generator draft

Author: iliakan

1-js/09-async/06-async-iteration/article.md

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+
+# Async iteration
+
+TODO

1-js/10-generators/01-generator/01-pseudo-random-generator/_js.view/solution.js

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+function* pseudoRandom(seed) {
+  let value = seed;
+
+  while(true) {
+    value = value * 16807 % 2147483647
+    yield value;
+  }
+
+};

1-js/10-generators/01-generator/01-pseudo-random-generator/_js.view/test.js

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+describe("pseudoRandom", function() {
+
+  it("follows the formula", function() {
+    let generator = pseudoRandom(1);
+
+    assert.equal(generator.next().value, 16807);
+    assert.equal(generator.next().value, 282475249);
+    assert.equal(generator.next().value, 1622650073);
+  });
+
+
+  it("returns same value for the same seed", function() {
+    let generator1 = pseudoRandom(123);
+    let generator2 = pseudoRandom(123);
+
+    assert.deepEqual(generator1.next(), generator2.next());
+    assert.deepEqual(generator1.next(), generator2.next());
+    assert.deepEqual(generator1.next(), generator2.next());
+  });
+
+});

1-js/10-generators/01-generator/01-pseudo-random-generator/solution.md

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+
+Please note, the same can be done with a regular function, like this:
+
+```js run
+function pseudoRandom(seed) {
+  let value = seed;
+
+  return function() {
+    value = value * 16807 % 2147483647;
+    return value;
+  }
+}
+
+let generator = pseudoRandom(1);
+
+alert(generator()); // 16807
+alert(generator()); // 282475249
+alert(generator()); // 1622650073
+```

1-js/10-generators/01-generator/01-pseudo-random-generator/task.md

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+
+# Pseudo-random generator
+
+There are many areas where we need random data.
+
+One of them is testing. We may need random data: text, numbers etc, to test things out well.
+
+In Javascript, we could use `Math.random()`. But if something goes wrong, we'd like to be able to repeat the test, using exactly the same data.
+
+For that, so called "seeded pseudo-random generators" are used. They take a "seed", the first value, and then generate next ones using a formula. So that the same seed yields the same sequence, and hence the whole flow is easily reproducable. We only need to remember the seed to repeat it.
+
+An example of such formula, that generates somewhat uniformly distributed values:
+
+```
+next = previous * 16807 % 2147483647
+```
+
+If we use `1` as the seed, the values will be:
+1. `16807`
+2. `282475249`
+3. `1622650073`
+4. ...and so on...
+
+The task is to create a generator function `pseudoRandom(seed)` that takes `seed` and creates the generator with this formula.
+
+Use example:
+
+```js
+let gen = pseudoRandom(1);
+
+alert(gen.next().value); // 16807
+alert(gen.next().value); // 282475249
+alert(gen.next().value); // 1622650073
+```