# words checklist
segfault_memory:
   - segfault
   - memory leaks
# assignees
filesystem_security_assignee:
   - mihaimaruseac
   
# Cuda Comment
cuda_comment: >
   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:
      * For TF-GPU - See point 1
      * For TF-CPU - See point 2
   -----------------------------------------------------------------------------------------------
   

But for those additional responses you have to make sure you return a `Response` like `JSONResponse` directly, with your status code and content.

## Additional Response with `model` { #additional-response-with-model }

You can pass to your *path operation decorators* a parameter `responses`.

It receives a `dict`: the keys are status codes for each response (like `200`), and the values are other `dict`s with the information for each of them.

		}
	}

	count, err := gorm.G[User](DB).Where("name like ?", "GenericsCreateInBatches%").Count(ctx, "*")
	if err != nil {
		t.Fatalf("Count failed: %v", err)
	}
	if count != 3 {
		t.Errorf("expected 3 records, got %d", count)
	}

	found, err := gorm.G[User](DB).Raw("SELECT * FROM users WHERE name LIKE ?", "GenericsCreateInBatches%").Find(ctx)
	if len(found) != len(batch) {

# Static Files - `StaticFiles`

You can use the `StaticFiles` class to serve static files, like JavaScript, CSS, images, etc.

Read more about it in the [FastAPI docs for Static Files](https://fastapi.tiangolo.com/tutorial/static-files/).

You can import it directly from `fastapi.staticfiles`:

```python
from fastapi.staticfiles import StaticFiles
```

* 따라서 이미지, 동영상, 큰 이진코드와 같은 대용량 파일들을 많은 메모리를 소모하지 않고 처리하기에 적합합니다.
* 업로드 된 파일의 메타데이터를 얻을 수 있습니다.
* <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a>  `async` 인터페이스를 갖고 있습니다.

	// message itself contains some colored text, we needed
	// to use some ANSI control escapes to cursor color state
	// and freely move in the screen.
	for line := range strings.SplitSeq(errMsg, "\n") {
		if len(line) == 0 {
			// No more text to print, just quit.
			break
		}

		// Save the attributes of the current cursor helps
		// us save the text color of the passed error message

    }

    /**
     * Creates a string with all location details for the specified model problem. If the project identifier is
     * provided, the generated location will omit the model id and source information and only give line/column
     * information for problems originating directly from this POM.
     *
     * @param problem The problem whose location should be formatted, must not be {@code null}.

			// validation needed.
			continue
		case !strings.Contains(output, line1):
			t.Errorf("Testcase %d: output '%s' did not contain line 1: '%s'", i+1, output, line1)
		case !strings.Contains(output, line2):
			t.Errorf("Testcase %d: output '%s' did not contain line 2: '%s'", i+1, output, line2)
		}
	}

                        // and captures the content within the brackets.
                        Files.readAllLines(file).forEach(line -> {
                            if (line.matches("^\\s*\\[\\[(.*)\\]\\].*")) {
                                String anchorName = line.replaceAll("^\\s*\\[\\[(.*)\\]\\].*$", "$1");
                                allAnchors.add(anchorName);
                            }

## Pydantic Models for Input and Output { #pydantic-models-for-input-and-output }

Let's say you have a Pydantic model with default values, like this one:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### Model for Input { #model-for-input }

If you use this model as an input like here:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}