gamesheet_sdk.admin.teams

GameSheet teams: competing organizations within a season.

A team is a competing organization within a season (e.g., “Raleigh Raptors”, “Durham Bulls”, etc.). Each team belongs to exactly one season and may be associated with a division. The dashboard displays teams after navigating into a season view. This module talks to the GameSheet JSON:API at /api/seasons/{season_id}/teams directly with the lightweight gamesheet_sdk.Session path – no Playwright needed for read-only access once a bearer token has been obtained (typically by reading the SPA’s accessToken from the saved browser storage state via gamesheet_sdk.common.auth.load_access_token()).

Functions

create_team(session, season_id, title, ...)

Create a new team within the specified season.

delete_team(session, season_id, team_id)

Delete a team.

get_team(session, season_id, team_id)

Get a single team by ID.

list_teams(session, season_id)

Return every team in the specified season.

update_team(session, season_id, team_id, *)

Update an existing team.

Classes

Team

A single team.
class gamesheet_sdk.admin.teams.Team[source]

Bases: BaseModel

A single team.

Maps the data[*] items in the JSON: API response of GET /api/seasons/{season_id}/teams to a flat typed model.

id

Team identifier (string in JSON:API).

Type:

str

season_id

Parent season identifier.

Type:

str

title

Team name/title.

Type:

str

division_id

Division identifier if team belongs to a division.

Type:

str | None

URL to the team logo image.

Type:

str | None

invitation_code

Invitation code for joining the team.

Type:

str | None

player_count

Number of players on the team.

Type:

int | None

coach_count

Number of coaches on the team.

Type:

int | None

created_at

When the team was created.

Type:

datetime

updated_at

Last time the team was updated.

Type:

datetime

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

id: str
season_id: str
title: str
division_id: str | None
logo: str | None
invitation_code: str | None
player_count: int | None
coach_count: int | None
created_at: datetime
updated_at: datetime
__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

classmethod construct(_fields_set=None, **values)
Return type:

Self

copy(*, include=None, exclude=None, update=None, deep=False)

Returns a copy of the model.

!!! warning “Deprecated”

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

`python {test="skip" lint="skip"} data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `

Parameters:

  • include (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to include in the copied model.

  • exclude (AbstractSetIntStr | MappingIntStrAny | None) – Optional set or mapping specifying which fields to exclude in the copied model.

  • update (Dict[str, Any] | None) – Optional dictionary of field-value pairs to override field values in the copied model.

  • deep (bool) – If True, the values of fields that are Pydantic models will be deep-copied.

Returns:

A copy of the model with included, excluded and updated fields as specified.

Return type:

Self

dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)
Return type:

Dict[str, Any]

classmethod from_orm(obj)
Return type:

Self

json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)
Return type:

str

model_computed_fields = {}
model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod model_construct(_fields_set=None, **values)

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

  • _fields_set (set[str] | None) – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

  • values (Any) – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

Return type:

Self

model_copy(*, update=None, deep=False)
!!! abstract “Usage Documentation”

[model_copy](../concepts/models.md#model-copy)

Returns a copy of the model.

!!! note

The underlying instance’s [__dict__][object.__dict__] attribute is copied. This might have unexpected side effects if you store anything in it, on top of the model fields (e.g. the value of [cached properties][functools.cached_property]).

Parameters:

  • update (Mapping[str, Any] | None) – Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data.

  • deep (bool) – Set to True to make a deep copy of the model.

Returns:

New model instance.

Return type:

Self

model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, exclude_computed_fields=False, round_trip=False, warnings=True, fallback=None, serialize_as_any=False, polymorphic_serialization=None)
!!! abstract “Usage Documentation”

[model_dump](../concepts/serialization.md#python-mode)

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

  • mode (Literal['json', 'python'] | str) – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.

  • include (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – A set of fields to include in the output.

  • exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – A set of fields to exclude from the output.

  • context (Any | None) – Additional context to pass to the serializer.

  • by_alias (bool | None) – Whether to use the field’s alias in the dictionary key if defined.

  • exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

  • exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

  • exclude_none (bool) – Whether to exclude fields that have a value of None.

  • exclude_computed_fields (bool) – Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.

  • round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

  • warnings (bool | Literal['none', 'warn', 'error']) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

  • fallback (Callable[[Any], Any] | None) – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

  • serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

  • polymorphic_serialization (bool | None) – Whether to use model and dataclass polymorphic serialization for this call.

Returns:

A dictionary representation of the model.

Return type:

dict[str, Any]

model_dump_json(*, indent=None, ensure_ascii=False, include=None, exclude=None, context=None, by_alias=None, exclude_unset=False, exclude_defaults=False, exclude_none=False, exclude_computed_fields=False, round_trip=False, warnings=True, fallback=None, serialize_as_any=False, polymorphic_serialization=None)
!!! abstract “Usage Documentation”

[model_dump_json](../concepts/serialization.md#json-mode)

Generates a JSON representation of the model using Pydantic’s to_json method.

Parameters:

  • indent (int | None) – Indentation to use in the JSON output. If None is passed, the output will be compact.

  • ensure_ascii (bool) – If True, the output is guaranteed to have all incoming non-ASCII characters escaped. If False (the default), these characters will be output as-is.

  • include (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – Field(s) to include in the JSON output.

  • exclude (set[int] | set[str] | Mapping[int, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | Mapping[str, set[int] | set[str] | Mapping[int, IncEx | bool] | Mapping[str, IncEx | bool] | bool] | None) – Field(s) to exclude from the JSON output.

  • context (Any | None) – Additional context to pass to the serializer.

  • by_alias (bool | None) – Whether to serialize using field aliases.

  • exclude_unset (bool) – Whether to exclude fields that have not been explicitly set.

  • exclude_defaults (bool) – Whether to exclude fields that are set to their default value.

  • exclude_none (bool) – Whether to exclude fields that have a value of None.

  • exclude_computed_fields (bool) – Whether to exclude computed fields. While this can be useful for round-tripping, it is usually recommended to use the dedicated round_trip parameter instead.

  • round_trip (bool) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].

  • warnings (bool | Literal['none', 'warn', 'error']) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].

  • fallback (Callable[[Any], Any] | None) – A function to call when an unknown value is encountered. If not provided, a [PydanticSerializationError][pydantic_core.PydanticSerializationError] error is raised.

  • serialize_as_any (bool) – Whether to serialize fields with duck-typing serialization behavior.

  • polymorphic_serialization (bool | None) – Whether to use model and dataclass polymorphic serialization for this call.

Returns:

A JSON string representation of the model.

Return type:

str

property model_extra: dict[str, Any] | None

Get extra fields set during validation.

Returns:

A dictionary of extra fields, or None if config.extra is not set to “allow”.

model_fields = {'coach_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of coaches on the team.'), 'created_at': FieldInfo(annotation=datetime, required=True, description='When the team was created.'), 'division_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Division identifier if team belongs to a division.'), 'id': FieldInfo(annotation=str, required=True, description='Team identifier (string in JSON:API).'), 'invitation_code': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Invitation code for joining the team.'), 'logo': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='URL to the team logo image.'), 'player_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of players on the team.'), 'season_id': FieldInfo(annotation=str, required=True, description='Parent season identifier.'), 'title': FieldInfo(annotation=str, required=True, description='Team name/title.'), 'updated_at': FieldInfo(annotation=datetime, required=True, description='Last time the team was updated.')}
property model_fields_set: set[str]

Returns the set of fields that have been explicitly set on this model instance.

Returns:

A set of strings representing the fields that have been set,

i.e. that were not filled from defaults.

classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation', *, union_format='any_of')

Generates a JSON schema for a model class.

Parameters:

  • by_alias (bool) – Whether to use attribute aliases or not.

  • ref_template (str) – The reference template.

  • union_format (Literal['any_of', 'primitive_type_array']) –

    The format to use when combining schemas from unions together. Can be one of:

    keyword to combine schemas (the default). - ‘primitive_type_array’: Use the [type](https://json-schema.org/understanding-json-schema/reference/type) keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive type (string, boolean, null, integer or number) or contains constraints/metadata, falls back to any_of.

  • schema_generator (type[GenerateJsonSchema]) – To override the logic used to generate the JSON schema, as a subclass of GenerateJsonSchema with your desired modifications

  • mode (Literal['validation', 'serialization']) – The mode in which to generate the schema.

Returns:

The JSON schema for the given model class.

Return type:

dict[str, Any]

classmethod model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

params (tuple[type[Any], ...]) – Tuple of types of the class. Given a generic class Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.

Returns:

String representing the new class where params are passed to cls as type variables.

Raises:

TypeError – Raised when trying to generate concrete names for non-generic models.

Return type:

str

model_post_init(context, /)

Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)

Try to rebuild the pydantic-core schema for the model.

This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.

Parameters:

  • force (bool) – Whether to force the rebuilding of the model schema, defaults to False.

  • raise_errors (bool) – Whether to raise errors, defaults to True.

  • _parent_namespace_depth (int) – The depth level of the parent namespace, defaults to 2.

  • _types_namespace (MappingNamespace | None) – The types namespace, defaults to None.

Returns:

Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.

Return type:

bool | None

classmethod model_validate(obj, *, strict=None, extra=None, from_attributes=None, context=None, by_alias=None, by_name=None)

Validate a pydantic model instance.

Parameters:

  • obj (Any) – The object to validate.

  • strict (bool | None) – Whether to enforce types strictly.

  • extra (Literal['allow', 'ignore', 'forbid'] | None) – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.

  • from_attributes (bool | None) – Whether to extract data from object attributes.

  • context (Any | None) – Additional context to pass to the validator.

  • by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

  • by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Raises:

ValidationError – If the object could not be validated.

Returns:

The validated model instance.

Return type:

Self

classmethod model_validate_json(json_data, *, strict=None, extra=None, context=None, by_alias=None, by_name=None)
!!! abstract “Usage Documentation”

[JSON Parsing](../concepts/json.md#json-parsing)

Validate the given JSON data against the Pydantic model.

Parameters:

  • json_data (str | bytes | bytearray) – The JSON data to validate.

  • strict (bool | None) – Whether to enforce types strictly.

  • extra (Literal['allow', 'ignore', 'forbid'] | None) – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.

  • context (Any | None) – Extra variables to pass to the validator.

  • by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

  • by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

Raises:

ValidationError – If json_data is not a JSON string or the object could not be validated.

Return type:

Self

classmethod model_validate_strings(obj, *, strict=None, extra=None, context=None, by_alias=None, by_name=None)

Validate the given object with string data against the Pydantic model.

Parameters:

  • obj (Any) – The object containing string data to validate.

  • strict (bool | None) – Whether to enforce types strictly.

  • extra (Literal['allow', 'ignore', 'forbid'] | None) – Whether to ignore, allow, or forbid extra data during model validation. See the [extra configuration value][pydantic.ConfigDict.extra] for details.

  • context (Any | None) – Extra variables to pass to the validator.

  • by_alias (bool | None) – Whether to use the field’s alias when validating against the provided input data.

  • by_name (bool | None) – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

Return type:

Self

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)
Return type:

Self

classmethod parse_obj(obj)
Return type:

Self

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)
Return type:

Self

classmethod schema(by_alias=True, ref_template='#/$defs/{model}')
Return type:

Dict[str, Any]

classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)
Return type:

str

classmethod update_forward_refs(**localns)
classmethod validate(value)
Return type:

Self

gamesheet_sdk.admin.teams.list_teams(session, season_id)[source]

Return every team in the specified season.

The supplied Session must already carry a bearer token (e.g. via Session.set_bearer_token()); the call is otherwise unauthenticated and will 401.

Parameters:

  • session (Session) – An authenticated Session.

  • season_id (str) – The season identifier whose teams to list.

Returns:

list[Team] –

A list of Team, in the order the server returned them. The list may be empty if

the season has no teams.

Return type:

list[Team]

gamesheet_sdk.admin.teams.get_team(session, season_id, team_id)[source]

Get a single team by ID.

The supplied Session must already carry a bearer token (e.g. via Session.set_bearer_token()); the call is otherwise unauthenticated and will 401.

Parameters:

  • session (Session) – An authenticated Session.

  • season_id (str) – The parent season identifier.

  • team_id (str) – The team identifier to retrieve.

Returns:

Team – The Team with the specified ID.

Raises:

GameSheetError – If the team is not found or for any other non-2xx response from the API.

Return type:

Team

Notes

The single-team GET endpoint doesn’t support including related invitations, so this function fetches all teams in the season (which does include invitations) and filters to the requested team. This ensures invitation_code is populated.

gamesheet_sdk.admin.teams.update_team(session, season_id, team_id, *, title=None, external_id=None, division_id=None, logo_path=None, remove_logo=False)[source]

Update an existing team.

The supplied Session must already carry a bearer token (e.g. via Session.set_bearer_token()); the call is otherwise unauthenticated and will 401. At least one field must be provided for update. The API requires sending the full team data, so this function first fetches the current team to preserve unchanged fields.

Parameters:

  • session (Session) – An authenticated Session.

  • season_id (str) – The season identifier containing the team.

  • team_id (str) – The team identifier to update.

  • title (str | None) – Optional new team name/title.

  • external_id (str | None) – Optional new external identifier.

  • division_id (str | None) – Optional new division identifier.

  • logo_path (str | None) – Optional path to a new logo image file.

  • remove_logo (bool) – If True, remove the team’s logo.

Returns:

Team – The updated Team.

Raises:
Return type:

Team

gamesheet_sdk.admin.teams.create_team(session, season_id, title, division_id, *, external_id=None, logo_path=None)[source]

Create a new team within the specified season.

This operation requires three sequential POSTs: 1. Request an upload URL for the logo (if logo_path is provided) 2. Upload the logo to the returned URL (if logo_path is provided) 3. Create the team with the logo URL

Parameters:

  • session (Session) – An authenticated Session.

  • season_id (str) – The season identifier to create the team in.

  • title (str) – The team name/title.

  • division_id (str) – The division identifier the team belongs to.

  • external_id (str | None) – Optional external identifier for the team.

  • logo_path (str | None) – Optional path to a local logo image file.

Returns:

dict[str, Any] – The server’s response containing prototeam, seasonTeam, member, and invitation data.

Raises:
Return type:

dict[str, Any]

gamesheet_sdk.admin.teams.delete_team(session, season_id, team_id)[source]

Delete a team.

The supplied Session must already carry a bearer token (e.g. via Session.set_bearer_token()); the call is otherwise unauthenticated and will 401.

Parameters:

  • session (Session) – An authenticated Session.

  • season_id (str) – The season identifier containing the team.

  • team_id (str) – The team identifier to delete.

Raises:

  • AuthenticationError – If the server returns 401 (the bearer is missing, malformed, or expired – run gamesheet-admin login to refresh).

  • GameSheetError – For any other non-2xx response.