"judu", "judvi", "judviejų", "jųdviejų", "judviem", "judviese", "jumis", "jums", "jumyse", "juo", "juodu", "juodviese", "juos", "juose", "jus", "jūs", "jūsų", "ką", "kad", "kai", "kaip", "kas", "kiek", "kol", "kur", "kurie", "kuris", "man", "mane", "manęs", "manimi", "mano", "manyje", "mes", "metu", "mudu", "mudvi", "mudviejų", "mudviem", "mudviese", "mumis", "mums", "mumyse", "mus", "mūsų", "nei", "nes", "net", "nors", "nuo", "o", "pat", "per", "po", "prie", "prieš", "sau", "save", "savęs", "savimi",...

"judu", "judvi", "judviejų", "jųdviejų", "judviem", "judviese", "jumis", "jums", "jumyse", "juo", "juodu", "juodviese", "juos", "juose", "jus", "jūs", "jūsų", "ką", "kad", "kai", "kaip", "kas", "kiek", "kol", "kur", "kurie", "kuris", "man", "mane", "manęs", "manimi", "mano", "manyje", "mes", "metu", "mudu", "mudvi", "mudviejų", "mudviem", "mudviese", "mumis", "mums", "mumyse", "mus", "mūsų", "nei", "nes", "net", "nors", "nuo", "o", "pat", "per", "po", "prie", "prieš", "sau", "save", "savęs", "savimi",...

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## Future { #future }

By this point, it's already clear that **FastAPI** with its ideas is being useful for many people.

It is being chosen over previous alternatives for suiting many use cases better.

Many developers and teams already depend on **FastAPI** for their projects (including me and my team).

But still, there are many improvements and features to come.

**FastAPI** has a great future ahead.

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);

With rewrites, redirects, follow-ups and retries, your simple request may yield many requests and responses. OkHttp uses `Call` to model the task of satisfying your request through however many intermediate requests and responses are necessary. Typically this isn’t many! But it’s comforting to know that your code will continue to work if your URLs are redirected or if you failover to an alternate IP address.

    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =

    assertThat(Stats.of(NaN).mean()).isNaN();
    assertThat(TWO_VALUES_STATS.mean()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN);
    // For datasets of many double values created from an array, we test many combinations of finite
    // and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      double mean = Stats.of(values.asArray()).mean();
      if (values.hasAnyNaN()) {

So, the thief won't be able to try to use that password in another system (as many users use the same password everywhere, this would be dangerous).

## Install `pwdlib` { #install-pwdlib }

pwdlib is a great Python package to handle password hashes.

It supports many secure hashing algorithms and utilities to work with them.

The recommended algorithm is "Argon2".