifs with mutation
(var status nil)
(if (< score 60)
  (set status :fail)
  (if (< score 80)
    (set status :pass)
    (set status :excellent)))

Function Composition

# Good - compose smaller functions
(def process
  (comp
    (partial filter valid?)
    (partial map normalize)
    (partial sort compare)))

# Use threading for readability
(defn analyze [data]
  (->> data
       (filter valid?)
       (map normalize)
       (sort compare)
       (take 10)))

Recursion and Reduce

# Good - tail-recursive
(defn factorial [n]
  (defn fac-iter [n acc]
    (if (<= n 1)
      acc
      (fac-iter (- n 1) (* n acc))))
  (fac-iter n 1))

# Good - reduce for aggregation
(defn sum [xs] (reduce + 0 xs))

# Avoid - imperative loop for simple aggregation
(defn sum [xs]
  (var total 0)
  (each x xs (set total (+ total x)))
  total)

Janet-Specific Idioms

Sequence Processing

# Use keep for filter+map
(keep |(when (even? $) (* $ 2)) (range 10))

# Use partition for chunking
(partition 3 (range 10))

# Use interleave/interpose for combining
(interleave [:a :b :c] [1 2 3])

Short Functions

Use | short-fn syntax for concise anonymous functions:

(map |(* $ $) (range 5))        # square
(filter |(> $ 10) numbers)      # greater than 10
(reduce |(+ $0 $1) 0 numbers)   # sum

Pattern Matching

Use match for elegant conditional dispatch:

(defn describe [value]
  (match value
    [:ok x] (string "success: " x)
    [:err e] (string "error: " e)
    _ "unknown"))

Struct/Table Construction

# Good - literal construction
(def config
  {:host "localhost"
   :port 8080
   :debug true})

# Use struct for immutable maps
(struct :a 1 :b 2 :c 3)

# Use zipcoll for key-value pairing
(zipcoll [:a :b :c] [1 2 3])

Performance: When to Choose Imperative Style

Janet's mutable data structures are often faster than immutable ones. Use imperative/mutable approaches when:

High-Performance Scenarios

• Building large collections incrementally: Use @[] and array/push instead of repeated concatenation
• Accumulating results in loops: Local mutation with var is faster than recursive accumulation
• Hot paths and tight loops: Mutation avoids allocation overhead
• String building: Use buffer with buffer/push-string instead of string concatenation
• Large data processing: Mutable operations avoid copying large structures

Performance-Optimized Patterns

Fast array building:

# Fast - mutation for large results
(defn process-large [items]
  (def result @[])
  (each item items
    (when (expensive-pred? item)
      (array/push result (expensive-transform item))))
  result)

# Slower for large collections - creates intermediate arrays
(defn process-large [items]
  (->> items
       (filter expensive-pred?)
       (map expensive-transform)))

Fast string building:

# Fast - buffer mutation
(defn build-report [data]
  (def buf @"")
  (each item data
    (buffer/push-string buf "Item: ")
    (buffer/push-string buf (item :name))
    (buffer/push-string buf "\n"))
  (string buf))

# Slower - string concatenation
(defn build-report [data]
  (reduce (fn [acc item]
            (string acc "Item: " (item :name) "\n"))
          "" data))

Fast accumulation:

# Fast - local mutation
(defn sum-squares [numbers]
  (var total 0)
  (each n numbers
    (+= total (* n n)))
  total)

# Slower - functional reduce (minor difference, but matters in hot paths)
(defn sum-squares [numbers]
  (reduce (fn [acc n] (+ acc (* n n))) 0 numbers))

Fast table/struct construction:

# Fast - build mutable then freeze
(defn group-by [key-fn items]
  (def groups @{})
  (each item items
    (def k (key-fn item))
    (if-let [group (groups k)]
      (array/push group item)
      (put groups k @[item])))
  (table/to-struct groups))  # Return immutable if needed

When Functional Style Still Wins

• Small collections: Overhead is negligible, clarity matters more
• One-pass transformations: map/filter are well-optimized
• Code that's not performance-critical: Readability and maintainability trump speed
• When immutability prevents bugs: Thread safety, easier reasoning about code

Hybrid Approach

Combine both styles for optimal results:

# Functional pipeline with imperative inner loop for performance
(defn analyze-data [raw-data]
  (->> raw-data
       (filter valid?)
       (partition-by get-category)
       (map (fn [batch]
              # Imperative processing of each batch
              (def result @{})
              (each item batch
                (def key (item :id))
                (put result key (expensive-compute item)))
              result))))

Anti-Patterns to Avoid

Dogmatic Functional Style Over Performance

# Avoid - pure but slow for large data
(defn process-huge-file [lines]
  (reduce (fn [acc line]
            (if (matches? line)
              (array/concat acc [(parse line)])
              acc))
          [] lines))

# Prefer - imperative but fast
(defn process-huge-file [lines]
  (def result @[])
  (each line lines
    (when (matches? line)
      (array/push result (parse line))))
  result)

Over-using var and set for Simple Values

# Avoid - unnecessary mutation
(var x 0)
(set x 10)
(set x (+ x 5))

# Prefer - direct calculation
(def x (+ 10 5))

Side Effects in Map/Filter (Unless Intentional)

# Avoid - side effects in map (unless debugging)
(map (fn [x] (print x) (* x 2)) items)

# Prefer - separate concerns
(each x items (print x))
(map |(* $ 2) items)

# OK for debugging/logging
(map |(do (log/debug "processing" $) (process $)) items)

Deeply Nested Conditionals

# Avoid
(if a
  (if b
    (if c x y)
    z)
  w)

# Prefer cond
(cond
  (and a b c) x
  (and a b) y
  a z
  w)

Janet Gotchas and Common Pitfalls

Truthiness: nil and false

Only nil and false are falsey in Janet. Everything else is truthy, including:

(if 0 "truthy" "falsey")      # => "truthy" (0 is truthy!)
(if "" "truthy" "falsey")     # => "truthy" (empty string is truthy!)
(if [] "truthy" "falsey")     # => "truthy" (empty array is truthy!)
(if {} "truthy" "falsey")     # => "truthy" (empty table is truthy!)

# Use explicit checks for emptiness
(if (empty? arr) "empty" "not empty")
(if (zero? n) "zero" "not zero")

Equality: = vs deep=

= checks reference equality for data structures, not content:

(= [1 2 3] [1 2 3])           # => false (different objects)
(deep= [1 2 3] [1 2 3])       # => true (same content)

(def a [1 2 3])
(def b a)
(= a b)                       # => true (same reference)

# Watch out in data structure comparisons
(def m {:a [1 2]})
(= (m :a) [1 2])              # => false! Use deep=

Keywords vs Symbols

Keywords and symbols look similar but behave differently:

:keyword    # keyword - evaluates to itself
'symbol     # symbol - quoted, used for metaprogramming

# Keywords are functions that look themselves up
(:name {:name "Alice"})       # => "Alice"
(map :name users)             # common idiom

# Don't confuse them
(= :foo 'foo)                 # => false

in Returns the Value, Not a Boolean

(in tbl key) returns the value at key, not a boolean indicating presence. This is a trap when the stored value is false or nil:

(def m @{:enabled false :count 0})

# WRONG — (in m :enabled) returns false, so this falls through!
(if (in m :enabled)
  (m :enabled)       # never reached when value is false
  :default)          # => :default (BUG!)

# CORRECT — use has-key? to check presence
(if (has-key? m :enabled)
  (m :enabled)       # => false (correct!)
  :default)

# This is especially dangerous in toggle/collapse patterns:
(def collapsed @{:section-a false})
(if (in collapsed :section-a)
  (collapsed :section-a)    # never reached — "in" returned false
  true)                     # => true (BUG — ignores the stored value)

Rule: Use has-key? when checking if a key exists. Use in/get only when you know the value won't be false or nil, or when you want nil-as-missing semantics.

Nil Punning in Collections

nil values in tables/structs disappear:

(def m {:a 1 :b nil :c 3})
m                             # => {:a 1 :c 3} (no :b!)
(get m :b)                    # => nil
(in m :b)                     # => false (key doesn't exist)

# Use sentinel values if you need to distinguish
(def m {:a 1 :b :missing :c 3})

Function Arity: Variable Arguments

Functions with variable arguments have gotchas:

# & rest parameters capture remaining args
(defn f [a b & rest]
  (pp rest))

(f 1 2 3 4)                   # rest => @[3 4] (mutable array!)

# Named parameters must come before &
(defn bad [& rest a b]        # WRONG - syntax error
  ...)

(defn good [a b & rest]       # Correct order
  ...)

Array/Tuple Confusion

Arrays and tuples have different properties:

[1 2 3]      # tuple (immutable)
@[1 2 3]     # array (mutable)
(tuple 1 2 3) # tuple (immutable, same as [1 2 3])

# Bracket literals are tuples, NOT arrays
(type [1 2 3])                # => :tuple
(type @[1 2 3])               # => :array

# You can't mutate a tuple
(array/push [1 2 3] 4)        # ERROR - not an array

# Use @[] when you need mutability
(def a @[1 2 3])
(array/push a 4)              # OK

Struct vs Table: Immutability Surprise

(def s {:a 1})                # struct (immutable)
(put s :b 2)                  # ERROR: struct is immutable

(def t @{:a 1})               # table (mutable)
(put t :b 2)                  # OK

# Converting between them
(table/to-struct t)           # table -> struct (freezes)
(struct/to-table s)           # struct -> table (thaws)

Integer Division vs Float Division

(/ 5 2)                       # => 2.5 (float division)
(div 5 2)                     # => 2 (integer division)

# Watch out in loops
(for i 0 (/ 10 3)             # i goes 0, 1, 2 (up to 3.333...)
  (print i))

(for i 0 (div 10 3)           # i goes 0, 1, 2 (up to 3)
  (print i))

Scope and def vs var

# def creates new binding in current scope
(def x 10)
(let [x 20]
  (def x 30)                  # New binding in let scope
  x)                          # => 30
x                             # => 10 (outer unchanged)

# var allows mutation
(var x 10)
(let []
  (set x 30)                  # Mutates outer var
  x)                          # => 30
x                             # => 30 (outer changed)

Short Function $ Parameters

# $ is first arg, $0 is also first arg
|(+ $ 1)        # (fn [x] (+ x 1))
|(+ $0 1)       # same thing

# $1, $2, etc. for multiple args
|(+ $0 $1)      # (fn [x y] (+ x y))

# Can't mix $ and explicit parameters
|(fn [x] (+ $ x))  # ERROR

do Block Returns Last Value

(def x (do
         (print "calculating")
         (+ 1 2)
         (* 3 4)))            # x => 12 (last value)

# Watch out with conditionals
(if (even? n)
  (do
    (print "even")
    :even)                    # Return :even
  :odd)

# Missing return value
(if (even? n)
  (print "even")              # Returns nil!
  :odd)

Loop vs While vs Each

# loop is a general iteration macro with verbs
(loop [i :range [0 10]]
  (print i))

# loop with multiple bindings and conditionals
(loop [i :range [0 10]
       :when (even? i)]
  (print i))

# loop with :in for iterating collections
(loop [x :in items
       :when (pos? x)]
  (print x))

# while is for conditional loops
(var i 0)
(while (< i 10)
  (+= i 1))

# each is shorthand for (loop [x :in coll] ...)
(each x items
  (print x))

# Prefer each for simple iteration, loop when you need
# :range, :keys, :pairs, :when, :until, :let, etc.

Negative Indices Work Differently

(def a [1 2 3 4 5])
(a -1)                        # => 5 (last element)
(a -2)                        # => 4 (second to last)

# But get doesn't support negative indices
(get a -1)                    # => nil (not 5!)

# Use negative indices carefully

Macro Hygiene and Unquote

# Macros don't evaluate arguments
(defmacro bad [x]
  (def y 10)
  ~(+ ,x y))                  # y might capture user's y

# Use gensym for hygiene
(defmacro good [x]
  (def y-sym (gensym))
  ~(let [,y-sym 10]
     (+ ,x ,y-sym)))

# Usually use defn, not defmacro

Array Mutation Surprise

(def original @[1 2 3])
(def copy original)           # Not a copy! Same reference

(array/push copy 4)
original                      # => @[1 2 3 4] (mutated!)

# Actually copy
(def real-copy (array/slice original))
(array/push real-copy 5)
original                      # => @[1 2 3 4] (unchanged)

reduce Argument Order

# reduce is: (reduce func init collection)
(reduce + 0 [1 2 3])          # correct

# Easy to get wrong
(reduce [1 2 3] + 0)          # WRONG - errors

# Function receives (accumulator, value)
(reduce (fn [acc x] (+ acc x)) 0 [1 2 3])

PEG (Parsing Expression Grammar) Capture Gotchas

# PEG captures can be subtle
(peg/match '(capture (some :d)) "123")   # => @["123"]
(peg/match '(some (capture :d)) "123")   # => @["1" "2" "3"]

# Position vs capture
(peg/match '(* "a" (position)) "abc")    # => @[1]
(peg/match '(* "a" (capture "b")) "abc") # => @["b"]

# DANGER: nil return from replacement drops the capture entirely!
# If a :replace or :/ callback returns nil, the capture is DROPPED.
(peg/match ~(/ "null" ,(fn [_] nil)) "null")  # => @[]  (empty! nil was dropped)

# Use a sentinel value instead:
(def my-nil :sentinel/nil)
(peg/match ~(/ "null" ,(fn [_] my-nil)) "null")  # => @[:sentinel/nil]
# Then unwrap sentinels back to nil in post-processing.

Code Review Checklist

When generating or reviewing Janet code, verify:

• let used for grouped bindings instead of sequential defs
• [...] used for tuples (immutable), @[...] for arrays (mutable)
• {...} used for structs (immutable), @{...} for tables (mutable)
• String building uses buffer for multiple concatenations, not repeated string
• Large collection building uses @[]/array/push not repeated concatenation
• Threading macros (->, ->>) used where they improve readability
• Short-fn | syntax used for simple lambdas
• Destructuring used in function parameters where clear
• deep= used for structural comparison, not =
• has-key? used instead of in when value may be false or nil
• PEG replacement functions never return nil (use sentinel values)
• loop uses correct verb syntax (:range, :in, :keys, etc.)
• Mutation scope is limited and intentional