gamesheet_sdk.teams

Teams dashboard SDK for GameSheet.

Functions

list_lookups(*[, timeout])

Fetch all lookup categories from the teams API.

refresh_access_token(refresh_token, *[, timeout])

Exchange a refresh token for a fresh {access, refresh} pair via the teams API gateway.

Classes

LookupValue

A single value within a lookup category.

TeamsAuthenticatedSession

Teams-pillar session that refreshes via the teams API gateway.

TeamsLoginFlow

HTTP-based LoginFlow for the teams dashboard.
class gamesheet_sdk.teams.LookupValue[source]

Bases: BaseModel

A single value within a lookup category.

All lookup values carry a key. Most also have a title; the few that don’t (e.g. entitlements) default to "". Category-specific fields (abbr, url, sport, scopes, etc.) are preserved via extra="allow" and appear in model_dump() output.

Variables:

  • key – Machine-readable identifier.

  • title – Human-readable display name.

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.

model_config = {'extra': 'allow'}

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

key: str
title: str
__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 = {}
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 = {'key': FieldInfo(annotation=str, required=True, description='Machine-readable identifier.'), 'title': FieldInfo(annotation=str, required=False, default='', description='Human-readable display name.')}
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

class gamesheet_sdk.teams.TeamsAuthenticatedSession[source]

Bases: BaseAuthenticatedSession

Teams-pillar session that refreshes via the teams API gateway.

Delegates to refresh_access_token(), which POSTs to the teams gateway’s /api/auth/refresh endpoint.

Example:

from gamesheet_sdk.common.auth import load_access_token, load_refresh_token, save_tokens
from gamesheet_sdk.teams.session import TeamsAuthenticatedSession
from gamesheet_sdk.common.config import Config

config = Config(base_url="https://teams.gamesheet.app")
with TeamsAuthenticatedSession(
    config,
    access_token=load_access_token(config),
    refresh_token=load_refresh_token(config),
    on_refresh=lambda tokens: save_tokens(config, **tokens),
) as s:
    resp = s.get("/api/seasons/team/123")
    print(resp.json())

Initialize an authenticated session with token auto-refresh on 401/403.

Parameters:

  • config (Config | None) – Optional configuration object. If None, a default Config is created.

  • access_token (str) – Current access token to use as the bearer in the Authorization header.

  • refresh_token (str) – Refresh token used to renew the access token on 401/403 responses.

  • on_refresh (OnRefreshCallback | None) – Optional callback invoked with a token dict after a successful token refresh. Use this to persist the new tokens to disk (e.g. via save_tokens()).

__init__(config=None, *, access_token, refresh_token, on_refresh=None)

Initialize an authenticated session with token auto-refresh on 401/403.

Parameters:

  • config (Config | None) – Optional configuration object. If None, a default Config is created.

  • access_token (str) – Current access token to use as the bearer in the Authorization header.

  • refresh_token (str) – Refresh token used to renew the access token on 401/403 responses.

  • on_refresh (OnRefreshCallback | None) – Optional callback invoked with a token dict after a successful token refresh. Use this to persist the new tokens to disk (e.g. via save_tokens()).

close()

Persist cookies and release the underlying HTTP connection pool.

property cookies: RequestsCookieJar

Underlying cookie jar.

Mutating this affects subsequent requests. :returns: Return value. :rtype: RequestsCookieJar

delete(url, **kwargs)

Send a DELETE request.

See request(). :param url: Absolute URL, or a path relative to Config.base_url. :type url: str :param kwargs: Additional keyword arguments forwarded to request(). :type kwargs: Any :returns: Return value. :rtype: requests.Response

Return type:

Response

get(url, **kwargs)

Send a GET request.

See request(). :param url: Absolute URL, or a path relative to Config.base_url. :type url: str :param kwargs: Additional keyword arguments forwarded to request(). :type kwargs: Any :returns: Return value. :rtype: requests.Response

Return type:

Response

property headers: MutableMapping[str, str | bytes]

Default headers attached to every request from this session.

The underlying mapping is a case-insensitive dict (as supplied by requests.Session), but the declared return type matches the stub for requests.Session.headers. :returns: Return value. :rtype: MutableMapping[str, str | bytes]

patch(url, **kwargs)

Send a PATCH request.

See request(). :param url: Absolute URL, or a path relative to Config.base_url. :type url: str :param kwargs: Additional keyword arguments forwarded to request(). :type kwargs: Any :returns: Return value. :rtype: requests.Response

Return type:

Response

post(url, **kwargs)

Send a POST request.

See request(). :param url: Absolute URL, or a path relative to Config.base_url. :type url: str :param kwargs: Additional keyword arguments forwarded to request(). :type kwargs: Any :returns: Return value. :rtype: requests.Response

Return type:

Response

put(url, **kwargs)

Send a PUT request.

See request(). :param url: Absolute URL, or a path relative to Config.base_url. :type url: str :param kwargs: Additional keyword arguments forwarded to request(). :type kwargs: Any :returns: Return value. :rtype: requests.Response

Return type:

Response

request(method, url, *, timeout=None, **kwargs)

Send a request, refreshing the bearer and retrying once on 401 or 403.

Parameters:

  • method (str) – HTTP method (GET, POST, PUT, DELETE, etc.).

  • url (str) – Target URL for the request.

  • timeout (float | None) – Request timeout in seconds. If None, uses the timeout from config.

  • kwargs (Any) – Additional keyword arguments forwarded to the parent request().

Returns:

HTTP response object from the request. If token refresh fails, returns the original 401/403 response without raising an exception.

Return type:

requests.Response

save()

Persist the current cookie state to Config.session_path.

The on-disk format preserves the full cookie attribute set (domain, path, secure, expires) so that reloaded cookies are sent against the correct scopes.

set_bearer_token(token)

Attach Authorization: Bearer <token> to all subsequent requests.

Convenience for s.headers["Authorization"] = f"Bearer {token}". :param token: The bearer token to attach :type token: str

class gamesheet_sdk.teams.TeamsLoginFlow[source]

Bases: object

HTTP-based LoginFlow for the teams dashboard.

Authenticates via two sequential HTTP calls — Firebase REST signInWithPassword followed by a token exchange against the teams API gateway — without requiring a headless browser.

Example:

from gamesheet_sdk.common.config import Config
from gamesheet_sdk.teams.login import TeamsLoginFlow

config = Config(base_url="https://teams.gamesheet.app")
flow = TeamsLoginFlow(config)
tokens = flow.authenticate(email="user@example.com", password="secret")
print(tokens["access"])

Store the configuration for credential resolution and token persistence.

Parameters:

config (Config) – SDK configuration (credentials, URLs, storage paths).

__init__(config)[source]

Store the configuration for credential resolution and token persistence.

Parameters:

config (Config) – SDK configuration (credentials, URLs, storage paths).

authenticate(email=None, password=None, *, timeout=None)[source]

Run the HTTP-only teams login and return tokens.

Resolves credentials from the arguments or Config, authenticates with Firebase, exchanges the ID token for application tokens, and persists them to disk.

Parameters:

  • email (str | None) – Login email, or None to resolve from config/env.

  • password (str | None) – Login password, or None to resolve from config/env.

  • timeout (float | None) – HTTP request timeout in seconds, or None for the default.

Returns:

Token bundle with "access" and "refresh" keys.

Return type:

dict[str, str]

Raises:

AuthenticationError – If credentials are missing, Firebase rejects them, or the token exchange fails.

gamesheet_sdk.teams.list_lookups(*, timeout=15.0)[source]

Fetch all lookup categories from the teams API.

This is a public endpoint — no authentication is required.

Parameters:

timeout (float) – HTTP request timeout in seconds.

Returns:

Dictionary mapping category names to lists of LookupValue objects.

Return type:

dict[str, list[LookupValue]]

Raises:

GameSheetError – If the server returns a non-2xx status code.

gamesheet_sdk.teams.refresh_access_token(refresh_token, *, timeout=15.0)[source]

Exchange a refresh token for a fresh {access, refresh} pair via the teams API gateway.

POSTs to TEAMS_REFRESH_PATH with Authorization: Bearer <refresh_token> and an empty JSON body. The gateway returns a new access token and a replacement refresh token.

This is a standalone HTTP call that does not use a Session, so it can be called from inside an auto-refresh retry path without recursing.

Parameters:

  • refresh_token (str) – The refresh token to exchange for new tokens.

  • timeout (float) – Request timeout in seconds. Defaults to DEFAULT_TIMEOUT_S.

Returns:

Dictionary with keys access and refresh, each containing the corresponding token string.

Return type:

dict[str, str]

Raises:

  • AuthenticationError – If the refresh token is rejected (HTTP 401). This typically means the token has expired and the user needs to re-authenticate via gamesheet-teams login.

  • GameSheetError – For any other non-2xx HTTP response from the token refresh endpoint.