timelink.api package

for structure of this directory see https://fastapi.tiangolo.com/tutorial/sql-databases/

Subpackages

Submodules

timelink.api.crud module

CRUD operations for the timelink API.

timelink.api.crud.get(db: Session, id: str) → EntityAttrRelSchema[source]

Get entity by id :param db: database session :param id: entity id

Returns:

Entity object

timelink.api.crud.get_syslog(db: Session, nlogs: int) → list[SysLog][source]

Get last n system logs last one first :param db: database session :param nlogs: sequence number

Returns:

List of SysLog objects

timelink.api.crud.get_syslog_by_time(db: Session, start_time: datetime, end_time: datetime) → list[SysLog][source]

Get system logs between start_time and end_time :param db: database session :param start_time: start time :param end_time: end time

Returns:

List of SysLog objects

timelink.api.crud.get_syspar(db: Session, q: list[str] | None = None)[source]

Get system parameters :param db: database session :param q: parameter name(s); if empty, return all parameters

Returns:

SysPar object

timelink.api.crud.set_syslog(db: Session, log: SysLogCreateSchema) → SysLog[source]

Set system log :param db: database session :param log: SysLogCreateSchema object with level, origin and message

Returns:

SysLog object

timelink.api.crud.set_syspar(db: Session, syspar: SysParSchema)[source]

Set system parameters :param db: database session :param syspar: SysPar object

Returns:

SysPar object

timelink.api.schemas module

Schemas for the Timelink API

In the FastAPi tutorial this file is used for the pydantic models for the API, including for the classes that are used for database access. Another file, called models.py, is used in the tutorial for the SQLAlchemy models.

We use a module called “models” for the SQLAlchemy models

Here we put the pydantic models that are not related to database models like search requests and search results.

class timelink.api.schemas.AttributeSchema(*, entity: str, the_type: str, the_value: str, the_date: str, obs: str | None, groupname: str = None)[source]

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'entity': FieldInfo(annotation=str, required=True), 'groupname': FieldInfo(annotation=str, required=False), 'obs': FieldInfo(annotation=Union[str, NoneType], required=True), 'the_date': FieldInfo(annotation=str, required=True), 'the_type': FieldInfo(annotation=str, required=True), 'the_value': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.EntityAttrRelSchema(*, id: str, pom_class: str, inside: str | None, the_order: int | None, the_level: int | None, the_line: int | None, groupname: str | None, updated: datetime | None, indexed: datetime | None, attributes: List[AttributeSchema] | None, rels_in: List[RelationInSchema] | None, rels_out: List[RelationOutSchema] | None, contains: List[EntityBriefSchema] | None)[source]

Pydantic Schema for Entity with attributes and relations

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'attributes': FieldInfo(annotation=Union[List[AttributeSchema], NoneType], required=True), 'contains': FieldInfo(annotation=Union[List[EntityBriefSchema], NoneType], required=True), 'groupname': FieldInfo(annotation=Union[str, NoneType], required=True), 'id': FieldInfo(annotation=str, required=True), 'indexed': FieldInfo(annotation=Union[datetime, NoneType], required=True), 'inside': FieldInfo(annotation=Union[str, NoneType], required=True), 'pom_class': FieldInfo(annotation=str, required=True), 'rels_in': FieldInfo(annotation=Union[List[RelationInSchema], NoneType], required=True), 'rels_out': FieldInfo(annotation=Union[List[RelationOutSchema], NoneType], required=True), 'the_level': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_line': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_order': FieldInfo(annotation=Union[int, NoneType], required=True), 'updated': FieldInfo(annotation=Union[datetime, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.EntityBriefSchema(*, id: str, pom_class: str, inside: str | None, the_order: int | None, the_level: int | None, the_line: int | None, groupname: str | None, updated: datetime | None, indexed: datetime | None)[source]

Pydantic Schema for Entity brief

No links to other entities

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'groupname': FieldInfo(annotation=Union[str, NoneType], required=True), 'id': FieldInfo(annotation=str, required=True), 'indexed': FieldInfo(annotation=Union[datetime, NoneType], required=True), 'inside': FieldInfo(annotation=Union[str, NoneType], required=True), 'pom_class': FieldInfo(annotation=str, required=True), 'the_level': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_line': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_order': FieldInfo(annotation=Union[int, NoneType], required=True), 'updated': FieldInfo(annotation=Union[datetime, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.EntitySchema(*, id: str, pom_class: str, inside: str | None, the_order: int | None, the_level: int | None, the_line: int | None, groupname: str | None, updated: datetime | None, indexed: datetime | None, contains: List[EntitySchema] | None)[source]

Pydantic Schema for Entity

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'contains': FieldInfo(annotation=Union[List[EntitySchema], NoneType], required=True), 'groupname': FieldInfo(annotation=Union[str, NoneType], required=True), 'id': FieldInfo(annotation=str, required=True), 'indexed': FieldInfo(annotation=Union[datetime, NoneType], required=True), 'inside': FieldInfo(annotation=Union[str, NoneType], required=True), 'pom_class': FieldInfo(annotation=str, required=True), 'the_level': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_line': FieldInfo(annotation=Union[int, NoneType], required=True), 'the_order': FieldInfo(annotation=Union[int, NoneType], required=True), 'updated': FieldInfo(annotation=Union[datetime, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.ImportStats(*, datetime: date, machine: str, database: str, file: str, import_time_seconds: float, entities_processed: int, entity_rate: float, person_rate: float, nerrors: int, errors: List[str])[source]

Import statistics

Fields:

datetime: date and time of import machine: machine where import was done database: specific database where import was done file: file that was imported import_time_seconds: time in seconds that import took entities_processed: number of entities processed entity_rate: number of entities processed per second person_rate: number of persons processed per second nerrors: number of errors errors: list of errors

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'database': FieldInfo(annotation=str, required=True), 'datetime': FieldInfo(annotation=date, required=True), 'entities_processed': FieldInfo(annotation=int, required=True), 'entity_rate': FieldInfo(annotation=float, required=True), 'errors': FieldInfo(annotation=List[str], required=True), 'file': FieldInfo(annotation=str, required=True), 'import_time_seconds': FieldInfo(annotation=float, required=True), 'machine': FieldInfo(annotation=str, required=True), 'nerrors': FieldInfo(annotation=int, required=True), 'person_rate': FieldInfo(annotation=float, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.RelationInSchema(*, id: str, origin: str, destination: str, the_type: str, the_value: str, the_date: str, obs: str | None, org_name: str | None)[source]

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'destination': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'obs': FieldInfo(annotation=Union[str, NoneType], required=True), 'org_name': FieldInfo(annotation=Union[str, NoneType], required=True), 'origin': FieldInfo(annotation=str, required=True), 'the_date': FieldInfo(annotation=str, required=True), 'the_type': FieldInfo(annotation=str, required=True), 'the_value': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.RelationOutSchema(*, id: str, origin: str, destination: str, the_type: str, the_value: str, the_date: str, obs: str | None, dest_name: str | None)[source]

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'dest_name': FieldInfo(annotation=Union[str, NoneType], required=True), 'destination': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'obs': FieldInfo(annotation=Union[str, NoneType], required=True), 'origin': FieldInfo(annotation=str, required=True), 'the_date': FieldInfo(annotation=str, required=True), 'the_type': FieldInfo(annotation=str, required=True), 'the_value': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.RelationSchema(*, id: str, origin: str, destination: str, the_type: str, the_value: str, the_date: str, obs: str | None)[source]

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'from_attributes': True}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'destination': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'obs': FieldInfo(annotation=Union[str, NoneType], required=True), 'origin': FieldInfo(annotation=str, required=True), 'the_date': FieldInfo(annotation=str, required=True), 'the_type': FieldInfo(annotation=str, required=True), 'the_value': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.SearchRequest(*, q: str, after: date | None = None, until: date | None = None, skip: int | None = 0, limit: int | None = 100)[source]

Search request

Fields:

q: search query after: date after which to search, possibly None until: date until which to search, possibly None skip: number of items to skip, default 0 limit: number of items to return, default 100

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'after': FieldInfo(annotation=Union[date, NoneType], required=False), 'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=100), 'q': FieldInfo(annotation=str, required=True), 'skip': FieldInfo(annotation=Union[int, NoneType], required=False, default=0), 'until': FieldInfo(annotation=Union[date, NoneType], required=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class timelink.api.schemas.SearchResults(*, id: str, the_class: str, description: str, start_date: date, end_date: date)[source]

Search results

Fields:

results: list of search results

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_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

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

model_fields: ClassVar[dict[str, FieldInfo]] = {'description': FieldInfo(annotation=str, required=True), 'end_date': FieldInfo(annotation=date, required=True), 'id': FieldInfo(annotation=str, required=True), 'start_date': FieldInfo(annotation=date, required=True), 'the_class': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

timelink.api.views module

class timelink.api.views.CreateView(name, selectable)[source]
class timelink.api.views.DropView(name)[source]
timelink.api.views.view(name, metadata, selectable)[source]

Create a view with the given name from the given selectable. The view is created when the metadata is first bound to an engine.

Example

stuff_view = view( “stuff_view”, metadata, sa.select(

stuff.c.id.label(“id”), stuff.c.data.label(“data”), more_stuff.c.data.label(“moredata”),

) .select_from(stuff.join(more_stuff)) .where(stuff.c.data.like((“%orange%”))), )

with engine.connect() as conn:
conn.execute(

sa.select(stuff_view.c.data, stuff_view.c.moredata) ).all()