And after searching for a long time for a similar framework and testing many different alternatives, APIStar was the best option available.

Then APIStar stopped to exist as a server and Starlette was created, and was a new better foundation for such a system. That was the final inspiration to build **FastAPI**.

        QueryBuilder builder = queryProcessor.execute(context, prefixQuery, 1.0f);

        assertNotNull(builder);
        assertTrue(builder instanceof DefaultQueryBuilder);

        // Query was processed successfully
    }

    public void test_convertPrefixQuery_withDefaultField_dismax() throws Exception {
        QueryContext context = new QueryContext("test", false);

     * block is automatically generated from the ntstatus package.
     */

    /** The operation completed successfully */
    int NT_STATUS_SUCCESS = 0x00000000;
    /** The requested operation was unsuccessful */
    int NT_STATUS_UNSUCCESSFUL = 0xC0000001;
    /** The requested operation is not implemented */
    int NT_STATUS_NOT_IMPLEMENTED = 0xC0000002;
    /** The specified information class is invalid */

        QueryBuilder result = queryCommand.convertPhraseQuery(context, phraseQuery, 1.0f);

        assertNotNull(result);
        assertTrue(result instanceof DefaultQueryBuilder);

        // Verify query was processed
        // Note: Field logging behavior depends on implementation
    }

    public void test_convertPhraseQuery_singleTerm_defaultField_dismax() {
        // Test with single term in default field with boost > 1

        assertNotNull(queryBuilder);
        assertTrue(queryBuilder instanceof WildcardQueryBuilder);

        // Query was processed successfully

        // Query was processed successfully
        WildcardQueryBuilder wqb = (WildcardQueryBuilder) queryBuilder;
        assertEquals("title", wqb.fieldName());
    }

    }

    public void test_execute_success() {
        // Execute the job
        String result = purgeDocJob.execute();

        // Assert deleteByQuery was called
        assertTrue(deleteByQueryCalled);

        // Assert correct index was used
        assertEquals("fess.update", deleteIndex);

        // Assert query builder is correct
        assertNotNull(deleteQuery);

For example, it was clear that ideally it should be based on standard Python type hints.

Also, the best approach was to use already existing standards.

	Name string

	// Date and time when the bucket was created.
	Created time.Time
	Deleted time.Time

	// Bucket features enabled
	Versioning, ObjectLocking bool
}

// ObjectInfo - represents object metadata.
type ObjectInfo struct {
	// Name of the bucket.
	Bucket string

	// Name of the object.
	Name string

	// Date and time when the object was last modified.
	ModTime time.Time

/// info

In Pydantic v1 the method was called `.dict()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_dump()`.

The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

///

That would generate a `dict` with only the data that was set when creating the `item` model, excluding default values.

    /** A notify change request is being completed and information is being returned */
    int NT_STATUS_NOTIFY_ENUM_DIR = 0x0000010C;
    /** The data was too large to fit into the specified buffer */
    int NT_STATUS_BUFFER_OVERFLOW = 0x80000005;
    /** The requested operation was unsuccessful */
    int NT_STATUS_UNSUCCESSFUL = 0xC0000001;
    /** The requested operation is not implemented */
    int NT_STATUS_NOT_IMPLEMENTED = 0xC0000002;