Merge pull request #145 from Toloka/stubs

Autogenerated stubs

src/autoquality/optimizer.pyi

@@ -2,6 +2,7 @@ __all__ = [
     'AutoQuality',
     'DEFAULT_DISTRIBUTIONS',
 ]
+import attr._make
 import pandas
 import toloka.autoquality.scoring
 import toloka.client
@@ -85,7 +86,7 @@ class AutoQuality:
         exam_skill_id: typing.Optional[str] = None,
         label_field: str = 'label',
         n_iter: int = 10,
-        parameter_distributions: typing.Dict = ...,
+        parameter_distributions: typing.Dict = attr._make._Nothing.NOTHING,
         score_func: typing.Callable = toloka.autoquality.scoring.default_calc_scores,
         ranking_func: typing.Callable = toloka.autoquality.scoring.default_calc_ranks,
         create_autoquality_pool_func: typing.Callable = _create_autoquality_pool_default

src/client/assignment.pyi

@@ -3,6 +3,7 @@ __all__ = [
     'AssignmentPatch',
     'GetAssignmentsTsvParameters',
 ]
+import attr._make
 import datetime
 import decimal
 import toloka.client.owner
@@ -200,11 +201,11 @@ class GetAssignmentsTsvParameters(toloka.client.primitives.parameter.Parameters)
     def __init__(
         self,
         *,
-        status: typing.Optional[typing.List[Status]] = ...,
+        status: typing.Optional[typing.List[Status]] = attr._make._Nothing.NOTHING,
         start_time_from: typing.Optional[datetime.datetime] = None,
         start_time_to: typing.Optional[datetime.datetime] = None,
         exclude_banned: typing.Optional[bool] = None,
-        field: typing.Optional[typing.List[Field]] = ...
+        field: typing.Optional[typing.List[Field]] = attr._make._Nothing.NOTHING
     ) -> None:
         """Method generated by attrs for class GetAssignmentsTsvParameters.
         """

src/client/collectors.pyi

@@ -19,6 +19,9 @@ import typing
 import uuid
 
 
+def _captcha_deprecation_warning(*args, **kwargs): ...
+
+
 class CollectorConfig(toloka.client.primitives.base.BaseParameters):
     """Base class for all collectors.
 
@@ -325,7 +328,7 @@ class AssignmentSubmitTime(CollectorConfig):
 
 
 class Captcha(CollectorConfig):
-    """Collects captcha statistics for every Toloker.
+    """Deprecated. Collects captcha statistics for every Toloker.
 
     Captcha provides an advanced protection against robots. It is used with conditions:
     * [StoredResultsCount](toloka.client.conditions.StoredResultsCount.md) — How many times the Toloker entered a captcha.
@@ -377,6 +380,8 @@ class Captcha(CollectorConfig):
         _unexpected: typing.Optional[typing.Dict[str, typing.Any]]
         history_size: typing.Optional[int]
 
+    def __attrs_post_init__(*args, **kwargs): ...
+
     @typing.overload
     def __init__(
         self,

src/client/conditions.pyi

@@ -253,7 +253,7 @@ class CorrectAnswersRate(ComparableRuleCondition):
 
 
 class FailRate(ComparableRuleCondition):
-    """The percentage of unsolved captchas.
+    """Deprecated. The percentage of unsolved captchas.
 
     `FailRate` is used with collectors:
     - [Captcha](toloka.client.collectors.Captcha.md)
@@ -558,7 +558,7 @@ class SkippedInRowCount(ComparableRuleCondition):
 
 
 class StoredResultsCount(ComparableRuleCondition):
-    """The number of times a Toloker entered captcha.
+    """Deprecated. The number of times a Toloker entered captcha.
 
     `StoredResultsCount` is used with collectors:
     - [Captcha](toloka.client.collectors.Captcha.md)
@@ -594,7 +594,7 @@ class SubmittedAssignmentsCount(ComparableRuleCondition):
 
 
 class SuccessRate(ComparableRuleCondition):
-    """A percentage of solved captchas out of all entered captchas.
+    """Deprecated. A percentage of solved captchas out of all entered captchas.
 
     `SuccessRate` is used with collectors:
     - [Captcha](toloka.client.collectors.Captcha.md)

src/client/pool/dynamic_overlap_config.pyi

@@ -7,42 +7,44 @@ import typing
 
 
 class DynamicOverlapConfig(toloka.client.primitives.base.BaseTolokaObject):
-    """Dynamic overlap setting.
+    """Dynamic overlap settings.
+
+    Toloka can automatically increase an overlap of tasks if the confidence level of aggregated responses is not high enough.
+
+    Dynamic overlap uses the `BASIC` algorithm.
+    Each response is assigned a weight depending on the Toloker's skill value.
+    The aggregated response confidence is calculated based on the probability algorithm.
+    The task overlap increases until it reaches `max_overlap` or until the confidence of the aggregated response exceeds `min_confidence`.
+
+    Note, that if you use dynamic overlap, then set the `auto_close_after_complete_delay_seconds` pool parameter to a non zero value.
+
+    Learn more about the [Dynamic overlap](https://toloka.ai/en/docs/guide/concepts/dynamic-overlap) in the guide.
 
-    Allows you to change the overlap depending on how well Tolokers handle the task.
-    Set the closing interval (auto_close_after_complete_delay_seconds). It should be enough to complete tasks
-    with an overlap higher than the minimum.
-    When all pool tasks are completed, aggregate the responses.
     Attributes:
-        type: The algorithm for dynamic overlap.
-        max_overlap: Maximum overlap. Must be higher than the values in defaults. Minimum — 1. Maximum — 30000.
-        min_confidence: Minimum confidence of the aggregated response. Values from 0 to 1.
-        answer_weight_skill_id: A skill that determines the weight of the Toloker's response. For best results, use
-            a skill calculated as percentage of correct responses in control tasks.
-        fields: Output data fields to use for aggregating responses.
+        type: The dynamic overlap algorithm.
+        max_overlap: Maximum overlap. The value must be higher than the default overlap value. Allowed range: from 1 to 30,000.
+        min_confidence: Minimum required confidence of the aggregated response. Allowed range: from 0 to 1.
+        answer_weight_skill_id: A skill that determines the weight of the Toloker's responses.
+            For the best results, use a skill calculated as a percentage of correct responses in control tasks.
+        fields: A list of output data fields used for aggregating responses.
+            For the best results, each field must have a limited number of response options.
+            Don't specify fields in the list together if they depend on each other.
     """
 
     class Type(toloka.util._extendable_enum.ExtendableStrEnum):
         """The algorithm for dynamic overlap.
 
         Attributes:
-            BASIC: Each response is assigned a weight depending on the Toloker's skill value.
-                The aggregated response confidence is calculated based on the probability algorithm. The task overlap
-                increases until it reaches max_overlap or until the confidence of the aggregated response
-                exceeds min_confidence.
-                You have to specify max_overlap, min_confidence, answer_weight_skill_id and fields.
+            BASIC: The algorithm based on a Toloker's skill value.
         """
 
         BASIC = 'BASIC'
 
     class Field(toloka.client.primitives.base.BaseTolokaObject):
-        """Output data fields to use for aggregating responses.
+        """An output data field used for aggregating responses.
 
-        For best results, each of these fields must
-        have a limited number of response options.
-        Don't specify several fields if their values depend on each other.
         Attributes:
-            name: The output data field name.
+            name: The name of the output field.
         """
 
         def __init__(self, name: typing.Optional[str] = None) -> None:

src/client/pool/dynamic_pricing_config.pyi

@@ -9,27 +9,31 @@ import typing
 class DynamicPricingConfig(toloka.client.primitives.base.BaseTolokaObject):
     """The dynamic pricing settings.
 
+    A price per task suite can be variable depending on a Toloker's skill.
+    If a Toloker is not covered by dynamic pricing settings then the default price is used. It is set in the `reward_per_assignment` pool parameter.
+
     Attributes:
-        type: Parameter type for calculating dynamic pricing. The SKILL value.
-        skill_id: ID of the skill that the task price is based on
-        intervals: Skill level intervals. Must not overlap.
-            A Toloker with a skill level that is not included in any interval will receive the basic
-            price for a task suite.
+        type: The dynamic pricing type. Only `SKILL` type is supported now.
+        skill_id: The ID of the skill that dynamic pricing is based on.
+        intervals: A list of skill intervals and prices.
+            The intervals must not overlap.
     """
 
     class Type(toloka.util._extendable_enum.ExtendableStrEnum):
-        """Dynamic pricing type
+        """Dynamic pricing type.
         """
 
         SKILL = 'SKILL'
 
     class Interval(toloka.client.primitives.base.BaseTolokaObject):
-        """Skill level interval
+        """Skill level interval with the associated price per task suite.
+
+        The lower and upper skill bounds are included in the interval.
 
         Attributes:
-            from_: Lower bound of the interval.
-            to: dynamic_pricing_config.intervals.to
-            reward_per_assignment: The price per task page for a Toloker with the specified skill level.
+            from_: The lower bound of the interval.
+            to: The upper bound of the interval.
+            reward_per_assignment: The price per task suite for a Toloker with the specified skill level.
         """
 
         def __init__(

src/client/pool/mixer_config.pyi

@@ -7,47 +7,46 @@ import typing
 
 
 class MixerConfig(toloka.client.primitives.base.BaseTolokaObject):
-    """Parameters for automatically creating a task suite ("smart mixing").
+    """Settings for automatically grouping tasks into suites (smart mixing).
 
-    For more information about creating task see Toloka Requester's guide.
+    You can set the number of general, training and control tasks in a task suite. Also, you control task shuffling and other settings.
 
     Attributes:
-        real_tasks_count: The number of main tasks to put in a task suite.
-            The maximum number of tasks in a task suite if training_task_distribution_function or
-            golden_task_distribution_function are used.
-        golden_tasks_count: The number of control ("golden set") tasks to put in a task suite.
-        training_tasks_count: The number of training tasks to put in a task suite.
-        min_real_tasks_count: Minimum number of main tasks in a task suite (if the number of assignments left is less
-            than the one specified in real_tasks_count). Minimum — 0. By default, the value is the same as in
-            real_tasks_count.
-        min_golden_tasks_count: Minimum number of control tasks in a task suite (if the number of assignments left is
-            less than the one specified in golden_tasks_count). Minimum — 0. By default, the value is the same as
-            in golden_tasks_count.
-        min_training_tasks_count: Minimum number of training tasks in a task suite (if the number of assignments left is
-            less than the one specified in golden_tasks_count). Minimum — 0. By default, the value is the same
-            as in training_tasks_count.
-        force_last_assignment: Setup for the last set of tasks in the pool, if less than the minimum remaining number of
-            tasks are not completed (mixer_config.min_real_tasks_count). Values:
-            * true - issue an incomplete task set.
-            * false - don't issue tasks. This option can be used if you are adding tasks after the pool is started.
-            This parameter only applies to main tasks. The number of control and training tasks in the last set must be
-            complete (golden_tasks_count, training_tasks_count).
-        force_last_assignment_delay_seconds: Waiting time (in seconds) since the addition of the task, or increase in
-            the overlap, prior to the issuance of the last set of tasks in the pool. The minimum is 0, the maximum is
-            86,400 seconds (one day).
-            This parameter can be used if the pool has force_last_assignment: True.
-        mix_tasks_in_creation_order: The order for including tasks in suites:
-            * True — Add tasks to suites in the order in which they were uploaded. For example, in a pool with an
-                overlap of 5, the first uploaded task will be included in the first 5 task suites. They will be
-                assigned to 5 Tolokers.
-            * False — Add tasks to suites in random order.
-        shuffle_tasks_in_task_suite: The order of tasks within a suite:
-            * True — Random.
-            * False — The order in which tasks were uploaded.
-        golden_task_distribution_function: Issue of control tasks with uneven frequency. The option allows you to change
-            the frequency of checking as the Toloker completes more tasks.
-        training_task_distribution_function: Issue of training tasks with uneven frequency. The option allows you to
-            change the frequency of training tasks as the Toloker completes more tasks.
+        real_tasks_count: The number of general tasks in a task suite.
+
+            If `training_task_distribution_function` or `golden_task_distribution_function` are used then `real_tasks_count` denotes the maximum number of tasks in a task suite.
+        golden_tasks_count: The number of control tasks in a task suite.
+        training_tasks_count: The number of training tasks in a task suite.
+        min_real_tasks_count: The minimum number of general tasks in a task suite if there are not enough tasks left to create a full task suite.
+
+            Allowed range: from 0 to `real_tasks_count`.
+            By default, the `min_real_tasks_count` value equals to the `real_tasks_count` value.
+        min_golden_tasks_count: The minimum number of control tasks in a task suite if there are not enough control tasks left to create a full task suite.
+
+            Allowed range: from 0 to `golden_tasks_count`.
+            By default, the `min_golden_tasks_count` value equals to the `golden_tasks_count` value.
+        min_training_tasks_count: The minimum number of training tasks in a task suite if there are not enough training tasks left to create a full task suite.
+
+            Allowed range: from 0 to `training_tasks_count`.
+            By default, the `min_training_tasks_count` value equals to the `training_tasks_count` value.
+        force_last_assignment: A setting used when the number of remaining general tasks in the pool is less than the `min_real_tasks_count` value.
+            Note, that there must be enough control and training tasks to create a task suite.
+
+            * True — An incomplete task suite is assigned.
+            * False — An incomplete task suite is not assigned. It is useful if you add tasks to an open pool.
+
+            Default: `True`.
+        force_last_assignment_delay_seconds: Time in seconds before assigning the last task suite. This parameter is used if `force_last_assignment` is set to `True`.
+
+            Allowed range: from 0 to 86,400 seconds (one day).
+        mix_tasks_in_creation_order:
+            * True — Tasks are grouped in task suites in the order they were created.
+            * False — Tasks are chosen for a task suite in a random order.
+        shuffle_tasks_in_task_suite:
+            * True — Tasks in a task suite are shuffled on the page.
+            * False — Tasks in a task suite are placed on the page in the order they were created.
+        golden_task_distribution_function: Customizing the number of control tasks in a task suite depending on completed tasks by a Toloker.
+        training_task_distribution_function: Customizing the number of training tasks in a task suite depending on completed tasks by a Toloker.
     """
 
     def __init__(

src/client/pool/speed_quality_balance_config.pyi

@@ -9,15 +9,20 @@ import typing
 
 
 class SpeedQualityBalanceConfig(toloka.client.primitives.base.BaseTolokaObject):
-    """Adjust balance between speed and quality.
+    """A configuration of selecting Tolokers based on a personalized quality forecast.
+
+    Tolokers are sorted by their quality forecast. You can limit the number of the best Tolokers who have access to your tasks.
+    It influences quality of results and speed of getting results.
+
+    Learn more about [Speed/quality balance](https://toloka.ai/en/docs/guide/concepts/adjust).
     """
 
     class Type(toloka.util._extendable_enum.ExtendableStrEnum):
-        """The type of speed quality balance:
+        """The type of the filter used in [SpeedQualityBalanceConfig](toloka.client.pool.speed_quality_balance_config.SpeedQualityBalanceConfig.md).
 
         Attributes:
-            TOP_PERCENTAGE_BY_QUALITY: get top XX% Tolokers by quality.
-            BEST_CONCURRENT_USERS_BY_QUALITY: get top x Tolokers by quality.
+            TOP_PERCENTAGE_BY_QUALITY: A percentage of the best Tolokers is configured.
+            BEST_CONCURRENT_USERS_BY_QUALITY: A maximum number of the best Tolokers is configured.
         """
 
         TOP_PERCENTAGE_BY_QUALITY = 'TOP_PERCENTAGE_BY_QUALITY'
@@ -32,7 +37,7 @@ class SpeedQualityBalanceConfig(toloka.client.primitives.base.BaseTolokaObject):
 
 
 class TopPercentageByQuality(SpeedQualityBalanceConfig):
-    """The percentage of Tolokers ordered by quality that will work on pool.
+    """`SpeedQualityBalanceConfig` that uses percentage of Tolokers.
     """
 
     def __init__(self, *, percent: typing.Optional[int] = None) -> None:
@@ -45,7 +50,7 @@ class TopPercentageByQuality(SpeedQualityBalanceConfig):
 
 
 class BestConcurrentUsersByQuality(SpeedQualityBalanceConfig):
-    """How many concurrent Tolokers ordered by quality will work on pool.
+    """`SpeedQualityBalanceConfig` that uses a maximum number of Tolokers.
     """
 
     def __init__(self, *, count: typing.Optional[int] = None) -> None:

src/client/project/localization.pyi

@@ -2,6 +2,7 @@ __all__ = [
     'AdditionalLanguage',
     'LocalizationConfig',
 ]
+import attr._make
 import enum
 import toloka.client.primitives.base
 import typing
@@ -37,7 +38,7 @@ class AdditionalLanguage(toloka.client.primitives.base.BaseTolokaObject):
             self,
             *,
             value: typing.Optional[str] = None,
-            source: typing.Union[Source, str, None] = ...
+            source: typing.Union[Source, str, None] = attr._make._Nothing.NOTHING
         ) -> None:
             """Method generated by attrs for class AdditionalLanguage.FieldTranslation.
             """
@@ -82,7 +83,7 @@ class LocalizationConfig(toloka.client.primitives.base.BaseTolokaObject):
         self,
         *,
         default_language: typing.Optional[str] = None,
-        additional_languages: typing.Optional[typing.List[AdditionalLanguage]] = ...
+        additional_languages: typing.Optional[typing.List[AdditionalLanguage]] = attr._make._Nothing.NOTHING
     ) -> None:
         """Method generated by attrs for class LocalizationConfig.
         """

src/client/project/template_builder/plugins.pyi

@@ -6,6 +6,7 @@ __all__ = [
     'TriggerPluginV1',
     'TolokaPluginV1',
 ]
+import attr._make
 import toloka.client.project.template_builder.base
 import toloka.util._extendable_enum
 import typing
@@ -337,7 +338,7 @@ class TolokaPluginV1(BasePluginV1):
     @typing.overload
     def __init__(
         self,
-        layout: typing.Optional[typing.Union[toloka.client.project.template_builder.base.BaseComponent, TolokaPluginLayout]] = ...,
+        layout: typing.Optional[typing.Union[toloka.client.project.template_builder.base.BaseComponent, TolokaPluginLayout]] = attr._make._Nothing.NOTHING,
         *,
         notifications: typing.Optional[typing.Union[toloka.client.project.template_builder.base.BaseComponent, typing.List[toloka.client.project.template_builder.base.BaseComponent]]] = None,
         version: typing.Optional[str] = '1.0.0'