MhdZddlmZddlZddlmZddlmZddlm Z ddl m Z ddl mZd d lmZd ZGd d eeZdS)zQModule containing a preprocessor that executes the code cells and updates outputs) annotationsN) KernelManager)NotebookClient)execute)CellExecutionError) NotebookNode) PreprocessorcLddlm}|dtdt|i|S)z DEPRECATED.r)warnzThe 'nbconvert.preprocessors.execute.executenb' function was moved to nbclient.execute. We recommend importing that library directly.) stacklevel)warningsr FutureWarning_execute)argskwargsr s _/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/nbconvert/preprocessors/execute.py executenbrsMD 8  T $V $ $$c0eZdZdZdZdZ ddd ZdZdS)ExecutePreprocessorz. Executes all the cells in a notebook c |d}|t}tj|fd|i|t j||fi|dS)zInitialize the preprocessor.nbN)getrr __init__r)selfkwrs rrzExecutePreprocessor.__init__+s^ VVD\\ :Bd00r0R000b//B/////rc<|st|ds ||_dSdS)N resources)hasattrr )rr s r_check_assign_resourcesz+ExecutePreprocessor._check_assign_resources3s0  'GD+66 '&DNNN ' 'rNrrr t.AnykmKernelManager | Nonereturn%tuple[NotebookNode, dict[str, t.Any]]c2tj|||||||5|jsJ||j}|sJ|dd|jj d<t|jj D]\}}| ||| dddn #1swxYwY| |j|jfS)a Preprocess notebook executing each code cell. The input argument *nb* is modified in-place. Note that this function recalls NotebookClient.__init__, which may look wrong. However since the preprocess call acts line an init on execution state it's expected. Therefore, we need to capture it here again to properly reset because traitlet assignments are not passed. There is a risk if traitlets apply any side effects for dual init. The risk should be manageable, and this approach minimizes side-effects relative to other alternatives. One alternative but rejected implementation would be to copy the client's init internals which has already gotten out of sync with nbclient 0.5 release before nbconvert 6.0 released. Parameters ---------- nb : NotebookNode Notebook being executed. resources : dictionary (optional) Additional resources used in the conversion process. For example, passing ``{'metadata': {'path': run_path}}`` sets the execution path to ``run_path``. km: KernelManager (optional) Optional kernel manager. If none is provided, a kernel manager will be created. Returns ------- nb : NotebookNode The executed notebook. resources : dictionary Additional resources used in the conversion process. content language_infoN)rrreset_execution_trackersr" setup_kernelkcwait_for_reply kernel_informetadata enumeratecellspreprocess_cellset_widgets_metadatar )rrr r$info_msgindexcells r preprocesszExecutePreprocessor.preprocess7sWL b"--- %%''' $$Y///     = =7NNN**47+>+>+@+@AAHOOO080CO0TDG _ -(77 = = t$$T9e<<<< =  = = = = = = = = = = = = = = = !!###w&&sB C,,C03C0cn|||||d}||jfS)a Override if you want to apply some preprocessing to each cell. Must return modified cell and resource dictionary. Parameters ---------- cell : NotebookNode cell Notebook cell being processed resources : dictionary Additional resources used in the conversion process. Allows preprocessors to pass variables into the Jinja engine. index : int Index of the cell being processed T) store_history)r" execute_cellr )rr7r r6s rr3z#ExecutePreprocessor.preprocess_cellls? $$Y///  uD AAT^##r)NN)rrr r#r$r%r&r')__name__ __module__ __qualname____doc__rr"r8r3rrrr&sl000''' UY3'3'3'3'3'j$$$$$rr)r? __future__rtypingtjupyter_client.managerrnbclient.clientrrrnbclient.exceptionsrnbformatrbaser rrr@rrrIs#"""""000000******//////322222!!!!!! % % % W$W$W$W$W$,W$W$W$W$W$r