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

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"]

Code Review Checklist

When generating or reviewing Janet code, verify:

Prefer let Over Sequential def

janet

Janet Style Guide

Core Principles

Functional Style by Default