def encode(self, obj: NDFrame, description: Optional[str], params: Optional[Dict]) -> FrameData:
buf = StringIO()
obj.to_csv(buf, index=self.index, header=self.header, encoding=self.encoding, quoting=QUOTE_ALL)
index_type = [str(obj.index.dtype)] if self.index else []
return FrameData(BytesContent(buf.getvalue().encode(self.encoding)), MediaType("text/csv", self.application()),
description, params,
{"header": self.header,
"index": self.index,
"schema": index_type + self.schema(obj),
"encoding": self.encoding,
"version": pandas_version})
def pull_data(context: Context,
params: Optional[Dict] = None,
**kwargs) -> FrameData:
path = context.stack_path()
params = merge_or_none(params, kwargs)
res = context.protocol.pull(path, context.profile.token, params)
attach = res["attachment"]
data = \
BytesContent(base64.b64decode(attach["data"])) if "data" in attach else \
StreamContent(*context.protocol.download(attach["download_url"]))
media_type = MediaType(attach["content_type"],
attach.get("application", None))
return FrameData(data, media_type, attach.get("description", None),
attach.get("params", None), attach.get("settings", None))
def encode(self, obj: Figure, description: Optional[str],
params: Optional[Dict]) -> FrameData:
"""Convert Bokeh figure to frame data.
Args:
obj (bokeh.plotting.figure.Figure): Bokeh's figure to publish.
description: Bokeh plot description.
params: Bokeh plot parameters.
Returns:
Frame data.
"""
text = dumps(json_item(obj))
return FrameData(BytesContent(text.encode("utf-8")),
MediaType("application/json", "bokeh"), description,
params, {"bokeh_version": bokeh_version})
def encode(self, obj: Figure, description: Optional[str], params: Optional[Dict]) -> FrameData:
"""Convert matplotlib figure to frame data.
Notes:
Figure will be converted to SVG format.
Args:
obj: Plot to be published.
description: Description of the plot.
params: Plot parameters if specified.
Returns:
Corresponding `FrameData` object.
"""
buf = io.BytesIO()
obj.savefig(buf, format="svg")
return FrameData(BytesContent(buf), MediaType("image/svg+xml", "matplotlib"), description, params)
def pull_data(context: Context,
params: ty.Optional[ty.Dict] = None,
meta: ty.Optional[ty.Dict] = None,
**kwargs) -> FrameData:
path = context.stack_path()
params = merge_or_none(params, kwargs)
# TODO: Split context.protocol.pull into to pull_head and pull_frame
frame, index, res = context.protocol.pull(path, context.profile.token,
params, meta)
attach = res["attachment"]
data = _cache_attach_data(attach, context, frame, index, path)
media_type = MediaType(attach["content_type"],
attach.get("application", None))
return FrameData(data, media_type, attach.get("description", None),
attach.get("params", None), attach.get("settings", None))
def encode(self, obj: BaseEstimator, description: Optional[str],
params: Optional[Dict]) -> FrameData:
buf = self.persistence.encode(obj)
settings = {
"class": f"{obj.__class__.__module__}.{obj.__class__.__name__}",
"scikit-learn": sklearn.__version__,
"scipy": scipy.__version__,
"numpy": numpy.__version__,
"joblib": joblib.__version__,
"storage_format": self.persistence.storage()
}
if obj.__class__ in self.map:
model_info = self.map[obj.__class__](obj)
settings["info"] = model_info.settings()
return FrameData(BytesContent(buf), self.persistence.type(),
description, params, settings)
def encode(self, obj: Figure, description: Optional[str],
params: Optional[Dict]) -> FrameData:
"""Build frame data object from Plotly figure.
Args:
obj (plotly.graph_objs._figure.Figure): A plotly figure to publish.
description: Description of Plotly chart.
params: Parameters of the chart.
Returns:
Frame data.
"""
json = obj.to_json()
return FrameData(
BytesContent(json.encode("utf-8")),
MediaType("application/json", "plotly"), description, params, {
"plotly_version": plotly_version,
"plotly_js_version": self.plotly_js_version
})
def encode(self, obj: Markdown, description: Optional[str],
params: Optional[Dict]) -> FrameData:
return FrameData(BytesContent(obj.text.encode("utf-8")),
MediaType("text/markdown", "markdown"), description,
params)