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import json
import decimal
import datetime
import warnings
from pathlib import Path
from plotly.io._utils import validate_coerce_fig_to_dict, validate_coerce_output_type
from _plotly_utils.optional_imports import get_module
from _plotly_utils.basevalidators import ImageUriValidator
# Orca configuration class
# ------------------------
class JsonConfig(object):
_valid_engines = ("json", "orjson", "auto")
def __init__(self):
self._default_engine = "auto"
@property
def default_engine(self):
return self._default_engine
@default_engine.setter
def default_engine(self, val):
if val not in JsonConfig._valid_engines:
raise ValueError(
"Supported JSON engines include {valid}\n Received {val}".format(
valid=JsonConfig._valid_engines, val=val
)
)
if val == "orjson":
self.validate_orjson()
self._default_engine = val
@classmethod
def validate_orjson(cls):
orjson = get_module("orjson")
if orjson is None:
raise ValueError("The orjson engine requires the orjson package")
config = JsonConfig()
def coerce_to_strict(const):
"""
This is used to ultimately *encode* into strict JSON, see `encode`
"""
# before python 2.7, 'true', 'false', 'null', were include here.
if const in ("Infinity", "-Infinity", "NaN"):
return None
else:
return const
_swap_json = (
("<", "\\u003c"),
(">", "\\u003e"),
("/", "\\u002f"),
)
_swap_orjson = _swap_json + (
("\u2028", "\\u2028"),
("\u2029", "\\u2029"),
)
def _safe(json_str, _swap):
out = json_str
for unsafe_char, safe_char in _swap:
if unsafe_char in out:
out = out.replace(unsafe_char, safe_char)
return out
def to_json_plotly(plotly_object, pretty=False, engine=None):
"""
Convert a plotly/Dash object to a JSON string representation
Parameters
----------
plotly_object:
A plotly/Dash object represented as a dict, graph_object, or Dash component
pretty: bool (default False)
True if JSON representation should be pretty-printed, False if
representation should be as compact as possible.
engine: str (default None)
The JSON encoding engine to use. One of:
- "json" for an engine based on the built-in Python json module
- "orjson" for a faster engine that requires the orjson package
- "auto" for the "orjson" engine if available, otherwise "json"
If not specified, the default engine is set to the current value of
plotly.io.json.config.default_engine.
Returns
-------
str
Representation of input object as a JSON string
See Also
--------
to_json : Convert a plotly Figure to JSON with validation
"""
orjson = get_module("orjson", should_load=True)
# Determine json engine
if engine is None:
engine = config.default_engine
if engine == "auto":
if orjson is not None:
engine = "orjson"
else:
engine = "json"
elif engine not in ["orjson", "json"]:
raise ValueError("Invalid json engine: %s" % engine)
modules = {
"sage_all": get_module("sage.all", should_load=False),
"np": get_module("numpy", should_load=False),
"pd": get_module("pandas", should_load=False),
"image": get_module("PIL.Image", should_load=False),
}
# Dump to a JSON string and return
# --------------------------------
if engine == "json":
opts = {}
if pretty:
opts["indent"] = 2
else:
# Remove all whitespace
opts["separators"] = (",", ":")
from _plotly_utils.utils import PlotlyJSONEncoder
return _safe(
json.dumps(plotly_object, cls=PlotlyJSONEncoder, **opts), _swap_json
)
elif engine == "orjson":
JsonConfig.validate_orjson()
opts = orjson.OPT_NON_STR_KEYS | orjson.OPT_SERIALIZE_NUMPY
if pretty:
opts |= orjson.OPT_INDENT_2
# Plotly
try:
plotly_object = plotly_object.to_plotly_json()
except AttributeError:
pass
# Try without cleaning
try:
return _safe(
orjson.dumps(plotly_object, option=opts).decode("utf8"), _swap_orjson
)
except TypeError:
pass
cleaned = clean_to_json_compatible(
plotly_object,
numpy_allowed=True,
datetime_allowed=True,
modules=modules,
)
return _safe(orjson.dumps(cleaned, option=opts).decode("utf8"), _swap_orjson)
def to_json(fig, validate=True, pretty=False, remove_uids=True, engine=None):
"""
Convert a figure to a JSON string representation
Parameters
----------
fig:
Figure object or dict representing a figure
validate: bool (default True)
True if the figure should be validated before being converted to
JSON, False otherwise.
pretty: bool (default False)
True if JSON representation should be pretty-printed, False if
representation should be as compact as possible.
remove_uids: bool (default True)
True if trace UIDs should be omitted from the JSON representation
engine: str (default None)
The JSON encoding engine to use. One of:
- "json" for an engine based on the built-in Python json module
- "orjson" for a faster engine that requires the orjson package
- "auto" for the "orjson" engine if available, otherwise "json"
If not specified, the default engine is set to the current value of
plotly.io.json.config.default_engine.
Returns
-------
str
Representation of figure as a JSON string
See Also
--------
to_json_plotly : Convert an arbitrary plotly graph_object or Dash component to JSON
"""
# Validate figure
# ---------------
fig_dict = validate_coerce_fig_to_dict(fig, validate)
# Remove trace uid
# ----------------
if remove_uids:
for trace in fig_dict.get("data", []):
trace.pop("uid", None)
return to_json_plotly(fig_dict, pretty=pretty, engine=engine)
def write_json(fig, file, validate=True, pretty=False, remove_uids=True, engine=None):
"""
Convert a figure to JSON and write it to a file or writeable
object.
Note: A figure converted to JSON with one version of Plotly.py may not be compatible with another version.
Parameters
----------
fig:
Figure object or dict representing a figure
file: str or writeable
A string representing a local file path or a writeable object
(e.g. a pathlib.Path object or an open file descriptor)
pretty: bool (default False)
True if JSON representation should be pretty-printed, False if
representation should be as compact as possible.
remove_uids: bool (default True)
True if trace UIDs should be omitted from the JSON representation
engine: str (default None)
The JSON encoding engine to use. One of:
- "json" for an engine based on the built-in Python json module
- "orjson" for a faster engine that requires the orjson package
- "auto" for the "orjson" engine if available, otherwise "json"
If not specified, the default engine is set to the current value of
plotly.io.json.config.default_engine.
Returns
-------
None
"""
# Get JSON string
# ---------------
# Pass through validate argument and let to_json handle validation logic
json_str = to_json(
fig, validate=validate, pretty=pretty, remove_uids=remove_uids, engine=engine
)
# Try to cast `file` as a pathlib object `path`.
# ----------------------------------------------
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
# Open file
# ---------
if path is None:
# We previously failed to make sense of `file` as a pathlib object.
# Attempt to write to `file` as an open file descriptor.
try:
file.write(json_str)
return
except AttributeError:
pass
raise ValueError(
"""
The 'file' argument '{file}' is not a string, pathlib.Path object, or file descriptor.
""".format(file=file)
)
else:
# We previously succeeded in interpreting `file` as a pathlib object.
# Now we can use `write_bytes()`.
path.write_text(json_str)
def from_json_plotly(value, engine=None):
"""
Parse JSON string using the specified JSON engine
Parameters
----------
value: str or bytes
A JSON string or bytes object
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
-------
dict
See Also
--------
from_json_plotly : Parse JSON with plotly conventions into a dict
"""
orjson = get_module("orjson", should_load=True)
# Validate value
# --------------
if not isinstance(value, (str, bytes)):
raise ValueError(
"""
from_json_plotly requires a string or bytes argument but received value of type {typ}
Received value: {value}""".format(typ=type(value), value=value)
)
# Determine json engine
if engine is None:
engine = config.default_engine
if engine == "auto":
if orjson is not None:
engine = "orjson"
else:
engine = "json"
elif engine not in ["orjson", "json"]:
raise ValueError("Invalid json engine: %s" % engine)
if engine == "orjson":
JsonConfig.validate_orjson()
# orjson handles bytes input natively
value_dict = orjson.loads(value)
else:
# decode bytes to str for built-in json module
if isinstance(value, bytes):
value = value.decode("utf-8")
value_dict = json.loads(value)
return value_dict
def from_json(value, output_type="Figure", skip_invalid=False, engine=None):
"""
Construct a figure from a JSON string
Parameters
----------
value: str or bytes
String or bytes object containing the JSON representation of a figure
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.
Raises
------
ValueError
if value is not a string, or if skip_invalid=False and value contains
invalid figure properties
Returns
-------
Figure or FigureWidget
"""
# Decode JSON
# -----------
fig_dict = from_json_plotly(value, engine=engine)
# Validate coerce output type
# ---------------------------
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.
Note: A figure converted to JSON with one version of Plotly.py may not be compatible with another version.
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`.
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 or obj is pd.NA:
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