var editor: DiskLruCache.Editor? = null
    try {
      editor = snapshot.edit() ?: return // edit() returns null if snapshot is not current.
      entry.writeTo(editor)
      editor.commit()
    } catch (_: IOException) {
      abortQuietly(editor)
    }
  }

  private fun abortQuietly(editor: DiskLruCache.Editor?) {
    // Give up because the cache cannot be written.
    try {

from the `envs` directory that is filled with configuration options:

-   Nightly jobs (Run nightly on the `nightly` branch)
    -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`
-   Presubmit jobs (Run on every GitHub PR)
    -   Uses `pycpp.sh`, `code_check_changed_files.sh`

These "env" files match up with an environment matrix that roughly covers:

rights granted under Section 2(b) shall terminate as of the date such
litigation is filed.

All Recipient's rights under this Agreement shall terminate if it
fails to comply with any of the material terms or conditions of this
Agreement and does not cure such failure in a reasonable period of
time after becoming aware of such noncompliance. If all Recipient's

    }

    public void setCity_Terms(ConditionOptionCall<TermsAggregationBuilder> opLambda) {
        setCity_Terms("city", opLambda, null);
    }

    public void setCity_Terms(ConditionOptionCall<TermsAggregationBuilder> opLambda, OperatorCall<BsUserCA> aggsLambda) {
        setCity_Terms("city", opLambda, aggsLambda);
    }

    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.

Spark/Hadoop workloads which use Hadoop MR Committer v1/v2 algorithm upload objects to a temporary prefix in a bucket. These objects are 'renamed' to a different prefix on Job commit. Object storage admins are forced to configure separate ILM policies to expire these objects and their versions to reclaim space.

### Solution

    * Automatic and clear errors when the data is invalid.
    * Validation even for deeply nested JSON objects.
* <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Forms.
    * Files.

You will get completion in code you might even consider impossible before. As for example, the `price` key inside a JSON body (that could have been nested) that comes from a request.

No more typing the wrong key names, coming back and forth between docs, or scrolling up and down to find if you finally used `username` or `user_name`.

### Short { #short }

* After applying the PR, the new tests should pass.
* Coverage should stay at 100%.
* If you see the PR makes sense, or we discussed it and considered it should be accepted, you can add commits on top of the PR to tweak it, to add docs, tests, format, refactor, remove extra files, etc.
* Feel free to comment in the PR to ask for more information, to suggest changes, etc.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[40:45] hl[40:45] *}

</details>

Aqui, usamos a dependência `SessionDep` (uma `Session`) para adicionar o novo `Hero` à instância `Session`, fazer commit das alterações no banco de dados, atualizar os dados no `hero` e então retorná-lo.

### Ler Heroes