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import os.path as opath
import textwrap
from io import StringIO
from codegen.utils import CAVEAT, write_source_py
deprecated_mapbox_traces = [
"scattermapbox",
"choroplethmapbox",
"densitymapbox",
]
locationmode_traces = [
"choropleth",
"scattergeo",
]
def get_typing_type(plotly_type, array_ok=False):
"""
Get Python type corresponding to a valType string from the plotly schema
Parameters
----------
plotly_type : str
a plotly datatype string
array_ok : bool
Whether lists/arrays are permitted
Returns
-------
str
Python type string
"""
if plotly_type == "data_array":
pytype = "numpy.ndarray"
elif plotly_type == "info_array":
pytype = "list"
elif plotly_type == "colorlist":
pytype = "list"
elif plotly_type in ("string", "color", "colorscale", "subplotid"):
pytype = "str"
elif plotly_type in ("enumerated", "flaglist", "any"):
pytype = "Any"
elif plotly_type in ("number", "angle"):
pytype = "int|float"
elif plotly_type == "integer":
pytype = "int"
elif plotly_type == "boolean":
pytype = "bool"
else:
raise ValueError("Unknown plotly type: %s" % plotly_type)
if array_ok:
return f"{pytype}|numpy.ndarray"
else:
return pytype
def build_datatype_py(node):
"""
Build datatype (graph_objs) class source code string for a datatype
PlotlyNode
Parameters
----------
node : PlotlyNode
The datatype node (node.is_datatype must evaluate to true) for which
to build the datatype class
Returns
-------
str
String containing source code for the datatype class definition
"""
# Validate inputs
assert node.is_compound
# Handle template traces
#
# We want template trace/layout classes like
# plotly.graph_objs.layout.template.data.Scatter to map to the
# corresponding trace/layout class (e.g. plotly.graph_objs.Scatter).
# So rather than generate a class definition, we just import the
# corresponding trace/layout class
if node.parent_path_str == "layout.template.data":
return f"from plotly.graph_objs import {node.name_datatype_class}"
elif node.path_str == "layout.template.layout":
return "from plotly.graph_objs import Layout"
# Extract node properties
datatype_class = node.name_datatype_class
literal_nodes = [n for n in node.child_literals if n.plotly_name in ["type"]]
# Initialze source code buffer
buffer = StringIO()
buffer.write(CAVEAT)
# Imports
buffer.write(
f"from plotly.basedatatypes "
f"import {node.name_base_datatype} as _{node.name_base_datatype}\n"
)
buffer.write("import copy as _copy\n")
if (
node.name_property in deprecated_mapbox_traces
or node.name_property in locationmode_traces
or node.name_property == "template"
):
buffer.write("import warnings\n")
# Write class definition
buffer.write(
f"""
class {datatype_class}(_{node.name_base_datatype}):\n"""
)
# Layout subplot properties
if datatype_class == "Layout":
subplot_nodes = [
node
for node in node.child_compound_datatypes
if node.node_data.get("_isSubplotObj", False)
]
subplot_names = [n.name_property for n in subplot_nodes]
buffer.write(
f"""
_subplotid_prop_names = {repr(subplot_names)}
import re
_subplotid_prop_re = re.compile(
'^(' + '|'.join(_subplotid_prop_names) + r')(\\d+)$')
"""
)
subplot_dict_str = (
"{"
+ ", ".join(
f'"{subname}": ValidatorCache.get_validator("layout", "{subname}")'
for subname in subplot_names
)
+ "}"
)
buffer.write(
f"""
@property
def _subplotid_validators(self):
\"\"\"
dict of validator classes for each subplot type
Returns
-------
dict
\"\"\"
from plotly.validator_cache import ValidatorCache
return {subplot_dict_str}
def _subplot_re_match(self, prop):
return self._subplotid_prop_re.match(prop)
"""
)
child_datatype_nodes = node.child_datatypes
subtype_nodes = child_datatype_nodes
valid_props_list = sorted(
[node.name_property for node in subtype_nodes + literal_nodes]
)
# class properties
buffer.write(
f"""
_parent_path_str = "{node.parent_path_str}"
_path_str = "{node.path_str}"
_valid_props = {{"{'", "'.join(valid_props_list)}"}}
"""
)
# Property definitions
for subtype_node in subtype_nodes:
if subtype_node.is_array_element:
prop_type = (
f"tuple[plotly.graph_objs{node.dotpath_str}."
+ f"{subtype_node.name_datatype_class}]"
)
elif subtype_node.is_compound:
prop_type = (
f"plotly.graph_objs{node.dotpath_str}."
+ f"{subtype_node.name_datatype_class}"
)
# remap template traces to regular traces
prop_type = prop_type.replace("layout.template.data", "")
elif subtype_node.is_mapped:
prop_type = ""
else:
prop_type = get_typing_type(subtype_node.datatype, subtype_node.is_array_ok)
# Get property description
raw_description = subtype_node.description
property_description = "\n".join(
textwrap.wrap(
raw_description,
initial_indent=" " * 8,
subsequent_indent=" " * 8,
width=79 - 8,
)
)
# Get validator description
validator = subtype_node.get_validator_instance()
if validator:
validator_description = reindent_validator_description(validator, 4)
# Combine to form property docstring
if property_description.strip():
property_docstring = f"""{property_description}
{validator_description}"""
else:
property_docstring = f" {validator_description}"
else:
property_docstring = property_description
# Write get property
buffer.write(
f'''\
@property
def {subtype_node.name_property}(self):
"""
{property_docstring}
Returns
-------
{prop_type}
"""
return self["{subtype_node.name_property}"]'''
)
# Write set property
buffer.write(
f"""
@{subtype_node.name_property}.setter
def {subtype_node.name_property}(self, val):
self["{subtype_node.name_property}"] = val\n"""
)
# Literals
for literal_node in literal_nodes:
buffer.write(
f"""\
@property
def {literal_node.name_property}(self):
return self._props["{literal_node.name_property}"]\n"""
)
# Private properties descriptions
buffer.write(
"""
@property
def _prop_descriptions(self):
return \"\"\"\\"""
)
buffer.write(node.get_constructor_params_docstring(indent=8))
buffer.write(
"""
\"\"\""""
)
mapped_nodes = [n for n in subtype_nodes if n.is_mapped]
mapped_properties = {n.plotly_name: n.relative_path for n in mapped_nodes}
if mapped_properties:
buffer.write(
f"""
_mapped_properties = {repr(mapped_properties)}"""
)
# Constructor
buffer.write(
"""
def __init__(self"""
)
add_constructor_params(buffer, subtype_nodes, prepend_extras=["arg"])
# Constructor Docstring
header = f"Construct a new {datatype_class} object"
class_name = (
f"plotly.graph_objs{node.parent_dotpath_str}.{node.name_datatype_class}"
)
extras = [
(
"arg",
"dict of properties compatible with this constructor "
f"or an instance of :class:`{class_name}`",
)
]
add_docstring(
buffer,
node,
header=header,
prepend_extras=extras,
return_type=node.name_datatype_class,
)
buffer.write(
f"""
super().__init__("{node.name_property}")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
"""
)
if datatype_class == "Layout":
# Override _valid_props for instance so that instance can mutate set
# to support subplot properties (e.g. xaxis2)
buffer.write(
f"""
self._valid_props = {{"{'", "'.join(valid_props_list)}"}}
"""
)
# Validate arg
buffer.write(
f"""
if arg is None:
arg = {{}}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = _copy.copy(arg)
else:
raise ValueError(\"\"\"\\
The first argument to the {class_name}
constructor must be a dict or
an instance of :class:`{class_name}`\"\"\")
"""
)
# Add warning for 'country names' locationmode
if node.name_property in locationmode_traces:
buffer.write(
f"""
if locationmode == "country names" and kwargs.get("_validate"):
warnings.warn(
"The library used by the *country names* `locationmode` option is changing in an upcoming version. "
"Country names in existing plots may not work in the new version. "
"To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.",
DeprecationWarning,
stacklevel=5,
)
"""
)
buffer.write(
f"""
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
"""
)
buffer.write("\n\n")
for subtype_node in subtype_nodes:
name_prop = subtype_node.name_property
if datatype_class == "Template" and name_prop == "data":
buffer.write(
f"""
# Template.data contains a 'scattermapbox' key, which causes a
# go.Scattermapbox trace object to be created during validation.
# In order to prevent false deprecation warnings from surfacing,
# we suppress deprecation warnings for this line only.
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning)
self._set_property("{name_prop}", arg, {name_prop})"""
)
else:
buffer.write(
f"""
self._set_property("{name_prop}", arg, {name_prop})"""
)
# Literals
if literal_nodes:
buffer.write("\n\n")
for literal_node in literal_nodes:
lit_name = literal_node.name_property
lit_val = repr(literal_node.node_data)
buffer.write(
f"""
self._props["{lit_name}"] = {lit_val}
arg.pop("{lit_name}", None)"""
)
buffer.write(
"""
self._process_kwargs(**dict(arg, **kwargs))
self._skip_invalid = False
"""
)
if node.name_property in deprecated_mapbox_traces:
buffer.write(
f"""
warnings.warn(
"*{node.name_property}* is deprecated!"
+ " Use *{node.name_property.replace("mapbox", "map")}* instead."
+ " Learn more at: https://plotly.com/python/mapbox-to-maplibre/",
stacklevel=2,
category=DeprecationWarning,
)
"""
)
# Return source string
return buffer.getvalue()
def reindent_validator_description(validator, extra_indent):
"""
Return validator description with modified indenting. The string that is
returned has no leading indent, and the subsequent lines are indented by 4
spaces (the default for validator descriptions) plus `extra_indent` spaces
Parameters
----------
validator : BaseValidator
Validator from which to extract the description
extra_indent : int
Number of spaces of indent to add to subsequent lines (those after
the first line). Validators description start with in indent of 4
spaces
Returns
-------
str
Validator description string
"""
# Remove leading indent and add extra spaces to subsequent indent
return ("\n" + " " * extra_indent).join(validator.description().strip().split("\n"))
def add_constructor_params(
buffer, subtype_nodes, prepend_extras=(), append_extras=(), output_type=None
):
"""
Write datatype constructor params to a buffer
Parameters
----------
buffer : StringIO
Buffer to write to
subtype_nodes : list of PlotlyNode
List of datatype nodes to be written as constructor params
prepend_extras : list[str]
List of extra parameters to include at the beginning of the params
append_extras : list[str]
List of extra parameters to include at the end of the params
Returns
-------
None
"""
for extra in prepend_extras:
buffer.write(
f""",
{extra}=None"""
)
for i, subtype_node in enumerate(subtype_nodes):
buffer.write(
f""",
{subtype_node.name_property}=None"""
)
for extra in append_extras:
buffer.write(
f""",
{extra}=None"""
)
buffer.write(
""",
**kwargs"""
)
buffer.write(
"""
)"""
)
if output_type:
buffer.write(f'-> "{output_type}"')
buffer.write(":")
def add_docstring(
buffer, node, header, prepend_extras=(), append_extras=(), return_type=None
):
"""
Write docstring for a compound datatype node
Parameters
----------
buffer : StringIO
Buffer to write to
node : PlotlyNode
Compound datatype plotly node for which to write docstring
header :
Top-level header for docstring that will preceded the input node's
own description. Header should be < 71 characters long
prepend_extras :
List or tuple of propery name / description pairs that should be
included at the beginning of the docstring
append_extras :
List or tuple of propery name / description pairs that should be
included at the end of the docstring
return_type :
The docstring return type
Returns
-------
"""
# Validate inputs
assert node.is_compound
# Build wrapped description
node_description = node.description
if node_description:
description_lines = textwrap.wrap(
node_description,
width=79 - 8,
initial_indent=" " * 8,
subsequent_indent=" " * 8,
)
node_description = "\n".join(description_lines) + "\n\n"
# Write header and description
buffer.write(
f"""
\"\"\"
{header}
{node_description} Parameters
----------"""
)
# Write parameter descriptions
# Write any prepend extras
for p, v in prepend_extras:
v_wrapped = "\n".join(
textwrap.wrap(
v, width=79 - 12, initial_indent=" " * 12, subsequent_indent=" " * 12
)
)
buffer.write(
f"""
{p}
{v_wrapped}"""
)
# Write core docstring
buffer.write(node.get_constructor_params_docstring(indent=8))
# Write any append extras
for p, v in append_extras:
if "\n" in v:
# If v contains newlines assume it's already wrapped
v_wrapped = v
else:
v_wrapped = "\n".join(
textwrap.wrap(
v,
width=79 - 12,
initial_indent=" " * 12,
subsequent_indent=" " * 12,
)
)
buffer.write(
f"""
{p}
{v_wrapped}"""
)
# Write return block and close docstring
buffer.write(
f"""
Returns
-------
{return_type}
\"\"\""""
)
def write_datatype_py(outdir, node):
"""
Build datatype (graph_objs) class source code and write to a file
Parameters
----------
outdir :
Root outdir in which the graph_objs package should reside
node :
The datatype node (node.is_datatype must evaluate to true) for which
to build the datatype class
Returns
-------
None
"""
# Build file path
# filepath = opath.join(outdir, "graph_objs", *node.parent_path_parts, "__init__.py")
filepath = opath.join(
outdir, "graph_objs", *node.parent_path_parts, "_" + node.name_undercase + ".py"
)
# Generate source code
datatype_source = build_datatype_py(node)
# Write file
write_source_py(datatype_source, filepath, leading_newlines=2)