build(deps): bump the deps group with 16 updates

dff/context_storages/database.py

@@ -7,6 +7,7 @@
 that developers can inherit from in order to create their own context storage solutions.
 This class implements the basic functionality and can be extended to add additional features as needed.
 """
+
 import asyncio
 import importlib
 import threading

dff/context_storages/json.py

@@ -5,6 +5,7 @@
 This class is used to store and retrieve context data in a JSON. It allows the DFF to easily
 store and retrieve context data.
 """
+
 import asyncio
 from typing import Hashable
 

dff/context_storages/mongo.py

@@ -11,6 +11,7 @@
 and environments. Additionally, MongoDB is highly scalable and can handle large amounts of data
 and high levels of read and write traffic.
 """
+
 from typing import Hashable, Dict, Any
 
 try:

dff/context_storages/pickle.py

@@ -10,6 +10,7 @@
 It is efficient and fast, but it is not recommended to use it to transfer data across
 different languages or platforms because it's not cross-language compatible.
 """
+
 import asyncio
 import pickle
 from typing import Hashable

dff/context_storages/protocol.py

@@ -12,6 +12,7 @@
 The DFF supports a variety of communication protocols,
 which allows it to communicate with different types of databases.
 """
+
 import json
 import pathlib
 

dff/context_storages/redis.py

@@ -12,6 +12,7 @@
 Additionally, Redis can be used as a cache, message broker, and database, making it a versatile
 and powerful choice for data storage and management.
 """
+
 import json
 from typing import Hashable
 

dff/context_storages/shelve.py

@@ -12,6 +12,7 @@
 It stores data in a dbm-style format in the file system, which is not as fast as the other serialization
 libraries like pickle or JSON.
 """
+
 import pickle
 from shelve import DbfilenameShelf
 from typing import Hashable

dff/context_storages/sql.py

@@ -12,6 +12,7 @@
 reliability and scalability. SQLite is a self-contained, high-reliability, embedded, full-featured,
 public-domain, SQL database engine.
 """
+
 import asyncio
 import importlib
 import json

dff/context_storages/ydb.py

@@ -9,6 +9,7 @@
 with Yandex Cloud services using python. This allows the DFF to easily integrate with the Yandex DataBase and
 take advantage of the scalability and high-availability features provided by the service.
 """
+
 import asyncio
 import os
 from typing import Hashable

dff/messengers/common/interface.py

@@ -4,6 +4,7 @@
 The Message Interfaces module contains several basic classes that define the message interfaces.
 These classes provide a way to define the structure of the messengers that are used to communicate with the DFF.
 """
+
 from __future__ import annotations
 import abc
 import asyncio

dff/messengers/common/types.py

@@ -3,6 +3,7 @@
 -----
 The Types module contains special types that are used throughout the `DFF Messengers`.
 """
+
 from typing import Callable
 from typing_extensions import TypeAlias
 

dff/messengers/telegram/interface.py

@@ -4,6 +4,7 @@
 This module implements various interfaces for :py:class:`~dff.messengers.telegram.messenger.TelegramMessenger`
 that can be used to interact with the Telegram API.
 """
+
 import asyncio
 from typing import Any, Optional, List, Tuple, Callable
 

dff/messengers/telegram/message.py

@@ -3,6 +3,7 @@
 ----------------
 This module implements inherited classes :py:mod:`dff.script.core.message` modified for usage with Telegram.
 """
+
 from typing import Optional, Union
 from enum import Enum
 
@@ -67,9 +68,9 @@ class ParseMode(Enum):
 
 
 class TelegramMessage(Message):
-    ui: Optional[
-        Union[TelegramUI, RemoveKeyboard, ReplyKeyboardRemove, ReplyKeyboardMarkup, InlineKeyboardMarkup]
-    ] = None
+    ui: Optional[Union[TelegramUI, RemoveKeyboard, ReplyKeyboardRemove, ReplyKeyboardMarkup, InlineKeyboardMarkup]] = (
+        None
+    )
     location: Optional[Location] = None
     callback_query: Optional[Union[str, _ClickButton]] = None
     update: Optional[

dff/messengers/telegram/messenger.py

@@ -6,6 +6,7 @@
 Using it, you can put Telegram update handlers inside your script and condition your transitions accordingly.
 
 """
+
 from pathlib import Path
 from typing import Union, List, Optional, Callable
 from enum import Enum

dff/messengers/telegram/utils.py

@@ -3,6 +3,7 @@
 ------
 This module contains utilities for connecting to Telegram.
 """
+
 from typing import Union, Iterable
 from contextlib import contextmanager
 from pathlib import Path

dff/pipeline/conditions.py

@@ -5,6 +5,7 @@
 are attached should be executed or not.
 The standard set of them allows user to setup dependencies between pipeline components.
 """
+
 from __future__ import annotations
 from typing import Optional, TYPE_CHECKING
 

dff/pipeline/pipeline/actor.py

@@ -22,6 +22,7 @@
 
 .. figure:: /_static/drawio/dfe/user_actor.png
 """
+
 from __future__ import annotations
 import logging
 import asyncio

dff/pipeline/pipeline/component.py

@@ -8,6 +8,7 @@
 The PipelineComponent class can be a group or a service. It is designed to be reusable and composable,
 allowing developers to create complex processing pipelines by combining multiple components.
 """
+
 from __future__ import annotations
 import logging
 import abc

dff/pipeline/pipeline/pipeline.py

@@ -13,6 +13,7 @@
 class, which is defined in the Component module. Together, these classes provide a powerful and flexible way
 to structure and manage the messages processing flow.
 """
+
 import asyncio
 import logging
 from typing import Union, List, Dict, Optional, Hashable, Callable

dff/pipeline/pipeline/utils.py

@@ -4,6 +4,7 @@
 The Utils module contains several service functions that are commonly used throughout the framework.
 These functions provide a variety of utility functionality.
 """
+
 import collections
 from typing import Union, List
 from inspect import isfunction

dff/pipeline/service/extra.py

@@ -5,6 +5,7 @@
 beyond the core functionality. Extra handlers is an input converting addition to :py:class:`.PipelineComponent`.
 For example, it is used to grep statistics from components, timing, logging, etc.
 """
+
 from __future__ import annotations
 import asyncio
 import logging

dff/pipeline/service/group.py

@@ -7,6 +7,7 @@
 allowing for easier management and organization of the services within the pipeline.
 The :py:class:`~.ServiceGroup` serves the important function of grouping services to work together in parallel.
 """
+
 from __future__ import annotations
 import asyncio
 import logging

dff/pipeline/service/service.py

@@ -9,6 +9,7 @@
 Service can be asynchronous only if its handler is a coroutine.
 Actor wrapping service is asynchronous.
 """
+
 from __future__ import annotations
 import logging
 import inspect

dff/pipeline/service/utils.py

@@ -4,6 +4,7 @@
 The Utility Functions module contains several utility functions that are commonly used throughout the DFF.
 These functions provide a variety of utility functionality.
 """
+
 import asyncio
 from typing import Callable, Any, Optional, Tuple, Mapping
 

dff/pipeline/types.py

@@ -5,6 +5,7 @@
 The classes and special types in this module can include data models,
 data structures, and other types that are defined for type hinting.
 """
+
 from __future__ import annotations
 from enum import unique, Enum
 from typing import Callable, Union, Awaitable, Dict, List, Optional, Iterable, Any, Protocol, Hashable, TYPE_CHECKING

dff/script/conditions/std_conditions.py

@@ -8,6 +8,7 @@
 These conditions can be used to check the current context, the user's input,
 or other factors that may affect the conversation flow.
 """
+
 from typing import Callable, Pattern, Union, List, Optional
 import logging
 import re

dff/script/core/context.py

@@ -16,6 +16,7 @@
 The context can be easily serialized to a format that can be stored or transmitted, such as JSON.
 This allows developers to save the context data and resume the conversation later.
 """
+
 from __future__ import annotations
 import logging
 from uuid import UUID, uuid4

dff/script/core/keywords.py

@@ -5,6 +5,7 @@
 They are used to determine all nodes in the script and to assign python objects and python functions for nodes.
 
 """
+
 from enum import Enum
 
 

dff/script/core/message.py

@@ -4,6 +4,7 @@
 The :py:class:`.Message` class is a universal data model for representing a message that should be supported by
 DFF. It only contains types and properties that are compatible with most messaging services.
 """
+
 from typing import Any, Optional, List, Union
 from enum import Enum, auto
 from pathlib import Path

dff/script/core/normalization.py

@@ -5,6 +5,7 @@
 that is suitable for script and actor execution process.
 This module contains a basic set of functions for normalizing data in a dialog script.
 """
+
 from __future__ import annotations
 import logging
 from typing import Union, Callable, Optional, TYPE_CHECKING

dff/script/core/script.py

@@ -5,6 +5,7 @@
 These models are used to define the conversation flow, and to determine the appropriate response based on
 the user's input and the current state of the conversation.
 """
+
 # %%
 from __future__ import annotations
 import logging

dff/script/core/types.py

@@ -6,6 +6,7 @@
 The types defined in this module include basic data types such as strings
 and lists, as well as more complex types that are specific to the framework.
 """
+
 from typing import Union, Callable, Tuple
 from enum import Enum, auto
 from typing_extensions import TypeAlias

dff/script/labels/std_labels.py

@@ -10,6 +10,7 @@
 This module contains a standard set of scripting :py:const:`labels <dff.script.NodeLabelType>` that
 can be used by developers to define the conversation flow.
 """
+
 from __future__ import annotations
 from typing import Optional, Callable, TYPE_CHECKING
 from dff.script import Context, NodeLabel3Type

dff/script/responses/std_responses.py

@@ -8,6 +8,7 @@
 This module provides only one predefined response function that can be used to quickly
 respond to the user and keep the conversation flowing.
 """
+
 import random
 from typing import List
 

dff/stats/__main__.py

@@ -25,6 +25,7 @@
             --outfile=config_artifact.zip
 
 """
+
 import sys
 import argparse
 from typing import Optional

dff/stats/cli.py

@@ -4,6 +4,7 @@
 This modules defines commands that can be called via the command line interface.
 
 """
+
 from uuid import uuid4
 import tempfile
 import shutil

dff/stats/default_extractors.py

@@ -10,6 +10,7 @@
 Detailed examples can be found in the `tutorials` section.
 
 """
+
 from datetime import datetime
 
 from dff.script import Context

dff/stats/instrumentor.py

@@ -8,6 +8,7 @@
 
 For detailed reference, see `~OtelInstrumentor` class.
 """
+
 import asyncio
 from typing import Collection, Optional
 

dff/stats/utils.py

@@ -11,6 +11,7 @@
     set_tracer_destination(OTLPSpanExporter("grpc://localhost:4317", insecure=True))
 
 """
+
 import json
 import getpass
 from urllib import parse

dff/utils/db_benchmark/basic_config.py

@@ -7,6 +7,7 @@
 as well as a set of configurations that covers different dialogs a user might have and some edge-cases
 (:py:data:`~.basic_configurations`).
 """
+
 from typing import Tuple, Optional
 import string
 import random

dff/utils/db_benchmark/benchmark.py

@@ -18,6 +18,7 @@
 :py:func:`~dff.utils.db_benchmark.report.report` or
 `our streamlit app <../_misc/benchmark_streamlit.py>`_.
 """
+
 from uuid import uuid4
 from pathlib import Path
 from time import perf_counter

dff/utils/db_benchmark/report.py

@@ -3,6 +3,7 @@
 --------
 This method contains a function to print benchmark results to console.
 """
+
 from pathlib import Path
 from typing import Union, Set, Literal
 import json
@@ -44,9 +45,11 @@ def report(
             "config": "\n".join(f"{k}: {v}" for k, v in benchmark["benchmark_config"].items()),
             "metrics": "".join(
                 [
-                    f"{metric.title() + ': ' + str(benchmark['average_results']['pretty_' + metric]):20}"
-                    if benchmark["success"]
-                    else benchmark["result"]
+                    (
+                        f"{metric.title() + ': ' + str(benchmark['average_results']['pretty_' + metric]):20}"
+                        if benchmark["success"]
+                        else benchmark["result"]
+                    )
                     for metric in ("write", "read", "update", "read+update")
                 ]
             ),

dff/utils/testing/cleanup_db.py

@@ -4,6 +4,7 @@
 This module defines functions that allow to delete data in various types of databases,
 including JSON, MongoDB, Pickle, Redis, Shelve, SQL, and YDB databases.
 """
+
 import os
 
 from dff.context_storages import (

dff/utils/testing/common.py

@@ -3,6 +3,7 @@
 ------
 This module contains several functions which are used to run demonstrations in tutorials.
 """
+
 from os import getenv
 from typing import Callable, Tuple, Optional
 from uuid import uuid4

dff/utils/testing/response_comparers.py

@@ -3,6 +3,7 @@
 -----------------
 This module defines function used to compare two response objects.
 """
+
 from typing import Any, Optional
 
 from dff.script import Context, Message