5f9854e2-3ace-4db8-8620-070e901a70eb

Committed 04 Apr 2025 03:41AM UTC coverage: 80.946% (+6.1%) from 74.814%

Build # 5f9854e2-3ace-4db8-8620-070e901a70eb

Build Type

push

circleci

Committed by

web-flow

Commit Message

JS local sources; Better Jupyter; Top level configs; R/JS attribute mapping

1.  Support local / custom CanvasXpress JS and CSS sources.
2.  Support top-level configuration declarations.
3.  Support mapping R/JS configuration key names to Pythonic editions.  For example, renderTo --> render_to.
4.  Improved Jupyter Notebook detection and pre-loading of CanvasXpress JS and CSS.

Run Details

93 of 117 new or added lines in 10 files covered. (79.49%)

7 existing lines in 3 files now uncovered.

1933 of 2388 relevant lines covered (80.95%)

0.81 hits per line

Source File
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40.74

/canvasxpress/plot.py

from typing import Any, Union

from canvasxpress.canvas import CanvasXpress
from canvasxpress.render.environment import (
    get_target_context,
    CONTEXT_RSTUDIO,
    CONTEXT_SHINY,
    CONTEXT_DASH,
    CONTEXT_JUPYTER,
    CONTEXT_STREAMLIT,
    CONTEXT_BROWSER,
)
from canvasxpress.render.image import CXImage
from canvasxpress.render.json import CXJSON
from canvasxpress.render.popup import CXBrowserPopup

# Track the runtime context
_g_contexts_imported: list = []
_g_context = get_target_context()

# Pre-load Jupyter JS and CSS.
if _g_context == CONTEXT_JUPYTER:
    if not _g_context in _g_contexts_imported:
        from canvasxpress.render.jupyter import CXNoteBook

        CXNoteBook.display_canvasxpress_header()


def convert_from_reproducible_json(json: str) -> Union[None, CanvasXpress]:
    """
    Accepts a str with a reproducible JSON and returns a CanvasXpress object.
    """
    return CanvasXpress.from_reproducible_json(json)


def convert_to_reproducible_json(canvas: CanvasXpress) -> str:
    """
    Converts the CanvasXpress object into a reproducible JSON string.
    """
    return CXJSON.render_to_json(canvas)


def convert_to_image(canvas: CanvasXpress, type: str = "png") -> Union[None, bytes]:
    """
    Converts the CanvasXpress object to an image of the specified type.
    """
    converter = CXImage(canvas)
    candidates = converter.render(format=type)
    for conversion in candidates:
        if conversion.get("image", {}).get("format") == type:
            return conversion.get("image", {}).get("binary")


def show_in_browser(canvas: CanvasXpress) -> None:
    """
    Opens a browser and displays the canvas.
    """
    plotter = CXBrowserPopup(canvas)
    plotter.render()


def graph(canvas: CanvasXpress) -> Any:
    """
    Displays the CanvasXpress object as a visualized chart in a manner appropriate to the running context.

    To override an assumed context the ENV variable `CANVASXPRESS_TARGET_CONTEXT` can be set to one of the following
    values, in which case `show` will attempt to illustrate the chart of the set target.

    - rstudio
    - shiny
    - jupyter
    - dash
    - streamlit
    - browser

    :returns: An `object` or `None` depending on the target context.  In the case of `browser` a popup browser will
        be launched.`
    """
    if _g_context == CONTEXT_RSTUDIO:
        if not _g_context in _g_contexts_imported:
            from canvasxpress.render.shiny import CXShinyWidget

        plotter = CXShinyWidget(canvas)
        plotter._repr_rstudio_viewer_()

    elif _g_context == CONTEXT_SHINY:
        if not _g_context in _g_contexts_imported:
            from canvasxpress.render.shiny import CXShinyWidget

        plotter = CXShinyWidget(canvas)
        return plotter

    elif _g_context == CONTEXT_DASH:
        if not _g_context in _g_contexts_imported:
            from canvasxpress.render.dash import CXElementFactory

        plotter = CXElementFactory()
        return plotter.render(canvas)

    elif _g_context == CONTEXT_JUPYTER:
        if not _g_context in _g_contexts_imported:
            from canvasxpress.render.jupyter import CXNoteBook

        plotter = CXNoteBook(canvas)
        return plotter.render()

    elif _g_context == CONTEXT_STREAMLIT:
        if not _g_context in _g_contexts_imported:
            from canvasxpress.render import streamlit

        streamlit.plot(canvas)

    elif _g_context == CONTEXT_BROWSER:
        plotter = CXBrowserPopup(canvas)
        plotter.render()

    else:
        return """
        show() cannot identify the target context.  Either explicitly use a module from canvasxpress.render to 
        illustrate the CanvasXpress object, which requires the proper canvasxpress package option to be installed 
        (for example, pip install canvasxpress[shiny]) or set the environment variable CANVASXPRESS_TARGET_CONTEXT 
        to be one of rstudio, shiny, jupyter, streamlit, dash, or browser.
        """

1	from typing import Any, Union	1✔
2
3	from canvasxpress.canvas import CanvasXpress	1✔
4	from canvasxpress.render.environment import (	1✔
5	get_target_context,
6	CONTEXT_RSTUDIO,
7	CONTEXT_SHINY,
8	CONTEXT_DASH,
9	CONTEXT_JUPYTER,
10	CONTEXT_STREAMLIT,
11	CONTEXT_BROWSER,
12	)
13	from canvasxpress.render.image import CXImage	1✔
14	from canvasxpress.render.json import CXJSON	1✔
15	from canvasxpress.render.popup import CXBrowserPopup	1✔
16
17	# Track the runtime context
18	_g_contexts_imported: list = []	1✔
19	_g_context = get_target_context()	1✔
20
21	# Pre-load Jupyter JS and CSS.
22	if _g_context == CONTEXT_JUPYTER:	1✔
NEW 23	if not _g_context in _g_contexts_imported:	×
NEW 24	from canvasxpress.render.jupyter import CXNoteBook	×
25
NEW 26	CXNoteBook.display_canvasxpress_header()	×
27
28
29	def convert_from_reproducible_json(json: str) -> Union[None, CanvasXpress]:	1✔
30	"""
31	Accepts a str with a reproducible JSON and returns a CanvasXpress object.
32	"""
33	return CanvasXpress.from_reproducible_json(json)	×
34
35
36	def convert_to_reproducible_json(canvas: CanvasXpress) -> str:	1✔
37	"""
38	Converts the CanvasXpress object into a reproducible JSON string.
39	"""
40	return CXJSON.render_to_json(canvas)	×
41
42
43	def convert_to_image(canvas: CanvasXpress, type: str = "png") -> Union[None, bytes]:	1✔
44	"""
45	Converts the CanvasXpress object to an image of the specified type.
46	"""
47	converter = CXImage(canvas)	×
48	candidates = converter.render(format=type)	×
49	for conversion in candidates:	×
50	if conversion.get("image", {}).get("format") == type:	×
51	return conversion.get("image", {}).get("binary")	×
52
53
54	def show_in_browser(canvas: CanvasXpress) -> None:	1✔
55	"""
56	Opens a browser and displays the canvas.
57	"""
58	plotter = CXBrowserPopup(canvas)	×
59	plotter.render()	×
60
61
62	def graph(canvas: CanvasXpress) -> Any:	1✔
63	"""
64	Displays the CanvasXpress object as a visualized chart in a manner appropriate to the running context.
65
66	To override an assumed context the ENV variable `CANVASXPRESS_TARGET_CONTEXT` can be set to one of the following
67	values, in which case `show` will attempt to illustrate the chart of the set target.
68
69	- rstudio
70	- shiny
71	- jupyter
72	- dash
73	- streamlit
74	- browser
75
76	:returns: An `object` or `None` depending on the target context. In the case of `browser` a popup browser will
77	be launched.`
78	"""
79	if _g_context == CONTEXT_RSTUDIO:	1✔
NEW 80	if not _g_context in _g_contexts_imported:	×
UNCOV 81	from canvasxpress.render.shiny import CXShinyWidget	×
82
83	plotter = CXShinyWidget(canvas)	×
84	plotter._repr_rstudio_viewer_()	×
85
86	elif _g_context == CONTEXT_SHINY:	1✔
NEW 87	if not _g_context in _g_contexts_imported:	×
UNCOV 88	from canvasxpress.render.shiny import CXShinyWidget	×
89
90	plotter = CXShinyWidget(canvas)	×
91	return plotter	×
92
93	elif _g_context == CONTEXT_DASH:	1✔
NEW 94	if not _g_context in _g_contexts_imported:	×
UNCOV 95	from canvasxpress.render.dash import CXElementFactory	×
96
97	plotter = CXElementFactory()	×
98	return plotter.render(canvas)	×
99
100	elif _g_context == CONTEXT_JUPYTER:	1✔
NEW 101	if not _g_context in _g_contexts_imported:	×
UNCOV 102	from canvasxpress.render.jupyter import CXNoteBook	×
103
104	plotter = CXNoteBook(canvas)	×
105	return plotter.render()	×
106
107	elif _g_context == CONTEXT_STREAMLIT:	1✔
108	if not _g_context in _g_contexts_imported:	1✔
109	from canvasxpress.render import streamlit	1✔
110
111	streamlit.plot(canvas)	1✔
112
NEW 113	elif _g_context == CONTEXT_BROWSER:	×
114	plotter = CXBrowserPopup(canvas)	×
115	plotter.render()	×
116
117	else:
118	return """	×
119	show() cannot identify the target context. Either explicitly use a module from canvasxpress.render to
120	illustrate the CanvasXpress object, which requires the proper canvasxpress package option to be installed
121	(for example, pip install canvasxpress[shiny]) or set the environment variable CANVASXPRESS_TARGET_CONTEXT
122	to be one of rstudio, shiny, jupyter, streamlit, dash, or browser.
123	"""

docinfosci / canvasxpress-python / 5f9854e2-3ace-4db8-8620-070e901a70eb

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