## Use the instance as a dependency { #use-the-instance-as-a-dependency }

Then, we could use this `checker` in a `Depends(checker)`, instead of `Depends(FixedContentQueryChecker)`, because the dependency is the instance, `checker`, not the class itself.

And when solving the dependency, **FastAPI** will call this `checker` like:

```Python
checker(q="somequery")
```

    "path,expected_status,expected_response",
    [
        (
            "/query-checker/",
            200,
            {"fixed_content_in_query": False},
        ),
        (
            "/query-checker/?q=qwerty",
            200,
            {"fixed_content_in_query": False},
        ),
        (
            "/query-checker/?q=foobar",
            200,
            {"fixed_content_in_query": True},
        ),

name: Scorecard supply-chain security
on:
  # For Branch-Protection check. Only the default branch is supported. See
  # https://github.com/ossf/scorecard/blob/main/docs/checks.md#branch-protection
  branch_protection_rule:
  # To guarantee Maintained check is occasionally updated. See
  # https://github.com/ossf/scorecard/blob/main/docs/checks.md#maintained
  schedule:
    - cron: '45 9 * * 0'
  push:
    branches: [ "master" ]

        }

        return false;
    }

    /**
     * Checks if a model version is eligible for inference optimizations.
     * Models 4.0.0+ are eligible (4.0.0 has limited inference, 4.1.0+ has full inference).
     *
     * @param modelVersion the model version to check
     * @return true if eligible for inference
     */

{* ../../docs_src/query_params_str_validations/tutorial013_an_py39.py hl[9] *}

/// note

Keep in mind that in this case, FastAPI won't check the contents of the list.

For example, `list[int]` would check (and document) that the contents of the list are integers. But `list` alone wouldn't.

///

## Declare more metadata { #declare-more-metadata }

    }

    @Override
    public boolean isValid(final String value, final ConstraintValidatorContext context) {
        if (StringUtil.isNotBlank(value)) {
            return check(protocols, value);
        }
        return true;
    }

    /**
     * Checks if the given value matches any of the specified protocols.
     *
     * @param protocols the allowed protocols
     * @param value the URI string to validate

        fileProtocols[fileProtocols.length - 1] = prefix;
    }

    /**
     * Checks if the given URL is a file path protocol that requires directory and permission handling.
     * Used for incremental crawling directory detection and file permission processing.
     *
     * @param url the URL to check
     * @return true if the URL uses a file path protocol (smb, smb1, file, ftp, s3, gcs)
     */

      // Allowed in case test doesn't have privs
    }
  }

  /**
   * Checks that thread does not terminate within the default millisecond delay of {@code
   * timeoutMillis()}.
   */
  void assertThreadStaysAlive(Thread thread) throws InterruptedException {
    assertThreadStaysAlive(thread, timeoutMillis());
  }

  /** Checks that thread does not terminate within the given millisecond delay. */

        notAnalyzedFieldSet = new HashSet<>();
        Collections.addAll(notAnalyzedFieldSet, fields);
    }

    /**
     * Checks if the specified field can be used for sorting.
     * Uses O(1) Set lookup for improved performance.
     *
     * @param field the field name to check
     * @return true if the field can be used for sorting, false otherwise
     */
    protected boolean isSortField(final String field) {

    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.
    * You can have deeply **nested JSON** objects and have them all validated and annotated.
* **Extensible**: