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plugcli 0.2.0
plugcli
Simple click-based tools for plugin-based CLIs.
plugcli is a small extension of
click. It provides several
useful pieces of functionality, including:
A plugin registration system, allowing user-created plugins to be registered
either by installing in a given namespace or by adding plugin files to a
specified directory.
A CLI class that uses that plugin registration system to register new
subcommands, and which separates subcommands into sections for the --help
documentation.
Tools to facilitate reuse of parameters between different subcommands,
helping ensure a consistent user interface. While much of this is already
enabled by click, the tools in plugcli are particularly useful in cases
where click's callbacks may not be sufficient, such as when the order in
which parameters are parsed is important.
Installing plugcli
plugcli can be installed through the standard mechanisms: pip install plugcli; or conda install -c conda-forge plugcli, or install from source
using setuptools (python setup.py install, etc.) Its only direct dependency
is click.
Plugin registration
The plugin registration system is designed to handle plugins that can
essentially be treated as entries in a dispatch table. That is, these are
plugins that are designed to give optionally-used additional functionality.
Subcommands of the CLI are one example, and plugcli provides specific tools
for this use case. Other examples might support for additional keywords when
processing a user input file, or support for other options in menus for
interactive user interfaces.
The basic approach to writing plugins is to wrap user-defined functionality in
some subclass of the plugcli.Plugin class, which may also encapsulate
additional metadata of use to the program. For example, the
plugcli.CommandPlugin class also takes a section label, to tell which help
section the plugin command should be listed in.
A program defines where a user can put plugins by creating one or more
PluginLoaders. The two concrete classes of PluginLoader are
FilePluginLoader, which takes a directory and searches for any plugins in
Python files in that directory, and the NamespacePluginLoader, which takes a
string representing a Python namespace and searches for any plugins in
modules/subpackages found in that namespace.
CLI Class
The plugcli.CLI class subclasses click.CLI, adding support for loading
commands from the plugcli plugin structure, and sorting commands in --help
into sections defined by the developer.
Users must subclass plugcli.CLI. The subclass should set the class variable
COMMAND_SECTIONS to a list of the section names used in sorting plugins for
the help. The subclass should also implement the get_installed_plugins
method, which uses a selection of PluginLoaders that determine the locations
where plugins will be found and registered.
Reusable parameters
The goal of plugcli's reusable parameters is to ensure consistency throughout
different subcommands by encapsulating names and behavior of parameters that
can be shared. This is done with the plugcli.Option and plugcli.Argument
classes, which take the same parameters as the click.option and
click.parameter decorators, plus a getter keyword-only argument that takes
an callable which converts the user input as processed by click and returns
an object ready for use in the CLI's underlying library code. This takes a
user-defined context dict, which provides more flexibility than the standard
click callbacks.
You can create a standard click decorator for one of these parameters with the
.parameter() method, allowing a single parameter instance to be reused in
multiple subcommands. click arguments set in the initialization of the
plugcli parameter can be overridden by keyword arguments passed to the
.parameter method, allowing some customizability in special cases (e.g., to
allow the parameter to be called a different number of times) while retaining
most of the consistency.
History
plugcli was originally part of the OpenPathSampling
CLI. It was
refactored into a separate package as it become more evident that it filled a
small, but useful, niche, and could be reused in other projects.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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