601 lines
18 KiB
Python
601 lines
18 KiB
Python
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import json
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import decimal
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import datetime
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import warnings
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from pathlib import Path
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from plotly.io._utils import validate_coerce_fig_to_dict, validate_coerce_output_type
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from _plotly_utils.optional_imports import get_module
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from _plotly_utils.basevalidators import ImageUriValidator
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# Orca configuration class
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# ------------------------
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class JsonConfig(object):
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_valid_engines = ("json", "orjson", "auto")
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def __init__(self):
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self._default_engine = "auto"
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@property
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def default_engine(self):
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return self._default_engine
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@default_engine.setter
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def default_engine(self, val):
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if val not in JsonConfig._valid_engines:
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raise ValueError(
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"Supported JSON engines include {valid}\n"
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" Received {val}".format(valid=JsonConfig._valid_engines, val=val)
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)
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if val == "orjson":
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self.validate_orjson()
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self._default_engine = val
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@classmethod
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def validate_orjson(cls):
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orjson = get_module("orjson")
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if orjson is None:
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raise ValueError("The orjson engine requires the orjson package")
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config = JsonConfig()
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def coerce_to_strict(const):
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"""
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This is used to ultimately *encode* into strict JSON, see `encode`
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"""
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# before python 2.7, 'true', 'false', 'null', were include here.
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if const in ("Infinity", "-Infinity", "NaN"):
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return None
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else:
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return const
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_swap_json = (
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("<", "\\u003c"),
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(">", "\\u003e"),
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("/", "\\u002f"),
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)
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_swap_orjson = _swap_json + (
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("\u2028", "\\u2028"),
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("\u2029", "\\u2029"),
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)
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def _safe(json_str, _swap):
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out = json_str
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for unsafe_char, safe_char in _swap:
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if unsafe_char in out:
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out = out.replace(unsafe_char, safe_char)
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return out
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def to_json_plotly(plotly_object, pretty=False, engine=None):
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"""
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Convert a plotly/Dash object to a JSON string representation
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Parameters
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----------
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plotly_object:
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A plotly/Dash object represented as a dict, graph_object, or Dash component
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pretty: bool (default False)
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True if JSON representation should be pretty-printed, False if
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representation should be as compact as possible.
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engine: str (default None)
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The JSON encoding engine to use. One of:
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- "json" for an engine based on the built-in Python json module
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- "orjson" for a faster engine that requires the orjson package
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- "auto" for the "orjson" engine if available, otherwise "json"
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If not specified, the default engine is set to the current value of
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plotly.io.json.config.default_engine.
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Returns
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-------
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str
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Representation of input object as a JSON string
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See Also
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--------
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to_json : Convert a plotly Figure to JSON with validation
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"""
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orjson = get_module("orjson", should_load=True)
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# Determine json engine
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if engine is None:
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engine = config.default_engine
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if engine == "auto":
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if orjson is not None:
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engine = "orjson"
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else:
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engine = "json"
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elif engine not in ["orjson", "json"]:
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raise ValueError("Invalid json engine: %s" % engine)
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modules = {
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"sage_all": get_module("sage.all", should_load=False),
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"np": get_module("numpy", should_load=False),
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"pd": get_module("pandas", should_load=False),
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"image": get_module("PIL.Image", should_load=False),
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}
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# Dump to a JSON string and return
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# --------------------------------
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if engine == "json":
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opts = {}
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if pretty:
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opts["indent"] = 2
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else:
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# Remove all whitespace
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opts["separators"] = (",", ":")
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from _plotly_utils.utils import PlotlyJSONEncoder
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return _safe(
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json.dumps(plotly_object, cls=PlotlyJSONEncoder, **opts), _swap_json
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)
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elif engine == "orjson":
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JsonConfig.validate_orjson()
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opts = orjson.OPT_NON_STR_KEYS | orjson.OPT_SERIALIZE_NUMPY
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if pretty:
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opts |= orjson.OPT_INDENT_2
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# Plotly
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try:
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plotly_object = plotly_object.to_plotly_json()
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except AttributeError:
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pass
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# Try without cleaning
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try:
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return _safe(
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orjson.dumps(plotly_object, option=opts).decode("utf8"), _swap_orjson
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)
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except TypeError:
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pass
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cleaned = clean_to_json_compatible(
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plotly_object,
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numpy_allowed=True,
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datetime_allowed=True,
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modules=modules,
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)
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return _safe(orjson.dumps(cleaned, option=opts).decode("utf8"), _swap_orjson)
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def to_json(fig, validate=True, pretty=False, remove_uids=True, engine=None):
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"""
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Convert a figure to a JSON string representation
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Parameters
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----------
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fig:
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Figure object or dict representing a figure
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validate: bool (default True)
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True if the figure should be validated before being converted to
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JSON, False otherwise.
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pretty: bool (default False)
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True if JSON representation should be pretty-printed, False if
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representation should be as compact as possible.
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remove_uids: bool (default True)
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True if trace UIDs should be omitted from the JSON representation
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engine: str (default None)
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The JSON encoding engine to use. One of:
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- "json" for an engine based on the built-in Python json module
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- "orjson" for a faster engine that requires the orjson package
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- "auto" for the "orjson" engine if available, otherwise "json"
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If not specified, the default engine is set to the current value of
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plotly.io.json.config.default_engine.
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Returns
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-------
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str
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Representation of figure as a JSON string
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See Also
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--------
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to_json_plotly : Convert an arbitrary plotly graph_object or Dash component to JSON
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"""
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# Validate figure
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# ---------------
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fig_dict = validate_coerce_fig_to_dict(fig, validate)
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# Remove trace uid
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# ----------------
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if remove_uids:
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for trace in fig_dict.get("data", []):
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trace.pop("uid", None)
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return to_json_plotly(fig_dict, pretty=pretty, engine=engine)
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def write_json(fig, file, validate=True, pretty=False, remove_uids=True, engine=None):
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"""
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Convert a figure to JSON and write it to a file or writeable
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object
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Parameters
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----------
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fig:
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Figure object or dict representing a figure
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file: str or writeable
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A string representing a local file path or a writeable object
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(e.g. a pathlib.Path object or an open file descriptor)
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pretty: bool (default False)
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True if JSON representation should be pretty-printed, False if
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representation should be as compact as possible.
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remove_uids: bool (default True)
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True if trace UIDs should be omitted from the JSON representation
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engine: str (default None)
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The JSON encoding engine to use. One of:
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- "json" for an engine based on the built-in Python json module
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- "orjson" for a faster engine that requires the orjson package
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- "auto" for the "orjson" engine if available, otherwise "json"
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If not specified, the default engine is set to the current value of
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plotly.io.json.config.default_engine.
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Returns
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-------
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None
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"""
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# Get JSON string
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# ---------------
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# Pass through validate argument and let to_json handle validation logic
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json_str = to_json(
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fig, validate=validate, pretty=pretty, remove_uids=remove_uids, engine=engine
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)
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# Try to cast `file` as a pathlib object `path`.
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# ----------------------------------------------
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if isinstance(file, str):
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# Use the standard Path constructor to make a pathlib object.
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path = Path(file)
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elif isinstance(file, Path):
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# `file` is already a Path object.
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path = file
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else:
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# We could not make a Path object out of file. Either `file` is an open file
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# descriptor with a `write()` method or it's an invalid object.
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path = None
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# Open file
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# ---------
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if path is None:
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# We previously failed to make sense of `file` as a pathlib object.
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# Attempt to write to `file` as an open file descriptor.
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try:
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file.write(json_str)
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return
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except AttributeError:
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pass
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raise ValueError(
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"""
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The 'file' argument '{file}' is not a string, pathlib.Path object, or file descriptor.
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""".format(
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file=file
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)
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)
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else:
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# We previously succeeded in interpreting `file` as a pathlib object.
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# Now we can use `write_bytes()`.
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path.write_text(json_str)
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def from_json_plotly(value, engine=None):
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"""
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Parse JSON string using the specified JSON engine
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Parameters
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----------
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value: str or bytes
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A JSON string or bytes object
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engine: str (default None)
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The JSON decoding engine to use. One of:
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- if "json", parse JSON using built in json module
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- if "orjson", parse using the faster orjson module, requires the orjson
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package
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- if "auto" use orjson module if available, otherwise use the json module
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If not specified, the default engine is set to the current value of
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plotly.io.json.config.default_engine.
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Returns
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-------
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dict
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See Also
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--------
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from_json_plotly : Parse JSON with plotly conventions into a dict
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"""
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orjson = get_module("orjson", should_load=True)
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# Validate value
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# --------------
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if not isinstance(value, (str, bytes)):
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raise ValueError(
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"""
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from_json_plotly requires a string or bytes argument but received value of type {typ}
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Received value: {value}""".format(
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typ=type(value), value=value
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)
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)
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# Determine json engine
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if engine is None:
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engine = config.default_engine
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if engine == "auto":
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if orjson is not None:
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engine = "orjson"
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else:
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engine = "json"
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elif engine not in ["orjson", "json"]:
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raise ValueError("Invalid json engine: %s" % engine)
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if engine == "orjson":
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JsonConfig.validate_orjson()
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# orjson handles bytes input natively
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value_dict = orjson.loads(value)
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else:
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# decode bytes to str for built-in json module
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if isinstance(value, bytes):
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value = value.decode("utf-8")
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value_dict = json.loads(value)
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return value_dict
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def from_json(value, output_type="Figure", skip_invalid=False, engine=None):
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"""
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Construct a figure from a JSON string
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Parameters
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----------
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value: str or bytes
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String or bytes object containing the JSON representation of a figure
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output_type: type or str (default 'Figure')
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The output figure type or type name.
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One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget'
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skip_invalid: bool (default False)
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False if invalid figure properties should result in an exception.
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True if invalid figure properties should be silently ignored.
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engine: str (default None)
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The JSON decoding engine to use. One of:
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- if "json", parse JSON using built in json module
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- if "orjson", parse using the faster orjson module, requires the orjson
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package
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- if "auto" use orjson module if available, otherwise use the json module
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If not specified, the default engine is set to the current value of
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plotly.io.json.config.default_engine.
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Raises
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------
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ValueError
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if value is not a string, or if skip_invalid=False and value contains
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invalid figure properties
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Returns
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-------
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Figure or FigureWidget
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"""
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# Decode JSON
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# -----------
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fig_dict = from_json_plotly(value, engine=engine)
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# Validate coerce output type
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# ---------------------------
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|
|
cls = validate_coerce_output_type(output_type)
|
||
|
|
|
||
|
|
# Create and return figure
|
||
|
|
# ------------------------
|
||
|
|
fig = cls(fig_dict, skip_invalid=skip_invalid)
|
||
|
|
return fig
|
||
|
|
|
||
|
|
|
||
|
|
def read_json(file, output_type="Figure", skip_invalid=False, engine=None):
|
||
|
|
"""
|
||
|
|
Construct a figure from the JSON contents of a local file or readable
|
||
|
|
Python object
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
file: str or readable
|
||
|
|
A string containing the path to a local file or a read-able Python
|
||
|
|
object (e.g. a pathlib.Path object or an open file descriptor)
|
||
|
|
|
||
|
|
output_type: type or str (default 'Figure')
|
||
|
|
The output figure type or type name.
|
||
|
|
One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget'
|
||
|
|
|
||
|
|
skip_invalid: bool (default False)
|
||
|
|
False if invalid figure properties should result in an exception.
|
||
|
|
True if invalid figure properties should be silently ignored.
|
||
|
|
|
||
|
|
engine: str (default None)
|
||
|
|
The JSON decoding engine to use. One of:
|
||
|
|
- if "json", parse JSON using built in json module
|
||
|
|
- if "orjson", parse using the faster orjson module, requires the orjson
|
||
|
|
package
|
||
|
|
- if "auto" use orjson module if available, otherwise use the json module
|
||
|
|
|
||
|
|
If not specified, the default engine is set to the current value of
|
||
|
|
plotly.io.json.config.default_engine.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Figure or FigureWidget
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Try to cast `file` as a pathlib object `path`.
|
||
|
|
# -------------------------
|
||
|
|
# ----------------------------------------------
|
||
|
|
file_is_str = isinstance(file, str)
|
||
|
|
if isinstance(file, str):
|
||
|
|
# Use the standard Path constructor to make a pathlib object.
|
||
|
|
path = Path(file)
|
||
|
|
elif isinstance(file, Path):
|
||
|
|
# `file` is already a Path object.
|
||
|
|
path = file
|
||
|
|
else:
|
||
|
|
# We could not make a Path object out of file. Either `file` is an open file
|
||
|
|
# descriptor with a `write()` method or it's an invalid object.
|
||
|
|
path = None
|
||
|
|
|
||
|
|
# Read file contents into JSON string
|
||
|
|
# -----------------------------------
|
||
|
|
if path is not None:
|
||
|
|
json_str = path.read_text()
|
||
|
|
else:
|
||
|
|
json_str = file.read()
|
||
|
|
|
||
|
|
# Construct and return figure
|
||
|
|
# ---------------------------
|
||
|
|
return from_json(
|
||
|
|
json_str, skip_invalid=skip_invalid, output_type=output_type, engine=engine
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def clean_to_json_compatible(obj, **kwargs):
|
||
|
|
# Try handling value as a scalar value that we have a conversion for.
|
||
|
|
# Return immediately if we know we've hit a primitive value
|
||
|
|
|
||
|
|
# Bail out fast for simple scalar types
|
||
|
|
if isinstance(obj, (int, float, str)):
|
||
|
|
return obj
|
||
|
|
|
||
|
|
if isinstance(obj, dict):
|
||
|
|
return {k: clean_to_json_compatible(v, **kwargs) for k, v in obj.items()}
|
||
|
|
elif isinstance(obj, (list, tuple)):
|
||
|
|
if obj:
|
||
|
|
# Must process list recursively even though it may be slow
|
||
|
|
return [clean_to_json_compatible(v, **kwargs) for v in obj]
|
||
|
|
|
||
|
|
# unpack kwargs
|
||
|
|
numpy_allowed = kwargs.get("numpy_allowed", False)
|
||
|
|
datetime_allowed = kwargs.get("datetime_allowed", False)
|
||
|
|
|
||
|
|
modules = kwargs.get("modules", {})
|
||
|
|
sage_all = modules["sage_all"]
|
||
|
|
np = modules["np"]
|
||
|
|
pd = modules["pd"]
|
||
|
|
image = modules["image"]
|
||
|
|
|
||
|
|
# Sage
|
||
|
|
if sage_all is not None:
|
||
|
|
if obj in sage_all.RR:
|
||
|
|
return float(obj)
|
||
|
|
elif obj in sage_all.ZZ:
|
||
|
|
return int(obj)
|
||
|
|
|
||
|
|
# numpy
|
||
|
|
if np is not None:
|
||
|
|
if obj is np.ma.core.masked:
|
||
|
|
return float("nan")
|
||
|
|
elif isinstance(obj, np.ndarray):
|
||
|
|
if numpy_allowed and obj.dtype.kind in ("b", "i", "u", "f"):
|
||
|
|
return np.ascontiguousarray(obj)
|
||
|
|
elif obj.dtype.kind == "M":
|
||
|
|
# datetime64 array
|
||
|
|
return np.datetime_as_string(obj).tolist()
|
||
|
|
elif obj.dtype.kind == "U":
|
||
|
|
return obj.tolist()
|
||
|
|
elif obj.dtype.kind == "O":
|
||
|
|
# Treat object array as a lists, continue processing
|
||
|
|
obj = obj.tolist()
|
||
|
|
elif isinstance(obj, np.datetime64):
|
||
|
|
return str(obj)
|
||
|
|
|
||
|
|
# pandas
|
||
|
|
if pd is not None:
|
||
|
|
if obj is pd.NaT:
|
||
|
|
return None
|
||
|
|
elif isinstance(obj, (pd.Series, pd.DatetimeIndex)):
|
||
|
|
if numpy_allowed and obj.dtype.kind in ("b", "i", "u", "f"):
|
||
|
|
return np.ascontiguousarray(obj.values)
|
||
|
|
elif obj.dtype.kind == "M":
|
||
|
|
if isinstance(obj, pd.Series):
|
||
|
|
with warnings.catch_warnings():
|
||
|
|
warnings.simplefilter("ignore", FutureWarning)
|
||
|
|
# Series.dt.to_pydatetime will return Index[object]
|
||
|
|
# https://github.com/pandas-dev/pandas/pull/52459
|
||
|
|
dt_values = np.array(obj.dt.to_pydatetime()).tolist()
|
||
|
|
else: # DatetimeIndex
|
||
|
|
dt_values = obj.to_pydatetime().tolist()
|
||
|
|
|
||
|
|
if not datetime_allowed:
|
||
|
|
# Note: We don't need to handle dropping timezones here because
|
||
|
|
# numpy's datetime64 doesn't support them and pandas's tz_localize
|
||
|
|
# above drops them.
|
||
|
|
for i in range(len(dt_values)):
|
||
|
|
dt_values[i] = dt_values[i].isoformat()
|
||
|
|
|
||
|
|
return dt_values
|
||
|
|
|
||
|
|
# datetime and date
|
||
|
|
try:
|
||
|
|
# Need to drop timezone for scalar datetimes. Don't need to convert
|
||
|
|
# to string since engine can do that
|
||
|
|
obj = obj.to_pydatetime()
|
||
|
|
except (TypeError, AttributeError):
|
||
|
|
pass
|
||
|
|
|
||
|
|
if not datetime_allowed:
|
||
|
|
try:
|
||
|
|
return obj.isoformat()
|
||
|
|
except (TypeError, AttributeError):
|
||
|
|
pass
|
||
|
|
elif isinstance(obj, datetime.datetime):
|
||
|
|
return obj
|
||
|
|
|
||
|
|
# Try .tolist() convertible, do not recurse inside
|
||
|
|
try:
|
||
|
|
return obj.tolist()
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
|
||
|
|
# Do best we can with decimal
|
||
|
|
if isinstance(obj, decimal.Decimal):
|
||
|
|
return float(obj)
|
||
|
|
|
||
|
|
# PIL
|
||
|
|
if image is not None and isinstance(obj, image.Image):
|
||
|
|
return ImageUriValidator.pil_image_to_uri(obj)
|
||
|
|
|
||
|
|
# Plotly
|
||
|
|
try:
|
||
|
|
obj = obj.to_plotly_json()
|
||
|
|
except AttributeError:
|
||
|
|
pass
|
||
|
|
|
||
|
|
# Recurse into lists and dictionaries
|
||
|
|
if isinstance(obj, dict):
|
||
|
|
return {k: clean_to_json_compatible(v, **kwargs) for k, v in obj.items()}
|
||
|
|
elif isinstance(obj, (list, tuple)):
|
||
|
|
if obj:
|
||
|
|
# Must process list recursively even though it may be slow
|
||
|
|
return [clean_to_json_compatible(v, **kwargs) for v in obj]
|
||
|
|
|
||
|
|
return obj
|