fiftyone.brain.similarity¶

Similarity interface.

Copyright 2017-2022, Voxel51, Inc.
voxel51.com

Classes:

`SimilarityConfig`([embeddings_field, model, …])	Similarity configuration.
`SimilarityResults`(samples, config, embeddings)	Class storing the results of `fiftyone.brain.compute_similarity()`.

class fiftyone.brain.similarity.SimilarityResults(samples, config, embeddings)¶

Bases: fiftyone.core.brain.BrainResults

Class storing the results of fiftyone.brain.compute_similarity().

Parameters

samples – the fiftyone.core.collections.SampleCollection used
config – the SimilarityConfig used
embeddings – a num_embeddings x num_dims array of embeddings

Methods:

`attributes`()	Returns the list of class attributes that will be serialized by `serialize()`.
`clear_view`()	Clears the view set by `use_view()`, if any.
`copy`()	Returns a deep copy of the object.
`custom_attributes`([dynamic, private])	Returns a customizable list of class attributes.
`duplicates_view`([type_field, id_field, …])	Returns a view that contains only the duplicate examples and their corresponding nearest non-duplicate examples generated by the last call to `find_duplicates()`.
`find_duplicates`([thresh, fraction])	Queries the index to find near-duplicate examples based on the provided parameters.
`find_unique`(count)	Queries the index to select a subset of examples of the specified size that are maximally unique with respect to each other.
`from_dict`(d, samples, config)	Builds a `RunResults` from a JSON dict representation of it.
`from_json`(path, args, *kwargs)	Constructs a Serializable object from a JSON file.
`from_str`(s, args, *kwargs)	Constructs a Serializable object from a JSON string.
`get_class_name`()	Returns the fully-qualified class name string of this object.
`plot_distances`([bins, log, backend])	Plots a histogram of the distance between each example and its nearest neighbor.
`serialize`([reflective])	Serializes the object into a dictionary.
`sort_by_similarity`(query_ids[, k, reverse, …])	Returns a view that sorts the samples/labels in `view()` by visual similarity to the specified query.
`to_str`([pretty_print])	Returns a string representation of this object.
`unique_view`()	Returns a view that contains only the unique examples generated by the last call to `find_duplicates()` or `find_unique()`.
`use_view`(sample_collection[, allow_missing])	Restricts the index to the provided view, which must be a subset of the full index’s collection.
`visualize_duplicates`([visualization, backend])	Generates an interactive scatterplot of the results generated by the last call to `find_duplicates()`.
`visualize_unique`([visualization, backend])	Generates an interactive scatterplot of the results generated by the last call to `find_unique()`.
`write_json`(path[, pretty_print])	Serializes the object and writes it to disk.

Attributes:

`cls`	The fully-qualified name of this `RunResults` class.
`config`	The `SimilarityConfig` for the results.
`duplicate_ids`	A list of duplicate IDs from the last call to `find_duplicates()` or `find_unique()`.
`index_size`	The number of data points in the index.
`missing_size`	The total number of data points in `view()` that are missing from this index.
`neighbors_map`	A dictionary mapping IDs to lists of `(dup_id, dist)` tuples from the last call to `find_duplicates()`.
`thresh`	The threshold used by the last call to `find_duplicates()` or `find_unique()`.
`total_index_size`	The total number of data points in the index.
`unique_ids`	A list of unique IDs from the last call to `find_duplicates()` or `find_unique()`.
`view`	The `fiftyone.core.collections.SampleCollection` against which results are currently being generated.

property config¶: The SimilarityConfig for the results.

property index_size¶

The number of data points in the index.

If use_view() has been called to restrict the index, this property will reflect the size of the active index.

property total_index_size¶

The total number of data points in the index.

If use_view() has been called to restrict the index, this value may be larger than the current index_size().

property missing_size¶

The total number of data points in view() that are missing from this index.

This property is only applicable when use_view() has been called, and it will be None if no data points are missing.

property view¶

The fiftyone.core.collections.SampleCollection against which results are currently being generated.

If use_view() has been called, this view may be a subset of the collection on which the full index was generated.

property thresh¶: The threshold used by the last call to find_duplicates() or find_unique().

property unique_ids¶: A list of unique IDs from the last call to find_duplicates() or find_unique().

property duplicate_ids¶: A list of duplicate IDs from the last call to find_duplicates() or find_unique().

property neighbors_map¶: A dictionary mapping IDs to lists of (dup_id, dist) tuples from the last call to find_duplicates().

use_view(sample_collection, allow_missing=False)¶

Restricts the index to the provided view, which must be a subset of the full index’s collection.

Subsequent calls to methods on this instance will only contain results from the specified view rather than the full index.

Use clear_view() to reset to the full index. Or, equivalently, use the context manager interface as demonstrated below to automatically reset the view when the context exits.

Example usage:

import fiftyone as fo
import fiftyone.brain as fob
import fiftyone.zoo as foz

dataset = foz.load_zoo_dataset("quickstart")

results = fob.compute_similarity(dataset)
print(results.index_size)  # 200

view = dataset.take(50)

with results.use_view(view):
    print(results.index_size)  # 50

    results.find_unique(10)
    print(results.unique_ids)

    plot = results.visualize_unique()
    plot.show()

Parameters

sample_collection – a fiftyone.core.collections.SampleCollection defining a subset of this index to use
allow_missing (False) – whether to allow the provided collection to contain data points that this index does not contain (True) or whether to raise an error in this case (False)

Returns

self

clear_view()¶

Clears the view set by use_view(), if any.

Subsequent operations will be performed on the full index.

plot_distances(bins=100, log=False, backend='plotly', **kwargs)¶

Plots a histogram of the distance between each example and its nearest neighbor.

If :meth:`find_duplicates or find_unique() has been executed, the threshold used is also indicated on the plot.

Parameters

bins (100) – the number of bins to use
log (False) – whether to use a log scale y-axis
backend ("plotly") – the plotting backend to use. Supported values are ("plotly", "matplotlib")
**kwargs – keyword arguments for the backend plotting method

Returns

a fiftyone.core.plots.plotly.PlotlyNotebookPlot, if you are working in a notebook context and the plotly backend is used
a plotly or matplotlib figure, otherwise

Return type

one of the following

sort_by_similarity(query_ids, k=None, reverse=False, aggregation='mean', dist_field=None, _mongo=False)¶

Returns a view that sorts the samples/labels in view() by visual similarity to the specified query.

The query IDs can be any IDs in the full index of this instance, even if the current view() contains a subset of the full index.

Parameters

query_ids – an ID or iterable of query IDs
k (None) – the number of matches to return. By default, all samples/labels are included
reverse (False) – whether to sort by least similarity
aggregation ("mean") – the aggregation method to use to compute composite similarities. Only applicable when query_ids contains multiple IDs. Supported values are ("mean", "min", "max")
dist_field (None) – the name of a float field in which to store the distance of each example to the specified query. The field is created if necessary

Returns

a fiftyone.core.view.DatasetView

find_duplicates(thresh=None, fraction=None)¶

Queries the index to find near-duplicate examples based on the provided parameters.

Calling this method populates the unique_ids(), duplicate_ids(), neighbors_map, and thresh properties of this object with the results of the query.

Use duplicates_view() and visualize_duplicates() to analyze the results generated by this method.

Parameters

thresh (None) – a distance threshold to use to determine duplicates. If specified, the non-duplicate set will be the (approximately) largest set such that all pairwise distances between non-duplicate examples are greater than this threshold
fraction (None) – a desired fraction of images/patches to tag as duplicates, in [0, 1]. In this case thresh is automatically tuned to achieve the desired fraction of duplicates

find_unique(count)¶

Queries the index to select a subset of examples of the specified size that are maximally unique with respect to each other.

Calling this method populates the unique_ids(), duplicate_ids(), and thresh properties of this object with the results of the query.

Use unique_view() and visualize_unique() to analyze the results generated by this method.

Parameters: count – the desired number of unique examples

duplicates_view(type_field=None, id_field=None, dist_field=None, sort_by='distance', reverse=False)¶

Returns a view that contains only the duplicate examples and their corresponding nearest non-duplicate examples generated by the last call to find_duplicates().

If you are analyzing patches, the returned view will be a fiftyone.core.patches.PatchesView.

The examples are organized so that each non-duplicate is immediately followed by all duplicate(s) that are nearest to it.

Parameters

type_field (None) – the name of a string field in which to store "nearest" and "duplicate" labels. The field is created if necessary
id_field (None) – the name of a string field in which to store the ID of the nearest non-duplicate for each example in the view. The field is created if necessary
dist_field (None) – the name of a float field in which to store the distance of each example to its nearest non-duplicate example. The field is created if necessary
sort_by ("distance") –
specifies how to sort the groups of duplicate examples. The supported values are:
- "distance": sort the groups by the distance between the non-duplicate and its (nearest, if multiple) duplicate
- "count": sort the groups by the number of duplicate examples
reverse (False) – whether to sort in descending order

Returns

a fiftyone.core.view.DatasetView

unique_view()¶

Returns a view that contains only the unique examples generated by the last call to find_duplicates() or find_unique().

If you are analyzing patches, the returned view will be a fiftyone.core.patches.PatchesView.

Returns: a fiftyone.core.view.DatasetView

visualize_duplicates(visualization=None, backend='plotly', **kwargs)¶

Generates an interactive scatterplot of the results generated by the last call to find_duplicates().

If provided, the visualization argument can be any visualization computed on the same dataset (or subset of it) as long as it contains every sample/object in the view whose results you are visualizing. If no visualization argument is provided and the embeddings have more than 3 dimensions, a 2D representation of the embeddings is computed via fiftyone.brain.compute_visualization().

The points are colored based on the following partition:

“duplicate”: duplicate example

“nearest”: nearest neighbor of a duplicate example

“unique”: the remaining unique examples

Edges are also drawn between each duplicate and its nearest non-duplicate neighbor.

You can attach plots generated by this method to an App session via its fiftyone.core.session.Session.plots attribute, which will automatically sync the session’s view with the currently selected points in the plot.

Parameters

visualization (None) – a fiftyone.brain.visualization.VisualizationResults instance to use to visualize the results
backend ("plotly") – the plotting backend to use. Supported values are ("plotly", "matplotlib")
**kwargs –
keyword arguments for the backend plotting method:
- ”plotly” backend: fiftyone.core.plots.plotly.scatterplot()
- ”matplotlib” backend: fiftyone.core.plots.matplotlib.scatterplot()

Returns

a fiftyone.core.plots.base.InteractivePlot

visualize_unique(visualization=None, backend='plotly', **kwargs)¶

Generates an interactive scatterplot of the results generated by the last call to find_unique().

If provided, the visualization argument can be any visualization computed on the same dataset (or subset of it) as long as it contains every sample/object in the view whose results you are visualizing. If no visualization argument is provided and the embeddings have more than 3 dimensions, a 2D representation of the embeddings is computed via fiftyone.brain.compute_visualization().

The points are colored based on the following partition:

“unique”: the unique examples

“other”: the other examples

You can attach plots generated by this method to an App session via its fiftyone.core.session.Session.plots attribute, which will automatically sync the session’s view with the currently selected points in the plot.

Parameters

visualization (None) – a fiftyone.brain.visualization.VisualizationResults instance to use to visualize the results
backend ("plotly") – the plotting backend to use. Supported values are ("plotly", "matplotlib")
**kwargs –
keyword arguments for the backend plotting method:
- ”plotly” backend: fiftyone.core.plots.plotly.scatterplot()
- ”matplotlib” backend: fiftyone.core.plots.matplotlib.scatterplot()

Returns

a fiftyone.core.plots.base.InteractivePlot

attributes()¶

Returns the list of class attributes that will be serialized by serialize().

Returns: a list of attributes

property cls¶: The fully-qualified name of this RunResults class.

copy()¶

Returns a deep copy of the object.

Returns: a Serializable instance

custom_attributes(dynamic=False, private=False)¶

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False
private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod from_dict(d, samples, config)¶

Builds a RunResults from a JSON dict representation of it.

Parameters

d – a JSON dict
samples – the fiftyone.core.collections.SampleCollection for the run
config – the RunConfig for the run

Returns

a RunResults

classmethod from_json(path, *args, **kwargs)¶

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

path – the path to the JSON file on disk
*args – optional positional arguments for self.from_dict()
**kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_str(s, *args, **kwargs)¶

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

s – a JSON string representation of a Serializable object
*args – optional positional arguments for self.from_dict()
**kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()¶: Returns the fully-qualified class name string of this object.

serialize(reflective=False)¶

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters: reflective – whether to include reflective attributes when serializing the object. By default, this is False
Returns: a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)¶

Returns a string representation of this object.

Parameters

pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True
**kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

write_json(path, pretty_print=False, **kwargs)¶

Serializes the object and writes it to disk.

Parameters

path – the output path
pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False
**kwargs – optional keyword arguments for self.serialize()

class fiftyone.brain.similarity.SimilarityConfig(embeddings_field=None, model=None, patches_field=None, metric=None, **kwargs)¶

Bases: fiftyone.core.brain.BrainMethodConfig

Similarity configuration.

Parameters

embeddings_field (None) – the sample field containing the embeddings, if one was provided
model (None) – the fiftyone.core.models.Model or class name of the model that was used to compute embeddings, if one was provided
patches_field (None) – the sample field defining the patches being analyzed, if any
metric (None) – the embedding distance metric used

Methods:

`attributes`()	Returns the list of class attributes that will be serialized by `serialize()`.
`build`()	Builds the `Run` instance associated with this config.
`builder`()	Returns a ConfigBuilder instance for this class.
`copy`()	Returns a deep copy of the object.
`custom_attributes`([dynamic, private])	Returns a customizable list of class attributes.
`default`()	Returns the default config instance.
`from_dict`(d)	Constructs a `RunConfig` from a serialized JSON dict representation of it.
`from_json`(path, args, *kwargs)	Constructs a Serializable object from a JSON file.
`from_kwargs`(**kwargs)	Constructs a Config object from keyword arguments.
`from_str`(s, args, *kwargs)	Constructs a Serializable object from a JSON string.
`get_class_name`()	Returns the fully-qualified class name string of this object.
`load_default`()	Loads the default config instance from file.
`parse_array`(d, key[, default])	Parses a raw array attribute.
`parse_bool`(d, key[, default])	Parses a boolean value.
`parse_categorical`(d, key, choices[, default])	Parses a categorical JSON field, which must take a value from among the given choices.
`parse_dict`(d, key[, default])	Parses a dictionary attribute.
`parse_int`(d, key[, default])	Parses an integer attribute.
`parse_mutually_exclusive_fields`(fields)	Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.
`parse_number`(d, key[, default])	Parses a number attribute.
`parse_object`(d, key, cls[, default])	Parses an object attribute.
`parse_object_array`(d, key, cls[, default])	Parses an array of objects.
`parse_object_dict`(d, key, cls[, default])	Parses a dictionary whose values are objects.
`parse_path`(d, key[, default])	Parses a path attribute.
`parse_raw`(d, key[, default])	Parses a raw (arbitrary) JSON field.
`parse_string`(d, key[, default])	Parses a string attribute.
`serialize`([reflective])	Serializes the object into a dictionary.
`to_str`([pretty_print])	Returns a string representation of this object.
`validate_all_or_nothing_fields`(fields)	Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.
`write_json`(path[, pretty_print])	Serializes the object and writes it to disk.

Attributes:

`cls`	The fully-qualified name of this `RunConfig` class.
`method`	The name of the method.
`run_cls`	The `Run` class associated with this config.

property method¶: The name of the method.

property run_cls¶: The Run class associated with this config.

attributes()¶

Returns the list of class attributes that will be serialized by serialize().

Returns: a list of attributes

build()¶

Builds the Run instance associated with this config.

Returns: a Run instance

classmethod builder()¶: Returns a ConfigBuilder instance for this class.

property cls¶: The fully-qualified name of this RunConfig class.

copy()¶

Returns a deep copy of the object.

Returns: a Serializable instance

custom_attributes(dynamic=False, private=False)¶

Returns a customizable list of class attributes.

By default, all attributes in vars(self) are returned, minus private attributes (those starting with “_”).

Parameters

dynamic – whether to include dynamic properties, e.g., those defined by getter/setter methods or the @property decorator. By default, this is False
private – whether to include private properties, i.e., those starting with “_”. By default, this is False

Returns

a list of class attributes

classmethod default()¶

Returns the default config instance.

By default, this method instantiates the class from an empty dictionary, which will only succeed if all attributes are optional. Otherwise, subclasses should override this method to provide the desired default configuration.

classmethod from_dict(d)¶

Constructs a RunConfig from a serialized JSON dict representation of it.

Parameters: d – a JSON dict
Returns: a RunConfig

classmethod from_json(path, *args, **kwargs)¶

Constructs a Serializable object from a JSON file.

Subclasses may override this method, but, by default, this method simply reads the JSON and calls from_dict(), which subclasses must implement.

Parameters

path – the path to the JSON file on disk
*args – optional positional arguments for self.from_dict()
**kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod from_kwargs(**kwargs)¶

Constructs a Config object from keyword arguments.

Parameters: **kwargs – keyword arguments that define the fields expected by cls
Returns: an instance of cls

classmethod from_str(s, *args, **kwargs)¶

Constructs a Serializable object from a JSON string.

Subclasses may override this method, but, by default, this method simply parses the string and calls from_dict(), which subclasses must implement.

Parameters

s – a JSON string representation of a Serializable object
*args – optional positional arguments for self.from_dict()
**kwargs – optional keyword arguments for self.from_dict()

Returns

an instance of the Serializable class

classmethod get_class_name()¶: Returns the fully-qualified class name string of this object.

classmethod load_default()¶

Loads the default config instance from file.

Subclasses must implement this method if they intend to support default instances.

static parse_array(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a raw array attribute.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default list to return if key is not present

Returns

a list of raw (untouched) values

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_bool(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a boolean value.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default bool to return if key is not present

Returns

True/False

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_categorical(d, key, choices, default=<eta.core.config.NoDefault object>)¶

Parses a categorical JSON field, which must take a value from among the given choices.

Parameters

d – a JSON dictionary
key – the key to parse
choices – either an iterable of possible values or an enum-like class whose attributes define the possible values
default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field, which is equal to a value from choices

Raises

ConfigError – if the key was present in the dictionary but its value was not an allowed choice, or if no default value was provided and the key was not found in the dictionary

static parse_dict(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a dictionary attribute.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default dict to return if key is not present

Returns

a dictionary

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_int(d, key, default=<eta.core.config.NoDefault object>)¶

Parses an integer attribute.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default integer value to return if key is not present

Returns

an int

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_mutually_exclusive_fields(fields)¶

Parses a mutually exclusive dictionary of pre-parsed fields, which must contain exactly one field with a truthy value.

Parameters: fields – a dictionary of pre-parsed fields
Returns: the (field, value) that was set
Raises: ConfigError – if zero or more than one truthy value was found

static parse_number(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a number attribute.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default numeric value to return if key is not present

Returns

a number (e.g. int, float)

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object(d, key, cls, default=<eta.core.config.NoDefault object>)¶

Parses an object attribute.

The value of d[key] can be either an instance of cls or a serialized dict from an instance of cls.

Parameters

d – a JSON dictionary
key – the key to parse
cls – the class of d[key]
default – a default cls instance to return if key is not present

Returns

an instance of cls

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_array(d, key, cls, default=<eta.core.config.NoDefault object>)¶

Parses an array of objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

d – a JSON dictionary
key – the key to parse
cls – the class of the elements of list d[key]
default – the default list to return if key is not present

Returns

a list of cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_object_dict(d, key, cls, default=<eta.core.config.NoDefault object>)¶

Parses a dictionary whose values are objects.

The values in d[key] can be either instances of cls or serialized dicts from instances of cls.

Parameters

d – a JSON dictionary
key – the key to parse
cls – the class of the values of dictionary d[key]
default – the default dict of cls instances to return if key is not present

Returns

a dictionary whose values are cls instances

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_path(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a path attribute.

The path is converted to an absolute path if necessary via os.path.abspath(os.path.expanduser(value)).

Parameters

d – a JSON dictionary
key – the key to parse
default – a default string to return if key is not present

Returns

a path string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

static parse_raw(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a raw (arbitrary) JSON field.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default value to return if key is not present

Returns

the raw (untouched) value of the given field

Raises

ConfigError – if no default value was provided and the key was not found in the dictionary

static parse_string(d, key, default=<eta.core.config.NoDefault object>)¶

Parses a string attribute.

Parameters

d – a JSON dictionary
key – the key to parse
default – a default string to return if key is not present

Returns

a string

Raises

ConfigError – if the field value was the wrong type or no default value was provided and the key was not found in the dictionary

serialize(reflective=False)¶

Serializes the object into a dictionary.

Serialization is applied recursively to all attributes in the object, including element-wise serialization of lists and dictionary values.

Parameters: reflective – whether to include reflective attributes when serializing the object. By default, this is False
Returns: a JSON dictionary representation of the object

to_str(pretty_print=True, **kwargs)¶

Returns a string representation of this object.

Parameters

pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is True
**kwargs – optional keyword arguments for self.serialize()

Returns

a string representation of the object

static validate_all_or_nothing_fields(fields)¶

Validates a dictionary of pre-parsed fields checking that either all or none of the fields have a truthy value.

Parameters: fields – a dictionary of pre-parsed fields
Raises: ConfigError – if some values are truth and some are not

write_json(path, pretty_print=False, **kwargs)¶

Serializes the object and writes it to disk.

Parameters

path – the output path
pretty_print – whether to render the JSON in human readable format with newlines and indentations. By default, this is False
**kwargs – optional keyword arguments for self.serialize()