Ich habe mehrere Ideen in den beliebtesten Python-Editoren getestet: PyCharm, VS Code, Jedi-basierte Editoren.

Laut der letzten <a href="https://www.jetbrains.com/research/python-developers-survey-2018/#development-tools" class="external-link" target="_blank">Python-Entwickler-Umfrage</a> deckt das etwa 80 % der Benutzer ab.

    // Once the journal has a failure, subsequent writes aren't permitted.
    filesystem.setFaultyWrite(journalFile, false)
    assertThat(cache.edit("d")).isNull()

    // Confirm that the fault didn't corrupt entries stored before the fault was introduced.
    cache.close()
    cache =
      DiskLruCache(filesystem, cacheDir, appVersion, 2, Int.MAX_VALUE.toLong(), taskRunner).also {
        toClose.add(it)
      }

   *
   * - https://github.com/jspecify/jdk/commit/71d826792b8c7ef95d492c50a274deab938f2552
   */
  /*
   * TODO(cpovirk): Is the unchecked cast avoidable? Would System.arraycopy be similarly fast (if
   * likewise not type-checked)? Could our single caller do something different?
   */
  @SuppressWarnings({"nullness", "unchecked"})

				return cfg, err
			}
		}
	}

	switch speed := env.Get(EnvSpeed, kvs.GetWithDefault(Speed, DefaultKVS)); speed {
	case "fastest":
		cfg.Delay, cfg.MaxWait, cfg.Cycle = 0, 0, time.Second
	case "fast":
		cfg.Delay, cfg.MaxWait, cfg.Cycle = 1, 100*time.Millisecond, time.Minute
	case "default":
		cfg.Delay, cfg.MaxWait, cfg.Cycle = 2, time.Second, time.Minute
	case "slow":

It was one of the first extremely fast Python frameworks based on `asyncio`. It was made to be very similar to Flask.

/// note | Technical Details

It used <a href="https://github.com/MagicStack/uvloop" class="external-link" target="_blank">`uvloop`</a> instead of the default Python `asyncio` loop. That's what made it so fast.

# Separate OpenAPI Schemas for Input and Output or Not { #separate-openapi-schemas-for-input-and-output-or-not }

Since **Pydantic v2** was released, the generated OpenAPI is a bit more exact and **correct** than before. 😎

In fact, in some cases, it will even have **two JSON Schemas** in OpenAPI for the same Pydantic model, for input and output, depending on if they have **default values**.

Let's see how that works and how to change it if you need to do that.

[build-system]
requires = ["pdm-backend"]
build-backend = "pdm.backend"

[project]
name = "fastapi"
dynamic = ["version"]
description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
readme = "README.md"
license = "MIT"
license-files = ["LICENSE"]
requires-python = ">=3.9"
authors = [
    { name = "Sebastián Ramírez", email = "******@****.***" },
]
classifiers = [

 * the License.
 */

/*
 * SipHash-c-d was designed by Jean-Philippe Aumasson and Daniel J. Bernstein and is described in
 * "SipHash: a fast short-input PRF" (available at https://131002.net/siphash/siphash.pdf).
 */

package com.google.common.hash;

import static com.google.common.base.Preconditions.checkArgument;

  /**
   * Returns a {@link ScheduledExecutorService} that never executes anything.
   *
   * <p>The {@code shutdownNow} method of the returned executor always returns an empty list despite
   * the fact that everything is still technically awaiting execution. The {@code getDelay} method
   * of any {@link ScheduledFuture} returned by the executor will always return the max long value

- To be able to reliably use S3 multipart APIs feature of the SDKs without re-inventing the wheel of pre-signing the each URL in multipart API. This is very tedious to implement with all the scenarios of fault tolerance that's already implemented by the client SDK. The general client SDKs don't support multipart with presigned URLs.