Config file and command line options#
Jupyter nbclient
can be run with a variety of command line arguments.
A list of available options can be found below in the options section.
Options#
This list of options can be generated by running the following and hitting enter:
$ jupyter execute --help-all
- Application.log_datefmtUnicode
Default:
'%Y-%m-%d %H:%M:%S'
The date format used by logging formatters for %(asctime)s
- Application.log_formatUnicode
Default:
'[%(name)s]%(highlevel)s %(message)s'
The Logging format template
- Application.log_levelany of
0``|``10``|``20``|``30``|``40``|``50``|
’DEBUG’|
’INFO’|
’WARN’|
’ERROR’|
’CRITICAL’`` Default:
30
Set the log level by value or name.
- Application.logging_configDict
Default:
{}
Configure additional log handlers.
The default stderr logs handler is configured by the log_level, log_datefmt and log_format settings.
This configuration can be used to configure additional handlers (e.g. to output the log to a file) or for finer control over the default handlers.
If provided this should be a logging configuration dictionary, for more information see: https://docs.python.org/3/library/logging.config.html#logging-config-dictschema
This dictionary is merged with the base logging configuration which defines the following:
A logging formatter intended for interactive use called
console
.A logging handler that writes to stderr called
console
which uses the formatterconsole
.A logger with the name of this application set to
DEBUG
level.
This example adds a new handler that writes to a file:
c.Application.logging_config = { "handlers": { "file": { "class": "logging.FileHandler", "level": "DEBUG", "filename": "<path/to/file>", } }, "loggers": { "<application-name>": { "level": "DEBUG", # NOTE: if you don't list the default "console" # handler here then it will be disabled "handlers": ["console", "file"], }, }, }
- Application.show_configBool
Default:
False
Instead of starting the Application, dump configuration to stdout
- Application.show_config_jsonBool
Default:
False
Instead of starting the Application, dump configuration to stdout (as JSON)
- JupyterApp.answer_yesBool
Default:
False
Answer yes to any prompts.
- JupyterApp.config_fileUnicode
Default:
''
Full path of a config file.
- JupyterApp.config_file_nameUnicode
Default:
''
Specify a config file to load.
- JupyterApp.generate_configBool
Default:
False
Generate default config file.
- JupyterApp.log_datefmtUnicode
Default:
'%Y-%m-%d %H:%M:%S'
The date format used by logging formatters for %(asctime)s
- JupyterApp.log_formatUnicode
Default:
'[%(name)s]%(highlevel)s %(message)s'
The Logging format template
- JupyterApp.log_levelany of
0``|``10``|``20``|``30``|``40``|``50``|
’DEBUG’|
’INFO’|
’WARN’|
’ERROR’|
’CRITICAL’`` Default:
30
Set the log level by value or name.
- JupyterApp.logging_configDict
Default:
{}
Configure additional log handlers.
The default stderr logs handler is configured by the log_level, log_datefmt and log_format settings.
This configuration can be used to configure additional handlers (e.g. to output the log to a file) or for finer control over the default handlers.
If provided this should be a logging configuration dictionary, for more information see: https://docs.python.org/3/library/logging.config.html#logging-config-dictschema
This dictionary is merged with the base logging configuration which defines the following:
A logging formatter intended for interactive use called
console
.A logging handler that writes to stderr called
console
which uses the formatterconsole
.A logger with the name of this application set to
DEBUG
level.
This example adds a new handler that writes to a file:
c.Application.logging_config = { "handlers": { "file": { "class": "logging.FileHandler", "level": "DEBUG", "filename": "<path/to/file>", } }, "loggers": { "<application-name>": { "level": "DEBUG", # NOTE: if you don't list the default "console" # handler here then it will be disabled "handlers": ["console", "file"], }, }, }
- JupyterApp.show_configBool
Default:
False
Instead of starting the Application, dump configuration to stdout
- JupyterApp.show_config_jsonBool
Default:
False
Instead of starting the Application, dump configuration to stdout (as JSON)
- NbClientApp.allow_errorsBool
Default:
False
When a cell raises an error the default behavior is that execution is stopped and a
nbclient.exceptions.CellExecutionError
is raised. If this flag is provided, errors are ignored and execution is continued until the end of the notebook.- NbClientApp.answer_yesBool
Default:
False
Answer yes to any prompts.
- NbClientApp.config_fileUnicode
Default:
''
Full path of a config file.
- NbClientApp.config_file_nameUnicode
Default:
''
Specify a config file to load.
- NbClientApp.generate_configBool
Default:
False
Generate default config file.
- NbClientApp.inplaceBool
Default:
False
Default is execute notebook without writing the newly executed notebook. If this flag is provided, the newly generated notebook will overwrite the input notebook.
- NbClientApp.kernel_nameUnicode
Default:
''
Name of kernel to use to execute the cells. If not set, use the kernel_spec embedded in the notebook.
- NbClientApp.log_datefmtUnicode
Default:
'%Y-%m-%d %H:%M:%S'
The date format used by logging formatters for %(asctime)s
- NbClientApp.log_formatUnicode
Default:
'[%(name)s]%(highlevel)s %(message)s'
The Logging format template
- NbClientApp.log_levelany of
0``|``10``|``20``|``30``|``40``|``50``|
’DEBUG’|
’INFO’|
’WARN’|
’ERROR’|
’CRITICAL’`` Default:
30
Set the log level by value or name.
- NbClientApp.logging_configDict
Default:
{}
Configure additional log handlers.
The default stderr logs handler is configured by the log_level, log_datefmt and log_format settings.
This configuration can be used to configure additional handlers (e.g. to output the log to a file) or for finer control over the default handlers.
If provided this should be a logging configuration dictionary, for more information see: https://docs.python.org/3/library/logging.config.html#logging-config-dictschema
This dictionary is merged with the base logging configuration which defines the following:
A logging formatter intended for interactive use called
console
.A logging handler that writes to stderr called
console
which uses the formatterconsole
.A logger with the name of this application set to
DEBUG
level.
This example adds a new handler that writes to a file:
c.Application.logging_config = { "handlers": { "file": { "class": "logging.FileHandler", "level": "DEBUG", "filename": "<path/to/file>", } }, "loggers": { "<application-name>": { "level": "DEBUG", # NOTE: if you don't list the default "console" # handler here then it will be disabled "handlers": ["console", "file"], }, }, }
- NbClientApp.notebooksList
Default:
[]
Path of notebooks to convert
- NbClientApp.output_baseUnicode
Default:
None
Write executed notebook to this file base name. Supports pattern replacements
'{notebook_name}'
, the name of the input notebook file without extension. Note that output is always relative to the parent directory of the input notebook.- NbClientApp.show_configBool
Default:
False
Instead of starting the Application, dump configuration to stdout
- NbClientApp.show_config_jsonBool
Default:
False
Instead of starting the Application, dump configuration to stdout (as JSON)
- NbClientApp.skip_cells_with_tagUnicode
Default:
'skip-execution'
Name of the cell tag to use to denote a cell that should be skipped.
- NbClientApp.startup_timeoutInt
Default:
60
The time to wait (in seconds) for the kernel to start. If kernel startup takes longer, a RuntimeError is raised.
- NbClientApp.timeoutInt
Default:
None
The time to wait (in seconds) for output from executions. If a cell execution takes longer, a TimeoutError is raised.
-1
will disable the timeout.