for making modifications to it.  "Object code" means any non-source
form of a work.

  A "Standard Interface" means an interface that either is an official
standard defined by a recognized standards body, or, in the case of
interfaces specified for a particular programming language, one that
is widely used among developers working in that language.

  The "System Libraries" of an executable work include anything, other

const (
	// Type '0' indicates a regular file.
	TypeReg = '0'

	// Deprecated: Use TypeReg instead.
	TypeRegA = '\x00'

	// Type '1' to '6' are header-only flags and may not have a data body.
	TypeLink    = '1' // Hard link
	TypeSymlink = '2' // Symbolic link
	TypeChar    = '3' // Character device node
	TypeBlock   = '4' // Block device node
	TypeDir     = '5' // Directory
	TypeFifo    = '6' // FIFO node

ar f=arguments.length&&(c||"boolean"!=typeof d),g=c||(d===!0||e===!0?"margin":"border");return J(this,function(b,c,d){var e;return n.isWindow(b)?b.document.documentElement["client"+a]:9===b.nodeType?(e=b.documentElement,Math.max(b.body["scroll"+a],e["scroll"+a],b.body["offset"+a],e["offset"+a],e["client"+a])):void 0===d?n.css(b,c,g):n.style(b,c,d,g)},b,f?d:void 0,f,null)}})}),n.fn.size=function(){return this.length},n.fn.andSelf=n.fn.addBack,"function"==typeof define&&define.amd&&define("jquery"...

https://qiita.com/hikarut/items/b178af2e2440c67c6ac4 title: フロントエンド開発者向けのDockerによるPython開発環境構築 - author: '@angel_katayoku' author_link: https://qiita.com/angel_katayoku link: https://qiita.com/angel_katayoku/items/8a458a8952f50b73f420 title: FastAPIでPOSTされたJSONのレスポンスbodyを受け取る - author: '@angel_katayoku' author_link: https://qiita.com/angel_katayoku link: https://qiita.com/angel_katayoku/items/4fbc1a4e2b33fa2237d2 title: FastAPIをMySQLと接続してDockerで管理してみる - author: '@angel_katayoku' author_link: https://qiita.com/angel_katayoku...

![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

## تغییر مثال

حال فایل `main.py` را مطابق زیر ویرایش کنید تا بتوانید <abbr title="Body">بدنه</abbr> یک درخواست `PUT` را دریافت کنید.

به کمک Pydantic بدنه درخواست را با <abbr title="Type">انواع</abbr> استاندارد پایتون تعریف کنید.

```Python hl_lines="4  9-12  25-27"
from typing import Optional

    /**
     * Get the value for the key 'crawler.document.file.append.body.content'. <br>
     * The value is, e.g. true <br>
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getCrawlerDocumentFileAppendBodyContent();

    /**
     * Is the property for the key 'crawler.document.file.append.body.content' true? <br>
     * The value is, e.g. true <br>

  // any values not recognized.
  //
  // "Deny" and "Warn" may not be used together since this combination
  // needlessly duplicates the validation failure both in the
  // API response body and the HTTP warning headers.
  //
  // Required.
  // +listType=set
  repeated string validationActions = 4;
}

// ValidatingAdmissionPolicyList is a list of ValidatingAdmissionPolicy.

   * If we make these calls inline inside toImmutableSortedMultiset, we get an Animal Sniffer error,
   * despite the @IgnoreJRERequirement annotation there. My assumption is that, because javac
   * generates a synthetic method for the body of the lambda, the actual method calls that Animal
   * Sniffer is flagging don't appear inside toImmutableSortedMultiset but rather inside that
   * synthetic method. By moving those calls to a named method, we're able to apply

			}
		}
	}
	r.err = err
	return
}

func (r *checksumReader) Close() error { return r.rc.Close() }

// findBodyOffset does the minimum work to verify the file has a header
// and returns the file body offset.
func (f *File) findBodyOffset() (int64, error) {
	var buf [fileHeaderLen]byte
	if _, err := f.zipr.ReadAt(buf[:], f.headerOffset); err != nil {
		return 0, err
	}
	b := readBuf(buf[:])

        separate_input_output_schemas: Annotated[
            bool,
            Doc(
                """
                Whether to generate separate OpenAPI schemas for request body and
                response body when the results would be more precise.

                This is particularly useful when automatically generating clients.

                For example, if you have a model like: