Add pyupgrade and doc8 hooks (#768)

Author: blink1073

.pre-commit-config.yaml

@@ -36,6 +36,18 @@ repos:
     hooks:
       - id: prettier
 
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v2.31.1
+    hooks:
+      - id: pyupgrade
+        args: [--py37-plus]
+
+  - repo: https://github.com/PyCQA/doc8
+    rev: 0.11.0
+    hooks:
+      - id: doc8
+        args: [--max-line-length=200]
+
   - repo: https://github.com/pycqa/flake8
     rev: 4.0.1
     hooks:

docs/source/conf.py

@@ -1,5 +1,4 @@
 #!/usr/bin/env python3
-# -*- coding: utf-8 -*-
 #
 # Jupyter Server documentation build configuration file, created by
 # sphinx-quickstart on Mon Apr 13 09:51:11 2015.

docs/source/developers/dependency.rst

@@ -1,9 +1,15 @@
 Depending on Jupyter Server
 ===========================
 
-If your project depends directly on Jupyter Server, be sure to watch Jupyter Server's ChangeLog and pin your project to a version that works for your application. Major releases represent possible backwards-compatibility breaking API changes or features.
-
-When a new major version in released on PyPI, a branch for that version will be created in this repository, and the version of the master branch will be bumped to the next major version number. That way, the master branch always reflects the latest un-released version.
+If your project depends directly on Jupyter Server, be sure to watch Jupyter
+Server's ChangeLog and pin your project to a version that works for your
+application. Major releases represent possible backwards-compatibility breaking
+API changes or features.
+
+When a new major version in released on PyPI, a branch for that version will be
+created in this repository, and the version of the master branch will be bumped
+to the next major version number. That way, the master branch always reflects
+the latest un-released version.
 
 To install the latest patch of a given version:
 

docs/source/developers/extensions.rst

@@ -10,7 +10,9 @@ You can check some simple examples on the `examples folder
 Authoring a basic server extension
 ==================================
 
-The simplest way to write a Jupyter Server extension is to write an extension module with a ``_load_jupyter_server_extension`` function. This function should take a single argument, an instance of the ``ServerApp``.
+The simplest way to write a Jupyter Server extension is to write an extension
+module with a ``_load_jupyter_server_extension`` function. This function should
+take a single argument, an instance of the ``ServerApp``.
 
 
 .. code-block:: python
@@ -62,7 +64,11 @@ Then add this handler to Jupyter Server's Web Application through the ``_load_ju
 Making an extension discoverable
 --------------------------------
 
-To make this extension discoverable to Jupyter Server, first define a ``_jupyter_server_extension_points()`` function at the root of the module/package. This function returns metadata describing how to load the extension. Usually, this requires a ``module`` key with the import path to the extension's ``_load_jupyter_server_extension`` function.
+To make this extension discoverable to Jupyter Server, first define a
+``_jupyter_server_extension_points()`` function at the root of the module/
+package. This function returns metadata describing how to load the extension.
+Usually, this requires a ``module`` key with the import path to the extension's
+``_load_jupyter_server_extension`` function.
 
 .. code-block:: python
 
@@ -85,7 +91,10 @@ Second, add the extension to the ServerApp's ``jpserver_extensions`` trait. This
         "my_extension": True
     }
 
-or loaded from a JSON file in the ``jupyter_server_config.d`` directory under one of `Jupyter's paths`_. (See the `Distributing a server extension`_ section for details on how to automatically enabled your extension when users install it.)
+or loaded from a JSON file in the ``jupyter_server_config.d`` directory under
+one of `Jupyter's paths`_. (See the `Distributing a server extension`_ section
+for details on how to automatically enabled your extension when users install
+it.)
 
 .. code-block:: python
 
@@ -161,7 +170,10 @@ The basic structure of an ExtensionApp is shown below:
             # Perform any required shut down steps
 
 
-The ``ExtensionApp`` uses the following methods and properties to connect your extension to the Jupyter server. You do not need to define a ``_load_jupyter_server_extension`` function for these apps. Instead, overwrite the pieces below to add your custom settings, handlers and templates:
+The ``ExtensionApp`` uses the following methods and properties to connect your
+extension to the Jupyter server. You do not need to define a
+``_load_jupyter_server_extension`` function for these apps. Instead, overwrite
+the pieces below to add your custom settings, handlers and templates:
 
 Methods
 
@@ -212,7 +224,9 @@ Jinja templating from frontend extensions
 
 Many Jupyter frontend applications use Jinja for basic HTML templating. Since this is common enough, Jupyter Server provides some extra mixin that integrate Jinja with Jupyter server extensions.
 
-Use ``ExtensionAppJinjaMixin`` to automatically add a Jinja templating environment to an ``ExtensionApp``. This adds a ``<name>_jinja2_env`` setting to Tornado Web Server's settings that will be used by request handlers.
+Use ``ExtensionAppJinjaMixin`` to automatically add a Jinja templating
+environment to an ``ExtensionApp``. This adds a ``<name>_jinja2_env`` setting
+to Tornado Web Server's settings that will be used by request handlers.
 
 .. code-block:: python
 
@@ -224,7 +238,9 @@ Use ``ExtensionAppJinjaMixin`` to automatically add a Jinja templating environme
         ...
 
 
-Pair the example above with ``ExtensionHandlers`` that also inherit the ``ExtensionHandlerJinjaMixin`` mixin. This will automatically load HTML templates from the Jinja templating environment created by the ``ExtensionApp``.
+Pair the example above with ``ExtensionHandlers`` that also inherit the
+``ExtensionHandlerJinjaMixin`` mixin. This will automatically load HTML
+templates from the Jinja templating environment created by the ``ExtensionApp``.
 
 
 .. code-block:: python
@@ -347,7 +363,10 @@ Putting it all together, authors can distribute their extension following this s
     This is where the extension logic will live (i.e. custom extension handlers, config, etc). See the sections above for more information on how to create an extension.
 
 3. Add the following JSON config file to the extension package.
-    The file should be named after the extension (e.g. ``myextension.json``) and saved in a subdirectory of the package with the prefix: ``jupyter-config/jupyter_server_config.d/``. The extension package will have a similar structure to this example:
+    The file should be named after the extension (e.g. ``myextension.json``)
+    and saved in a subdirectory of the package with the prefix:
+    ``jupyter-config/jupyter_server_config.d/``. The extension package will
+    have a similar structure to this example:
 
     .. code-block::
 
@@ -413,12 +432,18 @@ Putting it all together, authors can distribute their extension following this s
 Migrating an extension to use Jupyter Server
 ============================================
 
-If you're a developer of a `classic Notebook Server`_ extension, your extension should be able to work with *both* the classic notebook server and ``jupyter_server``.
+If you're a developer of a `classic Notebook Server`_ extension, your extension
+should be able to work with *both* the classic notebook server and
+``jupyter_server``.
 
 There are a few key steps to make this happen:
 
 1. Point Jupyter Server to the ``load_jupyter_server_extension`` function with a new reference name.
-    The ``load_jupyter_server_extension`` function was the key to loading a server extension in the classic Notebook Server. Jupyter Server expects the name of this function to be prefixed with an underscore—i.e. ``_load_jupyter_server_extension``. You can easily achieve this by adding a reference to the old function name with the new name in the same module.
+    The ``load_jupyter_server_extension`` function was the key to loading a
+    server extension in the classic Notebook Server. Jupyter Server expects the
+    name of this function to be prefixed with an underscore—i.e.
+    ``_load_jupyter_server_extension``. You can easily achieve this by adding a
+    reference to the old function name with the new name in the same module.
 
     .. code-block:: python
 
@@ -483,7 +508,10 @@ There are a few key steps to make this happen:
         )
 
 3. (Optional) Point extension at the new favicon location.
-    The favicons in the Jupyter Notebook have been moved to a new location in Jupyter Server. If your extension is using one of these icons, you'll want to add a set of redirect handlers this. (In ``ExtensionApp``, this is handled automatically).
+    The favicons in the Jupyter Notebook have been moved to a new location in
+    Jupyter Server. If your extension is using one of these icons, you'll want
+    to add a set of redirect handlers this. (In ``ExtensionApp``, this is
+    handled automatically).
 
     This usually means adding a chunk to your ``load_jupyter_server_extension`` function similar to this:
 

docs/source/developers/websocket-protocols.rst

@@ -8,7 +8,10 @@ The Jupyter Server needs to pass messages between kernels and the Jupyter web ap
 ZeroMQ wire protocol
 --------------------
 
-The kernel wire protocol over ZeroMQ takes advantage of multipart messages, allowing to decompose a message into parts and to send and receive them unmerged. The following table shows the message format (the beginning has been omitted for clarity):
+The kernel wire protocol over ZeroMQ takes advantage of multipart messages,
+allowing to decompose a message into parts and to send and receive them
+unmerged. The following table shows the message format (the beginning has been
+omitted for clarity):
 
 .. list-table:: Format of a kernel message over ZeroMQ socket (indices refer to parts, not bytes)
    :header-rows: 1

docs/source/operators/configuring-extensions.rst

@@ -3,7 +3,9 @@
 Configuring Extensions
 ======================
 
-Some Jupyter Server extensions are also configurable applications. There are two ways to configure such extensions: i) pass arguments to the extension's entry point or ii) list configurable options in a Jupyter config file.
+Some Jupyter Server extensions are also configurable applications. There are
+two ways to configure such extensions: i) pass arguments to the extension's
+entry point or ii) list configurable options in a Jupyter config file.
 
 Jupyter Server looks for an extension's config file in a set of specific paths. Use the ``jupyter`` entry point to list these paths:
 
@@ -45,7 +47,9 @@ A Jupyter Server will automatically load config for each enabled extension. You
 Extension config on the command line
 ------------------------------------
 
-Server extension applications can also be configured from the command line, and multiple extension can be configured at the same time. Simply pass the traits (with their appropriate prefix) to the ``jupyter server`` entrypoint, e.g.:
+Server extension applications can also be configured from the command line, and
+multiple extension can be configured at the same time. Simply pass the traits
+(with their appropriate prefix) to the ``jupyter server`` entrypoint, e.g.:
 
 .. code-block:: console
 

docs/source/operators/multiple-extensions.rst

@@ -4,7 +4,11 @@
 Managing multiple extensions
 ----------------------------
 
-One of the major benefits of Jupyter Server is that you can run serve multiple Jupyter frontend applications above the same Tornado web server. That's because every Jupyter frontend application is now a server extension. When you run a Jupyter Server will multiple extensions enabled, each extension appends its own set of handlers and static assets to the server.
+One of the major benefits of Jupyter Server is that you can run serve multiple
+Jupyter frontend applications above the same Tornado web server.
+That's because every Jupyter frontend application is now a server extension.
+When you run a Jupyter Server will multiple extensions enabled, each extension
+appends its own set of handlers and static assets to the server.
 
 Listing extensions
 ~~~~~~~~~~~~~~~~~~

docs/source/operators/public-server.rst

@@ -113,13 +113,13 @@ Preparing a hashed password
 You can prepare a hashed password manually, using the function
 :func:`notebook.auth.security.passwd`:
 
-.. code-block:: ipython
+.. code-block:: python
 
-    In [1]: from jupyter_server.auth import passwd
-    In [2]: passwd()
-    Enter password:
-    Verify password:
-    Out[2]: 'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
+    >>> from jupyter_server.auth import passwd
+    >>> passwd()
+    ... Enter password:
+    ... Verify password:
+    'sha1:67c9e60bb8b6:9ffede0825894254b2e042ea597d771089e11aed'
 
 .. caution::
 

docs/source/other/full-config.rst

@@ -514,7 +514,11 @@ ServerApp.show_config_json : Bool
 ServerApp.shutdown_no_activity_timeout : Int
     Default: ``0``
 
-    Shut down the server after N seconds with no kernels or terminals running and no activity. This can be used together with culling idle kernels (MappingKernelManager.cull_idle_timeout) to shutdown the Jupyter server when it's not in use. This is not precisely timed: it may shut down up to a minute later. 0 (the default) disables this automatic shutdown.
+    Shut down the server after N seconds with no kernels or terminals running
+    and no activity. This can be used together with culling idle kernels
+    (MappingKernelManager.cull_idle_timeout) to shutdown the Jupyter server
+    when it's not in use. This is not precisely timed: it may shut down up to
+    a minute later. 0 (the default) disables this automatic shutdown.
 
 ServerApp.ssl_options : Dict
     Default: ``{}``

docs/source/users/configuration.rst

@@ -27,7 +27,10 @@ By default, Jupyter Server looks for server-specific configuration in a ``jupyte
 The paths under ``config`` are listed in order of precedence. If the same trait is listed in multiple places, it will be set to the value from the file will highest precendence.
 
 
-Jupyter Server uses IPython's traitlets system for configuration. Traits can be listed in a Python or JSON config file. You can quickly create a ``jupyter_server_config.py`` file in the ``.jupyter`` directory, with all the defaults commented out, use the following command:
+Jupyter Server uses IPython's traitlets system for configuration. Traits can be
+listed in a Python or JSON config file. You can quickly create a
+``jupyter_server_config.py`` file in the ``.jupyter`` directory, with all the
+defaults commented out, use the following command:
 
 .. code-block:: console