module `ipythonhelper.notebook_runner`¶

Short summary¶

module pyquickhelper.ipythonhelper.notebook_runner

Modified version of runipy.notebook_runner.

Classes¶

class	truncated documentation
`NotebookError`	Raised when the execution fails.
`NotebookKernelError`	Raised when wait_for_ready …
`NotebookRunner`	The kernel communicates with mime-types while the notebook uses short labels for different cell types. We’ll use this …

Static Methods¶

staticmethod	truncated documentation
`get_cell_code`	Returns the code of a cell.

Methods¶

method	truncated documentation
`__add__`	Merges two notebooks together, returns a new none.
`__del__`	We close the kernel.
`__init__`
`__len__`	Returns the number of cells, it iterates on cells to get this information and does cache the information.
`_cell_container`	Returns a cells container, it may change according to the format.
`_check_thumbnail_tuple`	Checks types for a thumbnail.
`_merge_images`	Merges images defined by (buffer, format). The method uses PIL to merge images when possible.
`_scale_image`	Scales an image with the same aspect ratio centered in an image with a given max_width and max_height.
`add_tag_slide`	Tries to add tags for a slide show when they are too few.
`cell_height`	Approximates the height of a cell by its number of lines it contains.
`cell_image`	Returns the cell image or None if not found.
`cell_metadata`	Returns the cell metadata.
`cell_type`	Returns the cell type.
`clean_code`	Cleans the code before running it, the function comment out instruction such as `show()`.
`copy`	Copies the notebook (just the content).
`count_code_cells`	Returns the number of code cells in the notebook.
`create_picture_from`	Creates a picture from text.
`first_cell`	Returns the first cell.
`get_description`	Gets summary and description of this notebook. We expect the first cell to contain a title and a description …
`get_thumbnail`	Processes the notebook and creates one picture based on the outputs to illustrate a notebook.
`iter_cells`	Iterates over the notebook cells.
`iter_code_cells`	Iterates over the notebook cells containing code.
`merge_notebook`	Appends notebook nb to this one.
`run_cell`	Runs a notebook cell and update the output of that cell inplace.
`run_notebook`	Runs all the cells of a notebook in order and update the outputs in-place. If `skip_exceptions` is set, …
`shutdown_kernel`	Shuts down kernel.
`to_json`	Converts the notebook into JSON.
`to_python`	Converts the notebook into python.

Documentation¶

Modified version of runipy.notebook_runner.

source on GitHub

exception pyquickhelper.ipythonhelper.notebook_runner.NotebookError[source]¶

Bases: Exception

Raised when the execution fails.

source on GitHub

exception pyquickhelper.ipythonhelper.notebook_runner.NotebookKernelError[source]¶

Bases: Exception

Raised when wait_for_ready fails.

source on GitHub

class pyquickhelper.ipythonhelper.notebook_runner.NotebookRunner(nb, profile_dir=None, working_dir=None, comment='', fLOG=<function noLOG>, theNotebook=None, code_init=None, kernel_name='python', log_level='30', extended_args=None, kernel=False, filename=None, replacements=None, detailed_log=None, startup_timeout=300)[source]¶

Bases: object

The kernel communicates with mime-types while the notebook uses short labels for different cell types. We’ll use this to map from kernel types to notebook format types.

This classes executes a notebook end to end.

The class can use different kernels. The next links gives more information on how to create or test a kernel:

Do I need to shutdown the kernel after running a notebook?

If the class is instantiated with kernel=True, a kernel will be started. It must be shutdown otherwise the program might be waiting for it for ever. That is one of the reasons why the travis build does not complete. The build finished but cannot terminate until all kernels are shutdown.

source on GitHub

Parameters

nb – notebook as JSON
profile_dir – profile directory
working_dir – working directory
comment – additional information added to error message
theNotebook – if not None, populate the variable theNotebook with this value in the notebook
code_init – to initialize the notebook with a python code as if it was a cell
fLOG – logging function
log_level – Choices: (0, 10, 20, 30=default, 40, 50, ‘DEBUG’, ‘INFO’, ‘WARN’, ‘ERROR’, ‘CRITICAL’)
kernel_name – kernel name, it can be None
extended_args – others arguments to pass to the command line (–KernelManager.autorestar=True for example), see Jupyter Notebook Arguments for a full list
kernel – kernel is True by default, the notebook can be run, if False, the notebook can be read but not run
filename – to add the notebook file if there is one in error messages
replacements – replacements to make in every cell before running it, dictionary { string: string }
detailed_log – to log detailed information when executing the notebook, this should be a function with the same signature as print or None
startup_timeout –
wait for this long for the kernel to be ready, see wait_for_ready

Changed in version 1.8: Parameter startup_timeout was added.

source on GitHub

__add__(nb)[source]¶

Merges two notebooks together, returns a new none.

Parameters: nb – notebook
Returns: new notebook

source on GitHub

__del__()[source]¶

We close the kernel.

source on GitHub

__init__(nb, profile_dir=None, working_dir=None, comment='', fLOG=<function noLOG>, theNotebook=None, code_init=None, kernel_name='python', log_level='30', extended_args=None, kernel=False, filename=None, replacements=None, detailed_log=None, startup_timeout=300)[source]¶

Parameters

nb – notebook as JSON
profile_dir – profile directory
working_dir – working directory
comment – additional information added to error message
theNotebook – if not None, populate the variable theNotebook with this value in the notebook
code_init – to initialize the notebook with a python code as if it was a cell
fLOG – logging function
log_level – Choices: (0, 10, 20, 30=default, 40, 50, ‘DEBUG’, ‘INFO’, ‘WARN’, ‘ERROR’, ‘CRITICAL’)
kernel_name – kernel name, it can be None
extended_args – others arguments to pass to the command line (–KernelManager.autorestar=True for example), see Jupyter Notebook Arguments for a full list
kernel – kernel is True by default, the notebook can be run, if False, the notebook can be read but not run
filename – to add the notebook file if there is one in error messages
replacements – replacements to make in every cell before running it, dictionary { string: string }
detailed_log – to log detailed information when executing the notebook, this should be a function with the same signature as print or None
startup_timeout –
wait for this long for the kernel to be ready, see wait_for_ready

Changed in version 1.8: Parameter startup_timeout was added.

source on GitHub

__len__()[source]¶

Returns the number of cells, it iterates on cells to get this information and does cache the information.

Returns: int

source on GitHub

_cell_container()[source]¶

Returns a cells container, it may change according to the format.

Returns: cell container

source on GitHub

_check_thumbnail_tuple(b)[source]¶

Checks types for a thumbnail.

Parameters: b – tuple image, format
Returns: b

The function raises an exception if the type is incorrect.

source on GitHub

_merge_images(results)[source]¶

Merges images defined by (buffer, format). The method uses PIL to merge images when possible.

Returns: [ (image, format) ]

source on GitHub

_scale_image(in_bytes, format=None, max_width=200, max_height=200)[source]¶

Scales an image with the same aspect ratio centered in an image with a given max_width and max_height.

Parameters

in_bytes – image as bytes
format – indication of the format (can be empty)
max_width – maximum size of the thumbnail
max_height – maximum size of the thumbnail

Returns

Image (PIL)

source on GitHub

add_tag_slide(max_nb_cell=4, max_nb_line=25)[source]¶

Tries to add tags for a slide show when they are too few.

Parameters

max_nb_cell – maximum number of cells within a slide
max_nb_line – maximum number of lines within a slide

Returns

list of modified cells { #slide: (kind, reason, cell) }

source on GitHub

cell_height(cell)[source]¶

Approximates the height of a cell by its number of lines it contains.

Parameters: cell – cell
Returns: number of cell

source on GitHub

cell_image(cell, image_from_text=False)[source]¶

Returns the cell image or None if not found.

Parameters

cell – cell to examine
image_from_text – produce an image even if it is not one

Returns

None for no image or a list of tuple (image as bytes, extension) for each output of the cell

source on GitHub

cell_metadata(cell)[source]¶

Returns the cell metadata.

Parameters: cell – cell
Returns: metadata

source on GitHub

cell_type(cell)[source]¶

Returns the cell type.

Parameters: cell – from iter_cells
Returns: type

source on GitHub

clean_code(code)[source]¶

Cleans the code before running it, the function comment out instruction such as show().

Parameters: code – code (string)
Returns: cleaned code

source on GitHub

copy()[source]¶

Copies the notebook (just the content).

Returns: instance of NotebookRunner

source on GitHub

count_code_cells()[source]¶

Returns the number of code cells in the notebook.

source on GitHub

create_picture_from(text, format, asbytes=True, context=None)[source]¶

Creates a picture from text.

Parameters

text – the text
format – text, json, …
context – (str) indication on the content of text (error, …)
asbytes – results as bytes or as an image

Returns

tuple (picture, format) or PIL.Image (if asbytes is False)

The picture will be bytes, the format png, bmp… The size of the picture will depend on the text. The longer, the bigger. The method relies on matplotlib and then convert the image into a PIL image.

HTML could be rendered with QWebPage from PyQt (not implemented).

source on GitHub

first_cell()[source]¶

Returns the first cell.

source on GitHub

static get_cell_code(cell)[source]¶

Returns the code of a cell.

Parameters: cell – a cell or a string
Returns: boolean (=iscell), string

source on GitHub

get_description()[source]¶

Gets summary and description of this notebook. We expect the first cell to contain a title and a description of its content.

Returns: header, description

source on GitHub

get_thumbnail(max_width=200, max_height=200, use_default=False)[source]¶

Processes the notebook and creates one picture based on the outputs to illustrate a notebook.

Parameters

max_width – maximum size of the thumbnail
max_height – maximum size of the thumbnail
use_default – force using a default image even if an even is present

Returns

string (SVG) or Image (PIL)

source on GitHub

iter_cells()[source]¶

Iterates over the notebook cells.

source on GitHub

iter_code_cells()[source]¶

Iterates over the notebook cells containing code.

source on GitHub

merge_notebook(nb)[source]¶

Appends notebook nb to this one.

Parameters: nb – notebook or list of notebook (NotebookRunner)
Returns: number of added cells

How to merge notebook?

The following code merges two notebooks into the first one and stores the result unto a file.

from pyquickhelper.ipythonhelper import read_nb
nb1 = read_nb("<file1>", kernel=False)
nb2 = read_nb("<file2>", kernel=False)
nb1.merge_notebook(nb2)
nb1.to_json(outfile)

source on GitHub

run_cell(index_cell, cell, clean_function=None, max_nbissue=15)[source]¶

Runs a notebook cell and update the output of that cell inplace.

Parameters

index_cell – index of the cell
cell – cell to execute
clean_function – cleaning function to apply to the code before running it
max_nbissue – number of times an issue can be raised before stopping

Returns

output of the cell

source on GitHub

run_notebook(skip_exceptions=False, progress_callback=None, additional_path=None, valid=None, clean_function=None, context=None)[source]¶

Runs all the cells of a notebook in order and update the outputs in-place.

If skip_exceptions is set, then if exceptions occur in a cell, the subsequent cells are run (by default, the notebook execution stops).

Parameters

skip_exceptions – skip exception
progress_callback – call back function
additional_path – additional paths (as a list or None if none)
valid – if not None, valid is a function which returns whether or not the cell should be executed or not, if the function returns None, the execution of the notebooks and skip the execution of the other cells
clean_function – function which cleans a cell’s code before executing it (None for None)

Returns

dictionary with statistics

The function adds the local variable theNotebook with the absolute file name of the notebook. Function valid can return None to stop the execution of the notebook before this cell.

source on GitHub

shutdown_kernel()[source]¶

Shuts down kernel.

source on GitHub

to_json(filename=None, encoding='utf8')[source]¶

Converts the notebook into JSON.

Parameters

filename – filename or stream
encoding – encoding

Returns

Json string if filename is None, None otherwise

source on GitHub

to_python()[source]¶

Converts the notebook into python.

Returns: string

source on GitHub

module `ipythonhelper.notebook_runner`¶

Short summary¶

Classes¶

Static Methods¶

Methods¶

Documentation¶

Links

Contents

Information

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module ipythonhelper.notebook_runner¶

Short summary¶

Classes¶

Static Methods¶

Methods¶

Documentation¶

module `ipythonhelper.notebook_runner`¶