def test_cell_output_to_nodes(doctree):
# tests the image uri paths on conversion to docutils image nodes
priority = ['image/png', 'image/jpeg', 'text/latex', 'text/plain']
output_dir = '/_build/jupyter_execute'
img_locs = ['/_build/jupyter_execute/docs/image_1.png','/_build/jupyter_execute/image_2.png']
cells = [
{'outputs':
[{'data': {'image/png': 'Vxb6L1wAAAABJRU5ErkJggg==\n', 'text/plain': '<Figure size 432x288 with 1 Axes>'}, 'metadata': {'filenames': {'image/png': img_locs[0]}}, 'output_type': 'display_data'}]
},
{'outputs':
[{'data': {'image/png': 'iVBOJggg==\n', 'text/plain': '<Figure size 432x288 with 1 Axes>'}, 'metadata': {'filenames': {'image/png': img_locs[1]}}, 'output_type': 'display_data'}]
}]
for index, cell in enumerate(cells):
cell = from_dict(cell)
output_node = cell_output_to_nodes(cell["outputs"], priority, True, output_dir, None)
assert output_node[0].attributes['uri'] == img_locs[index]
# Testing inline functionality
outputs = [
{"name": "stdout", "output_type": "stream", "text": ["hi\n"]},
{"name": "stderr", "output_type": "stream", "text": ["hi\n"]},
]
output_nodes = cell_output_to_nodes(outputs, priority, True, output_dir, None)
for output, kind in zip(output_nodes, [literal_block, container]):
assert isinstance(output, kind)
output_nodes = cell_output_to_nodes(outputs, priority, True, output_dir, None, inline=True)
for output, kind in zip(output_nodes, [literal, literal]):
assert isinstance(output, kind)
def apply(self):
builder = self.app.builder.name
output_dir = sphinx_abs_dir(self.env)
for node in self.document.traverse(CellOutputBundleNode):
cell = {"outputs": node.outputs}
outputs = cell.get("outputs", [])
if node.get("inline", False):
output_nodes = cell_output_to_nodes_inline(
outputs, RENDER_PRIORITY.get(builder, 'html'), True,
output_dir, None)
else:
output_nodes = cell_output_to_nodes(
outputs, RENDER_PRIORITY.get(builder, 'html'), True,
output_dir, None)
# TODO add warning if output_nodes is empty
node.replace_self(output_nodes)
# Image collect extra nodes from cell outputs that we need to process
for node in self.document.traverse(nodes.image):
# If the image node has `candidates` then it's already been processed
# as in-line markdown, so skip it
if "candidates" in node:
continue
col = ImageCollector()
col.process_doc(self.app, node)
def cell_output_to_nodes(outputs, data_priority, write_stderr, dir,
thebe_config):
from jupyter_sphinx.ast import cell_output_to_nodes
to_add = []
for _, output in enumerate(outputs):
if output["output_type"] == "display_data":
if "text/markdown" in output["data"]:
continue # because we had to deal with the markdown earlier on.
to_add.extend(
cell_output_to_nodes(outputs, data_priority, write_stderr, dir,
thebe_config))
return to_add
def test_image_mimetype_uri(doctree):
# tests the image uri paths on conversion to docutils image nodes
priority = ['image/png', 'image/jpeg', 'text/latex', 'text/plain']
output_dir = '/_build/jupyter_execute'
img_locs = [
'/_build/jupyter_execute/docs/image_1.png',
'/_build/jupyter_execute/image_2.png'
]
cells = [{
'outputs': [{
'data': {
'image/png': 'Vxb6L1wAAAABJRU5ErkJggg==\n',
'text/plain': '<Figure size 432x288 with 1 Axes>'
},
'metadata': {
'filenames': {
'image/png': img_locs[0]
}
},
'output_type': 'display_data'
}]
}, {
'outputs': [{
'data': {
'image/png': 'iVBOJggg==\n',
'text/plain': '<Figure size 432x288 with 1 Axes>'
},
'metadata': {
'filenames': {
'image/png': img_locs[1]
}
},
'output_type': 'display_data'
}]
}]
for index, cell in enumerate(cells):
cell = from_dict(cell)
output_node = cell_output_to_nodes(cell, priority, True, output_dir,
None)
assert output_node[0].attributes['uri'] == img_locs[index]
