assertFailsWith<IllegalStateException> {
      abort()
    }
  }

  private fun Editor.setString(
    index: Int,
    value: String,
  ) {
    newSink(index).buffer().use { writer ->
      writer.writeUtf8(value)
    }
  }

pkg log/syslog (freebsd-riscv64), method (*Writer) Debug(string) error #53466
pkg log/syslog (freebsd-riscv64), method (*Writer) Emerg(string) error #53466
pkg log/syslog (freebsd-riscv64), method (*Writer) Err(string) error #53466
pkg log/syslog (freebsd-riscv64), method (*Writer) Info(string) error #53466
pkg log/syslog (freebsd-riscv64), method (*Writer) Notice(string) error #53466
pkg log/syslog (freebsd-riscv64), method (*Writer) Warning(string) error #53466

### Iterators

The new [`iter` package](/pkg/iter/) provides the basic definitions for

feature gate is enabled, user should not upgrade to Kubernetes v1.22. vSphere CSI Driver does not support Kubernetes v1.22 yet because it uses v1beta1 CRD APIs. Support for v1.22 will be added at a later release. Check the following document for supported Kubernetes releases for a given [vSphere CSI Driver version](https://vsphere-csi-driver.sigs.k8s.io/compatiblity_matrix.html#compatibility-matrix-for-vsphere-csi-driver).

### Workloads that saturate nodes with pods may see pods that fail...

- Set CSIMigrationvSphere feature gates to beta.
  Users should enable CSIMigration + CSIMigrationvSphere features and install the vSphere CSI Driver (https://github.com/kubernetes-sigs/vsphere-csi-driver) to move workload from the in-tree vSphere plugin "kubernetes.io/vsphere-volume" to vSphere CSI Driver.
  

---

## Instala FastAPI

El primer paso es instalar FastAPI.

Para el tutorial, es posible que quieras instalarlo con todas las dependencias y características opcionales:

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%

`tensorflow` pip package has a new, optional installation method for Linux that installs necessary Nvidia CUDA libraries through pip. As long as the Nvidia driver is already installed on the system, you may now run `pip install tensorflow[and-cuda]` to install TensorFlow's Nvidia CUDA library dependencies in the Python environment. Aside from the Nvidia driver, no other pre-existing Nvidia CUDA packages are necessary.

*   Enable JIT-compiled i64-indexed kernels on GPU for large tensors with more...

        opt Handhabt
            dep -->> dep: Kann Exception abfangen, eine neue HTTPException auslösen, andere Exceptions auslösen
            dep -->> handler: Leitet Exception automatisch weiter
        end
        handler -->> client: HTTP-Error-Response
    end
    operation ->> client: Sendet Response an Client
    Note over client,operation: Response wurde gesendet, kann nicht mehr geändert werden

import org.jetbrains.kotlin.analysis.project.structure.KtDanglingFileModule
import org.jetbrains.kotlin.analysis.project.structure.KtModule
import org.jetbrains.kotlin.analysis.utils.printer.parentOfType
import org.jetbrains.kotlin.fileClasses.javaFileFacadeFqName
import org.jetbrains.kotlin.fir.FirElementWithResolveState
import org.jetbrains.kotlin.fir.analysis.checkers.getContainingClassSymbol

import org.jetbrains.kotlin.analysis.low.level.api.fir.util.collectUseSiteContainers
import org.jetbrains.kotlin.analysis.utils.errors.withKtModuleEntry
import org.jetbrains.kotlin.analysis.utils.printer.parentsOfType
import org.jetbrains.kotlin.fir.FirElement
import org.jetbrains.kotlin.fir.analysis.checkers.declaration.isLocalMember
import org.jetbrains.kotlin.fir.declarations.*
import org.jetbrains.kotlin.fir.expressions.*