plugins {
  kotlin("jvm")
  application
  id("com.google.devtools.ksp")
}

application {
  mainClass.set("okhttp3.survey.RunSurveyKt")
}

dependencies {
  implementation(projects.okhttp)
  implementation(projects.okhttpCoroutines)
  implementation(libs.conscrypt.openjdk)

  implementation(libs.retrofit)
  implementation(libs.converter.moshi)
  implementation(libs.squareup.moshi)
  implementation(libs.squareup.moshi.kotlin)

I tested several ideas in the most popular Python editors: PyCharm, VS Code, Jedi based editors.

By the last <a href="https://www.jetbrains.com/research/python-developers-survey-2018/#development-tools" class="external-link" target="_blank">Python Developer Survey</a>, that covers about 80% of the users.

In the Python developer surveys, it's clear <a href="https://www.jetbrains.com/research/python-developers-survey-2017/#tools-and-features" class="external-link" target="_blank">that one of the most used features is "autocompletion"</a>.

      if (wrapper.getCause() instanceof Error) {
        throw new ExecutionError((Error) wrapper.getCause());
      }
      /*
       * It's an Exception. (Or it's a non-Error, non-Exception Throwable. From my survey of such
       * classes, I believe that most users intended to extend Exception, so we'll treat it like an
       * Exception.)
       */
      throw new UncheckedExecutionException(wrapper.getCause());
    }

pkg crypto, type MessageSigner interface, SignMessage(io.Reader, []uint8, SignerOpts) ([]uint8, error) #63405
pkg crypto/ecdsa, func ParseRawPrivateKey(elliptic.Curve, []uint8) (*PrivateKey, error) #63963
pkg crypto/ecdsa, func ParseUncompressedPublicKey(elliptic.Curve, []uint8) (*PublicKey, error) #63963
pkg crypto/ecdsa, method (*PrivateKey) Bytes() ([]uint8, error) #63963
pkg crypto/ecdsa, method (*PublicKey) Bytes() ([]uint8, error) #63963

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* 🔧 Add new Gold Sponsor vim.so 🎉. PR [#2669](https://github.com/tiangolo/fastapi/pull/2669) by [@tiangolo](https://github.com/tiangolo).
* 🔧 Add FastAPI user survey banner. PR [#2623](https://github.com/tiangolo/fastapi/pull/2623) by [@tiangolo](https://github.com/tiangolo).

    *   Add `tf.keras.layers.AbstractRNNCell` as the preferred implementation
        for RNN cells in TF v2. User can use it to implement RNN cells with
        custom behavior.
    *   Keras training and validation curves are shown on the same plot when
        using the TensorBoard callback.
    *   Switched Keras `fit/evaluate/predict` execution to use only a single
        unified path by default unless eager execution has been explicitly

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