meerkat.interactive.app.src.lib.component.core.Gallery

class Gallery(df: meerkat.dataframe.DataFrame, *, main_column: str = None, tag_columns: List[str] = None, selected: List[int] = [], allow_selection: bool = False, cell_size: int = 24, per_page: int = 20, page: int = 0)

__init__(df: meerkat.dataframe.DataFrame, *, main_column: Optional[str] = None, tag_columns: Optional[List[str]] = None, selected: List[int] = [], allow_selection: bool = False, cell_size: int = 24, per_page: int = 20, page: int = 0)

Gallery view of a DataFrame.

Parameters

• df (DataFrame) – The DataFrame to display.

• main_column (str) – The column to display in the main gallery view.

• tag_columns (List[str], optional) – The columns to display as tags. Defaults to [].

• selected (List[int], optional) – The indices of the rows selected in the gallery. Useful for labeling and other tasks. Defaults to [].

• allow_selection (bool, optional) – Whether to allow the user to select rows. Defaults to False.

• per_page (int, optional) – The number of rows to display per page.

Methods

__init__(df, *[, main_column, tag_columns, ...])	Gallery view of a DataFrame.
append(other)
construct([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy(*[, include, exclude, update, deep])	Duplicate a model, optionally choose which fields to include, exclude and change.
dict(*[, include, exclude, by_alias, ...])	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
from_id(id)
from_orm(obj)
get_components()
json(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
prepend_meerkat_id_prefix(id)
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate(value)

Attributes

alias
component_name
event_names
events
frontend	Returns a Pydantic model that can be should be sent to the frontend.
frontend_alias
id
identifiable_group
library
namespace
path
prop_bindings
prop_names
props
slots
slottable
virtual_props	Props, and all events (as_*) as props.
wrapper_import_style
df
main_column
tag_columns
selected
allow_selection
cell_size
per_page