```

There are 2 main differences from a normal *path operation*:

* It doesn't need to have any actual code, because your app will never call this code. It's only used to document the *external API*. So, the function could just have `pass`.

///

## Bodies of pure lists

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python
images: List[Image]
```

or in Python 3.9 and above:

```Python
images: list[Image]
```

as in:

//// tab | Python 3.9+

     *            authority.
     * @param tc
     *            The context that should be used to communicate with the named server.
     * @param sids
     *            The SIDs that should be resolved. After this function is called, the names associated with the SIDs
     *            may be queried with the <tt>toDisplayString</tt>, <tt>getDomainName</tt>, and <tt>getAccountName</tt>
     *            methods.
     */
    @Override

        `TFCI_` variables shared to it.
3.  Top-level scripts (`wheel.sh`, etc.) reference `env` variables and call
    `utilities/` scripts.
    -   The `tfrun` function makes a command run correctly in Docker if Docker

   * have been newly added to {@link ConcurrentMap}! These are marked with "Since: 1.8" in the
   * {@code ConcurrentMap} documentation. They will not function correctly and it is impossible for
   * Guava to fix them until Guava is ready to <i>require</i> Java 8 for all users.
   */
  ConcurrentMap<K, V> asMap();

  /**

			cleanupFns[i]()
		}
		return nil, PreConditionFailed{}
	}
	return &GetObjectReader{
		ObjInfo:    oi,
		Reader:     r,
		cleanUpFns: cleanupFns,
	}, nil
}

// ObjReaderFn is a function type that takes a reader and returns
// GetObjectReader and an error. Request headers are passed to provide
// encryption parameters. cleanupFns allow cleanup funcs to be
// registered for calling after usage of the reader.

شما پایتون استاندارد را با استفاده از تایپ ها مینویسید:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

که سپس میتوان به این شکل از آن استفاده کرد:

import java.util.Collection;
import java.util.Collections;
import java.util.Iterator;
import java.util.List;
import java.util.Set;
import java.util.Spliterator;
import java.util.function.Consumer;
import java.util.function.ObjIntConsumer;
import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**

#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/distributed_runtime/coordination/coordination_service_error_util.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/graph_debug_info.pb.h"
#include "tensorflow/core/lib/monitoring/counter.h"
#include "tensorflow/core/lib/monitoring/gauge.h"
#include "tensorflow/core/lib/monitoring/sampler.h"

	c.writeStream(ctx, conn, cancel)
}

// readStream handles the read side of the connection.
// It will read messages and send them to c.handleMsg.
// If an error occurs the cancel function will be called and conn be closed.
// The function will block until the connection is closed or an error occurs.
func (c *Connection) readStream(ctx context.Context, conn net.Conn, cancel context.CancelCauseFunc) {
	defer func() {