--- language: "Lean 4" filename: learnlean4.lean contributors: - ["Balagopal Komarath", "https://bkomarath.rbgo.in/"] - ["Ferinko", "https://github.com/Ferinko"] --- [Lean 4](https://lean-lang.org/) is a dependently typed functional programming language and an interactive theorem prover. ```lean4 /- An enumerated data type. -/ inductive Grade where | A : Grade | B : Grade | F : Grade deriving Repr /- Functions. -/ def grade (m : Nat) : Grade := if 80 <= m then Grade.A else if 60 <= m then Grade.B else Grade.F def highMarks := 80 + 9 def lowMarks := 25 + 25 #eval grade highMarks #eval grade lowMarks #check (0 : Nat) /- #check (0 : Grade) -/ /- This is an error. -/ /- Types themselves are values. -/ #check (Nat : Type) /- Mathematical propositions are values in Lean. `Prop` is the type of propositions. Here are some simple propositions. -/ #check 0 = 1 #check 1 = 1 #check 2^9 - 2^8 = 2^8 /- Notice Lean displays `0 = 1 : Prop` to say: The statement "0 = 1" is a proposition. We want to distinguish true propositions and false propositions. We do this via proofs. Each proposition is a type. `0 = 1` is a type, `1 = 1` is another type. A proposition is true iff there is a value of that type. How do we construct a value of type `1 = 1`? We use a constructor that is defined for that type. `Eq.refl a` constructs a value of type `a = a`. (reflexivity) Using this we can prove `1 = 1` as follows. -/ theorem one_eq_one : 1 = 1 := Eq.refl 1 /- But there is no way to prove (construct a value of type) `0 = 1`. The following will fail. As will `Eq.refl 1` -/ /- theorem zero_eq_one : 0 = 1 := Eq.refl 0 -/ /- Let us prove an inequality involving variables. The `calc` primitive allows us to prove equalities using stepwise calculations. Each step has to be justified by a proof. -/ theorem plus_squared (a b : Nat) : (a+b)^2 = a^2 + 2*a*b + b^2 := calc (a+b)^2 = (a+b)*(a+b) := Nat.pow_two _ _ = (a+b)*a + (a+b)*b := Nat.mul_add _ _ _ _ = a*a + b*a + (a*b + b*b) := by repeat rw [Nat.add_mul] _ = a*a + b*a + a*b + b*b := by rw [← Nat.add_assoc] _ = a*a + a*b + a*b + b*b := by rw [Nat.mul_comm b _] _ = a^2 + a*b + a*b + b*b := by rw [← Nat.pow_two _] _ = a^2 + a*b + a*b + b^2 := by rw [← Nat.pow_two _] _ = a^2 + (a*b + a*b) + b^2 := by rw [Nat.add_assoc (a^_)] _ = a^2 + 2*(a*b) + b^2 := by rw [← Nat.two_mul _] _ = a^2 + 2*a*b + b^2 := by rw [Nat.mul_assoc _ _ _] /- Underscores can be used when there is no ambiguity in what is to be matched. For example, in the first step, we want to apply `Nat.pow_two (a+b)`. But, `(a+b)` is the only pattern here to apply `Nat.pow_two`. So we can omit it. -/ /- Let us now prove more "realistic" theorems. Those involving logical connectives. First, we define even and odd numbers. -/ def Even (n : Nat) := ∃ k, n = 2*k def Odd (n : Nat) := ∃ k, n = 2*k + 1 /- To prove an existential, we can provide specific values if we know them. -/ theorem zero_even : Even 0 := have h : 0 = 2 * 0 := Eq.symm (Nat.mul_zero 2) Exists.intro 0 h /- `Exists.intro v h` proves `∃ x, p x` by substituting `x` by `v` and using the proof `h` for `p v`. -/ /- Now, we will see how to use hypothesis that are existentials to prove conclusions that are existentials. The curly braces around parameters `n` and `m` indicate that they are implicit. Here, Lean will infer them from `hn` and `hm`. -/ theorem even_mul_even_is_even' {n m : Nat} (hn : Even n) (hm : Even m) : Even (n*m) := Exists.elim hn (fun k1 hk1 => Exists.elim hm (fun k2 hk2 => Exists.intro (k1 * ( 2 * k2)) ( calc n*m = (2 * k1) * (2 * k2) := by rw [hk1, hk2] _ = 2 * (k1 * (2 * k2)) := by rw [Nat.mul_assoc] ) ) ) /- Most proofs are written using *tactics*. These are commands to Lean that guide it to construct proofs by itself. The same theorem, proved using tactics. -/ theorem even_mul_even_is_even {n m : Nat} (hn : Even n) (hm : Even m) : Even (n*m) := by have ⟨k1, hk1⟩ := hn have ⟨k2, hk2⟩ := hm apply Exists.intro $ k1 * (2 * k2) calc n*m = (2 * k1) * (2 * k2) := by rw [hk1, hk2] _ = 2 * (k1 * (2 * k2)) := by rw [Nat.mul_assoc] /- Let us work with implications. -/ theorem succ_of_even_is_odd' {n : Nat} : Even n → Odd (n+1) := fun hn => have ⟨k, hk⟩ := hn Exists.intro k ( calc n + 1 = 2 * k + 1 := by rw [hk] ) /- To prove an implication `p → q`, you have to write a function that takes a proof of `p` and construct a proof of `q`. Here, `pn` is proof of `Even n := ∃ k, n = 2 *k`. Eliminating the existential gets us `k` and a proof `hk` of `n = 2 * k`. Now, we have to introduce the existential `∃ k, n + 1 = 2 * k + 1`. This `k` is the same as `k` for `n`. And, the equation is proved by a simple calculation that substitutes `2 * k` for `n`, which is allowed by `hk`. -/ /- Same theorem, now using tactics. -/ theorem succ_of_even_is_odd {n : Nat} : Even n → Odd (n+1) := by intro hn have ⟨k, hk⟩ := hn apply Exists.intro k rw [hk] /- The following theorem can be proved similarly. We will use this theorem later. A `sorry` proves any theorem. It should not be used in real proofs. -/ theorem succ_of_odd_is_even {n : Nat} : Odd n → Even (n+1) := sorry /- We can use theorems by applying them. -/ example : Odd 1 := by apply succ_of_even_is_odd exact zero_even /- The two new tactics are: - `apply p` where `p` is an implication `q → r` and `r` is the goal rewrites the goal to `q`. More generally, `apply t` will unify the current goal with the conclusion of `t` and generate goals for each hypothesis of `t`. - `exact h` solves the goal by stating that the goal is the same as `h`. -/ /- Let us see examples of disjunctions. -/ example : Even 0 ∨ Odd 0 := Or.inl zero_even example : Even 0 ∨ Odd 1 := Or.inl zero_even example : Odd 1 ∨ Even 0 := Or.inr zero_even /- Here, we always know from `p ∨ q` which of `p` and/or `q` is correct. So we can introduce a proof of the correct side. -/ /- Let us see a more "standard" disjunction. Here, from the hypothesis that `n : Nat`, we cannot determine whether `n` is even or odd. So we cannot construct `Or` directly. But, for any specific `n`, we will know which one to construct. This is exactly what induction allows us to do. We introduce the `induction` tactic. The inductive hypothesis is a disjunction. When disjunctions appear at the hypothesis, we use *proof by exhaustive cases*. This is done using the `cases` tactic. -/ theorem even_or_odd {n : Nat} : Even n ∨ Odd n := by induction n case zero => left ; exact zero_even case succ n ihn => cases ihn with | inl h => right ; apply (succ_of_even_is_odd h) | inr h => left ; apply (succ_of_odd_is_even h) /- `induction` is not just for natural numbers. It is for any type, since all types in Lean are inductive. -/ /- We now state Collatz conjecture. The proof is left as an exercise to the reader. -/ def collatz_next (n : Nat) : Nat := if n % 2 = 0 then n / 2 else 3 * n + 1 def iter (k : Nat) (f : Nat → Nat) := match k with | Nat.zero => fun x => x | Nat.succ k' => fun x => f (iter k' f x) theorem collatz : ∀ n, n > 0 → ∃ k, iter k collatz_next n = 1 := sorry /- Now, some "corner cases" in logic. -/ /- The proposition `True` is something that can be trivially proved. `True.intro` is a constructor for proving `True`. Notice that it needs no inputs. -/ theorem obvious : True := True.intro /- On the other hand, there is no constructor for `False`. We have to use `sorry`. -/ theorem impossible : False := sorry /- Any `False` in the hypothesis allows us to conclude anything. Written in term style, we use the eliminator `False.elim`. It takes a proof of `False`, here `h`, and concludes whatever is the goal. -/ theorem nonsense (h : False) : 0 = 1 := False.elim h /- The `contradiction` tactic uses any `False` in the hypothesis to conclude the goal. -/ theorem more_nonsense (h : False) : 1 = 2 := by contradiction /- To illustrate constructive vs classical logic, we now prove the contrapositive theorem. The forward direction does not require classical logic. -/ theorem contrapositive_forward' (p q : Prop) : (p → q) → (¬q → ¬p) := fun pq => fun hqf => fun hp => hqf (pq hp) /- Use the definition `¬q := q → False`. Notice that we have to construct `p → False` given `p → q` and `q → False`. This is just function composition. -/ /- The above proof, using tactics. -/ theorem contrapositive_forward (p q : Prop) : (p → q) → (¬q → ¬p) := by intro hpq intro intro hp specialize hpq hp contradiction /- The reverse requires classical logic. Here, we are required to construct a `q` given values of following types: - `(q → False) → (p → False)`. - `p`. This is impossible without using the law of excluded middle. -/ theorem contrapositive_reverse' (p q : Prop) : (¬q → ¬p) → (p → q) := fun hnqnp => Classical.byCases (fun hq => fun _ => hq) (fun hnq => fun hp => absurd hp (hnqnp hnq)) /- Law of excluded middle tells us that we will have a `q` or a `q → False`. In the first case, it is trivial to construct a `q`, we already have it. In the second case, we give the `q → False` to obtain a `p → False`. Then, we use the fact (in constructive logic) that given `p` and `p → False`, we can construct `False`. Once, we have `False`, we can construct anything, and specifically `q`. -/ /- Same proof, using tactics. -/ theorem contrapositive_reverse (p q : Prop) : (¬q → ¬p) → (p → q) := by intro hnqnp intro hp have emq := Classical.em q cases emq case inl _ => assumption case inr h => specialize hnqnp h ; contradiction /- To illustrate how we can define an work with axiomatic systems. Here is a definition of Groups and some proofs directly translated from "Topics in Algebra" by Herstein, Second edition. -/ /- A `section` introduces a namespace. -/ section GroupTheory /- To define abstract objects like groups, we may use `class`. -/ class Group (G : Type u) where op : G → G → G assoc : ∀ a b c : G, op (op a b) c = op a (op b c) e : G identity: ∀ a : G, op a e = a ∧ op e a = a inverse: ∀ a : G, ∃ b : G, op a b = e ∧ op b a = e /- Let us introduce some notation to make this convenient. -/ open Group infixl:70 " * " => op /- `G` will always stand for a group and variables `a b c` will be elements of that group in this `section`. -/ variable [Group G] {a b c : G} def is_identity (e' : G) := ∀ a : G, (a * e' = a ∧ e' * a = a) /- We prove that the identity element is unique. -/ theorem identity_element_unique : ∀ e' : G, is_identity e' → e' = e := by intro e' intro h specialize h e have ⟨h1, _⟩ := h have h' := identity e' have ⟨_, h2⟩ := h' exact Eq.trans (Eq.symm h2) h1 /- Note that we used the `identity` axiom. -/ /- Left cancellation. We have to use both `identity` and `inverse` axioms from `Group`. -/ theorem left_cancellation : ∀ x y : G, a * x = a * y → x = y := by have h1 := inverse a have ⟨ai, a_inv⟩ := h1 have ⟨_, h2⟩ := a_inv intro x y intro h3 calc x = (e : G) * x := Eq.symm (identity x).right _ = ai * a * x := by rw [h2] _ = ai * (a * x) := by rw [assoc] _ = ai * (a * y) := by rw [h3] _ = ai * a * y := by rw [← assoc] _ = (e : G) * y := by rw [h2] _ = y := (identity y).right end GroupTheory /- Variables `G`, `a`, `b`, `c` are now not in scope. -/ /- Let us see a mutually recursive definition. The game of Nim with two heaps. -/ abbrev between (lower what upper : Nat) : Prop := lower ≤ what ∧ what ≤ upper mutual def Alice : Nat → Nat → Prop | n1, n2 => ∃ k, (between 1 k n1 ∧ (between 1 k n1 → Bob (n1-k) n2)) ∨ (between 1 k n2 ∧ (between 1 k n2 → Bob n1 (n2-k))) def Bob : Nat → Nat → Prop | n1, n2 => ∀ k, (between 1 k n1 → Alice (n1-k) n2) ∧ (between 1 k n2 → Alice n1 (n2-k)) end example : Bob 0 0 := by intro k induction k case zero => constructor intro ; contradiction intro ; contradiction case succ => constructor intro a ; have := a.right ; contradiction intro a ; have := a.right ; contradiction /- We have to convince Lean of termination when a function is defined using just a `def`. Here's a simple primality checking algorithm that tests all candidate divisors. -/ def prime' (n : Nat) : Bool := if h : n < 2 then false else @go 2 n (by omega) where go (d : Nat) (n : Nat) {_ : n ≥ d} : Bool := if h : n = d then /- `h` needed for `omega` below. -/ true else if n % d = 0 then false else @go (Nat.succ d) n (by omega) termination_by (n - d) /- We have to specify that the recursive function `go` terminates because `n-k` decreases in each recursive call. This needs the hypothesis `n > k` at the recursive call site. But the function itself can only assume that `n ≥ k`. We label the test `n ≤ k` by `h` so that the falsification of this proposition can be used by `omega` later to conclude that `n > k`. The tactic `omega` can solve simple equalities and inequalities. -/ /- You can also instruct Lean to not check for totality by prefixing `partial` to `def`. -/ /- Or, we can rewrite the function to test the divisors from largest to smallest. In this case, Lean easily verifies that the function is total. -/ def prime (n : Nat) : Bool := if n < 2 then true else go (n-1) n where go d n := if d < 2 then true else if n % d = 0 then false else go (d-1) n /- Now, to Lean, it is obvious that `go` will terminate because `d` decreases in each recursive call. -/ #eval prime 57 #eval prime 97 ``` For further learning, see: * [Functional Programming in Lean](https://lean-lang.org/functional_programming_in_lean/) * [Theorem Proving in Lean 4](https://lean-lang.org/theorem_proving_in_lean4/) * [Lean 4 Manual](https://lean-lang.org/lean4/doc/)