yaml2plot.PlotSpec

class yaml2plot.PlotSpec(**data)[source]

Pydantic-based plot specification with fluent API.

Replaces PlotConfig with structured validation and composable workflow.

__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.

Methods

__init__(**data)

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

construct([_fields_set])

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

dict(*[, include, exclude, by_alias, ...])

from_file(file_path)

Create PlotSpec from YAML file.

from_orm(obj)

from_yaml(yaml_str)

Create PlotSpec from YAML string.

json(*[, include, exclude, by_alias, ...])

model_construct([_fields_set])

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

model_copy(*[, update, deep])

!!! abstract "Usage Documentation"

model_dump(*[, mode, include, exclude, ...])

!!! abstract "Usage Documentation"

model_dump_json(*[, indent, include, ...])

!!! abstract "Usage Documentation"

model_json_schema([by_alias, ref_template, ...])

Generates a JSON schema for a model class.

model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

model_post_init(context, /)

Override this method to perform additional initialization after __init__ and model_construct.

model_rebuild(*[, force, raise_errors, ...])

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

model_validate(obj, *[, strict, ...])

Validate a pydantic model instance.

model_validate_json(json_data, *[, strict, ...])

!!! abstract "Usage Documentation"

model_validate_strings(obj, *[, strict, ...])

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

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

to_dict()

Export clean configuration dictionary for v1.0.0 plotting functions.

update_forward_refs(**localns)

validate(value)

Attributes

model_computed_fields

model_config

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

model_extra

Get extra fields set during validation.

model_fields

model_fields_set

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

x

y

title

raw

width

height

theme

title_x

title_xanchor

show_legend

grid

show_rangeslider

x: XAxisSpec
y: List[YAxisSpec]
title: Optional[str]
raw: Optional[str]
width: Optional[int]
height: Optional[int]
theme: Optional[str]
title_x: float
title_xanchor: str
show_legend: bool
grid: bool
show_rangeslider: bool
model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

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

classmethod from_yaml(yaml_str)[source]

Create PlotSpec from YAML string.

Return type:

PlotSpec

classmethod from_file(file_path)[source]

Create PlotSpec from YAML file.

Parameters:

file_path (Union[str, Path]) – Path to YAML configuration file

Return type:

PlotSpec

Returns:

PlotSpec instance

Raises:
to_dict()[source]

Export clean configuration dictionary for v1.0.0 plotting functions.

Return type:

Dict[str, Any]

Returns:

Dict containing clean configuration suitable for standalone plotting functions