python_lib_path = environ_cp.get('PYTHON_LIB_PATH')
  if not python_lib_path:
    python_lib_paths = get_python_path(environ_cp, python_bin_path)
    if environ_cp.get('USE_DEFAULT_PYTHON_LIB_PATH') == '1':
      python_lib_path = python_lib_paths[0]
    else:
      print('Found possible Python library paths:\n  %s' %
            '\n  '.join(python_lib_paths))
      default_python_lib_path = python_lib_paths[0]

К примеру, есть официальный <a href="https://hub.docker.com/_/python" class="external-link" target="_blank">образ Python</a>.

Также там представлены и другие полезные образы, такие как базы данных:

* <a href="https://hub.docker.com/_/postgres" class="external-link" target="_blank">PostgreSQL</a>

build:release_linux_base --linkopt=-Wl,--undefined-version

# Container environment settings below this point.
# Use Python 3.X as installed in container image
build:release_linux_base --action_env PYTHON_BIN_PATH="/usr/bin/python3"
build:release_linux_base --action_env PYTHON_LIB_PATH="/usr/lib/tf_python"
build:release_linux_base --python_path="/usr/bin/python3"
# Set Clang as compiler. Use the actual path to clang installed in container.

        ":tensorflow_py_no_contrib",
        "//tensorflow/lite/python:analyzer",
        "//tensorflow/lite/python:lite",
        "//tensorflow/lite/python/authoring",
    ],
)

py_library(
    name = "tensorflow_py_no_contrib",
    srcs = select({
        "api_version_2": [":tf_python_api_gen_v2"],
        "//conditions:default": [":tf_python_api_gen_v1"],
    }) + [
        ":root_init_gen",
    ],

            This will be used to extract the data and for the generated OpenAPI.
            It is particularly useful when you can't use the name you want because it
            is a Python reserved keyword or similar.
            """
        ),
    ] = None,
    alias_priority: Annotated[
        Union[int, None],
        Doc(
            """

```

### Step 3: Test on RabbitMQ

The python program below waits on the queue exchange `bucketevents` and prints event notifications on the console. We use [Pika Python Client](https://www.rabbitmq.com/tutorials/tutorial-three-python.html) library to do this.

```py
#!/usr/bin/env python
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

// TF_FinishWhile() or TF_AbortWhile().
//
// Missing functionality (TODO):
// - Gradients
// - Reference-type inputs
// - Directly referencing external tensors from the cond/body graphs (this is
//   possible in the Python API)
TF_CAPI_EXPORT extern TF_WhileParams TF_NewWhile(TF_Graph* g, TF_Output* inputs,
                                                 int ninputs,
                                                 TF_Status* status);

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ontent:"\f486"}.fa-print:before{content:"\f02f"}.fa-procedures:before{content:"\f487"}.fa-product-hunt:before{content:"\f288"}.fa-project-diagram:before{content:"\f542"}.fa-pushed:before{content:"\f3e1"}.fa-puzzle-piece:before{content:"\f12e"}.fa-python:before{content:"\f3e2"}.fa-qq:before{content:"\f1d6"}.fa-qrcode:before{content:"\f029"}.fa-question:before{content:"\f128"}.fa-question-circle:before{content:"\f059"}.fa-quidditch:before{content:"\f458"}.fa-quinscape:before{content:"\f459"}.fa-qu...