@app.post("/file_before_form")
def file_before_form(
    file: bytes = File(),
    city: str = Form(),
):
    return {"file_content": file, "city": city}


@app.post("/file_after_form")
def file_after_form(
    city: str = Form(),
    file: bytes = File(),
):
    return {"file_content": file, "city": city}


@app.post("/file_list_before_form")
def file_list_before_form(

		return
	}

	DB.Migrator().DropTable(&City{}, &Museum{})

	if err = db.AutoMigrate(&City{}, &Museum{}); err != nil {
		t.Fatalf("failed to migrate countries & cities tables, got error: %v", err)
	}

	city := City{Name: "Amsterdam"}

	err = db.Create(&city).Error
	if err != nil {
		t.Fatalf("failed to create city: %v", err)
	}

        """

        line_1: str
        city: str
        state_province: str

    class Facility(BaseModel):
        id: str
        address: Address

    app = FastAPI()

    @app.get("/facilities/{facility_id}")
    def get_facility(facility_id: str) -> Facility:
        return Facility(
            id=facility_id,
            address=Address(line_1="123 Main St", city="Anytown", state_province="CA"),
        )

 * failing tasks only, to not use up unnecessary disk space on Team City. This also improves the performance of
 * artifact publishing by reducing the artifacts and packaging reports that consist of multiple files.
 *
 * Reducing the number of reports also makes it easier to find the important ones when analysing a failed build in
 * Team City.
 */

		b[i] = charset[randSrc.Intn(len(charset))]
	}
	return string(b)
}

func genSampleCSVData(count int) []byte {
	buf := &bytes.Buffer{}
	csvWriter := csv.NewWriter(buf)
	csvWriter.Write([]string{"id", "name", "age", "city"})

	for i := range count {
		csvWriter.Write([]string{
			strconv.Itoa(i),
			newRandString(10),
			newRandString(5),
			newRandString(10),
		})
	}

	csvWriter.Flush()
	return buf.Bytes()
}

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: FastAPI
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Sebastián
    family-names: Ramírez
    email: ******@****.***
identifiers:
repository-code: 'https://github.com/fastapi/fastapi'

cff-version: 1.2.0
message: "If you use TensorFlow in your research, please cite it using these metadata. Software is available from tensorflow.org."
title: TensorFlow, Large-scale machine learning on heterogeneous systems