Before executing any code check if server side is configured to execute
unrestricted code.

erp5_data_notebook: ZBigArray may not be available, add it to well_known_unserializable_type_tuple if possible.

erp5_data_notebook: Don't save ZBigArray in data notebook. It may be too big that zope process may crash.

erp5_data_notebook: If wrong setup method was added, then remove it otherwise jupyter becomes permanent unusable state.

erp5_data_notebook: Don't try to serialize well known unserializable objects and ignore any exceptions happened during serialization otherwise jupyter becomes permanent unusable state.

erp5_data_notebook: Support _repr_html_. Object such as pandas' DataFrame is rendered as HTML in Jupyter.

This reverts commit 6b6f1fe0.

This reverts commit 003e34c7.

Try to import module before it is added to environment this way if user tries to import non existent module Exception is immediately raised and doesn't block next Jupyter cell execution.

If user using Jupyter with ERP5 kernel is simply passing a comment inside a cell a server side error is raised thus this commit properly fixes it.
Clean up & style.

Fix coding style and typos.

pivottablejs is a very useful pivot table implementation in Javascript that
alllows the user to create his own tables and charts. And also they had examples
of integration with Pandas.DataFrame objects and Jupyter. So this is highly
based on that.

**ATTENTION**: this is an experimental integration and does not follow the ERP5
Javascript standards. It will be refactored in the future to use RenderJS and
JIO.

The integration generates an HTML page template which starts the pivot table and
have a placeholder for the data, that will be later replaced with a Data Frame
data as CSV. After this replacement the page is stored in the memcached server
and then served from there, through a Script (Python) object, inside an HTML
iframe. The iframe is necessary because a lot of Javascript libraries that are
not included in the Jupyter web page are loaded.

A web page with id "PivotTableJs_getMovementHistoryList" was created to demo
how pivottablejs can be integrated within ERP5, either using AJAX or not.

In the process of this integration a simple external method to render
iPython's display classes (Images, Video, Youtube, IFrame, etc) was created. It
will be refactored and polished along with the kernel itself in the future.

@kirr, @Tyagov and @tatuya, please review.

Now the ERP5 Jupyter kernel automatically renders errors that happens in the
user-side code. Errors are captured during the AST tree creation (to be able to
detect syntax errors) and at execution time. The current transaction is
automatically aborted on error detection.

/reviewed-on nexedi/erp5!85

The external method Base_displayImage displays images of two kind: plot and OFS image
saved in erp5. We had earlier checks for erp5 images but no check to for matplotlib
plot images.

erp5_data_notebook bt5: Close plot object and after every call to Base_dispalyImage with matplotlib object

erp5_dat_notebook bt5: Add Base_savePlot to JupyterCompile extension which would help creating an ERP5 Image object from matplotlib plots

mime_type for results for executed jupyter_code from JupyterCompile extension
has also been defined on the server side itself.

This would help server to have more command over what Content-Type  would be
displayed to jupyter frontend.

erp5_data_notebook bt5: Use dictionary to save module imports instead of saving it as list of strings.

Using dictinary its easier to update modules frequently.

For example, executing code:

'''
import numpy as np
import numpy
'''

would result as :
local_variable_dict['imports'] = {'numpy': 'numpy', 'np': 'numpy'}
which is what we expect to be saved in globals() also.

Problem: Module objects are not picklable, thus, trying them to save in
local_variable_dict which is further saved in ZODB via ActiveResult object
of CMFActivity was giving error. So, its better to save the module objects
as code_strings in local_variable_dict.

As for now, for example:
local_variable_dict = {'imports': ['import numpy as np', 'import matplotlib as mpl'],
			 'variables': {'a':1, 'b:2'}}
for jupyter_code = """
import numpy as np
import matplotlib as mlp
a= 1; b=2; print a+b
"""

erp5_data_notebook bt5: Use interactivity/mode and finally execute all code using exec to get rid of try:except

erp5-data-notebook bt5: Remove exception catching from Base_runJupyter external function and let the errors be raised loudly

erp5_data_notebook bt5: Add transaction abort and fail loudly in case of error in transaction script

erp5_data_notebook: Refactor jupyter_compile to only return the local variables which are added after code execution

erp5_data_notebook bt5: Updated extension JupyterCompile to use globals variable while running exec command

This BT is used to interact ERP5 with Jupyter and execute the python code.
1. External method `Base_executeJupyter` to interact between code from Jupyter and ERP5 backend.
2. Module - Data Notebooks
3. Unittest `JupyterCompile` to test external method and extensions.

* Initial Release

Due activity-race, the rules should be present before install erp5_demo_maxma_sample, because it contains simulation movements with workflows history. This case provokes the simulation be re-expanded and raising errors due missing (or not indexed) rules.

git-svn-id: https://svn.erp5.org/repos/public/erp5/trunk@44845 20353a03-c40f-0410-a6d1-a30d3c3de9de

git-svn-id: https://svn.erp5.org/repos/public/erp5/trunk@44696 20353a03-c40f-0410-a6d1-a30d3c3de9de