Advanced Groups and Context

In addition to the capabilities covered in the previous section, Groups have more advanced capabilities that leverage the Context.

Callback Invocation

For a regular command, the callback is executed whenever the command runs. If the script is the only command, it will always fire (unless a parameter callback prevents it. This for instance happens if someone passes --help to the script).

For groups, the situation looks different. In this case, the callback fires whenever a subcommand fires. What this means in practice is that an outer command runs when an inner command runs:

@click.group()
@click.option('--debug/--no-debug', default=False)
def cli(debug):
    click.echo(f"Debug mode is {'on' if debug else 'off'}")

@cli.command()  # @cli, not @click!
def sync():
    click.echo('Syncing')

Here is what this looks like:

$ tool.py
Usage: tool.py [OPTIONS] COMMAND [ARGS]...

Options:
  --debug / --no-debug
  --help                Show this message and exit.

Commands:
  sync

$ tool.py --debug sync
Debug mode is on
Syncing

Nested Handling and Contexts

As you can see from the earlier example, the basic command group accepts a debug argument which is passed to its callback, but not to the sync command itself. The sync command only accepts its own arguments.

This allows tools to act completely independent of each other, but how does one command talk to a nested one? The answer to this is the Context.

Each time a command is invoked, a new context is created and linked with the parent context. Normally, you can’t see these contexts, but they are there. Contexts are passed to parameter callbacks together with the value automatically. Commands can also ask for the context to be passed by marking themselves with the pass_context() decorator. In that case, the context is passed as first argument.

The context can also carry a program specified object that can be used for the program’s purposes. What this means is that you can build a script like this:

@click.group()
@click.option('--debug/--no-debug', default=False)
@click.pass_context
def cli(ctx, debug):
    # ensure that ctx.obj exists and is a dict (in case `cli()` is called
    # by means other than the `if` block below)
    ctx.ensure_object(dict)

    ctx.obj['DEBUG'] = debug

@cli.command()
@click.pass_context
def sync(ctx):
    click.echo(f"Debug is {'on' if ctx.obj['DEBUG'] else 'off'}")

if __name__ == '__main__':
    cli(obj={})

If the object is provided, each context will pass the object onwards to its children, but at any level a context’s object can be overridden. To reach to a parent, context.parent can be used.

In addition to that, instead of passing an object down, nothing stops the application from modifying global state. For instance, you could just flip a global DEBUG variable and be done with it.

Decorating Commands

As you have seen in the earlier example, a decorator can change how a command is invoked. What actually happens behind the scenes is that callbacks are always invoked through the Context.invoke() method which automatically invokes a command correctly (by either passing the context or not).

This is very useful when you want to write custom decorators. For instance, a common pattern would be to configure an object representing state and then storing it on the context and then to use a custom decorator to find the most recent object of this sort and pass it as first argument.

For instance, the pass_obj() decorator can be implemented like this:

from functools import update_wrapper

def pass_obj(f):
    @click.pass_context
    def new_func(ctx, *args, **kwargs):
        return ctx.invoke(f, ctx.obj, *args, **kwargs)
    return update_wrapper(new_func, f)

The Context.invoke() command will automatically invoke the function in the correct way, so the function will either be called with f(ctx, obj) or f(obj) depending on whether or not it itself is decorated with pass_context().

This is a very powerful concept that can be used to build very complex nested applications; see Complex Applications for more information.

Command Chaining

It is useful to invoke more than one subcommand in one call. For example, my-app validate build upload would invoke validate, then build, then upload. To implement this, pass chain=True when creating a group.

@click.group(chain=True)
def cli():
    pass

@cli.command('validate')
def validate():
    click.echo('validate')

@cli.command('build')
def build():
    click.echo('build')

You can invoke it like this:

$ my-app validate build
validate
build

When using chaining, there are a few restrictions:

  • Only the last command may use nargs=-1 on an argument, otherwise the parser will not be able to find further commands.

  • It is not possible to nest groups below a chain group.

  • On the command line, options must be specified before arguments for each command in the chain.

  • The Context.invoked_subcommand attribute will be '*' because the parser doesn’t know the full list of commands that will run yet.

Command Pipelines

When using chaining, a common pattern is to have each command process the result of the previous command.

A straightforward way to do this is to use make_pass_decorator() to pass a context object to each command, and store and read the data on that object.

pass_ns = click.make_pass_decorator(dict, ensure=True)

@click.group(chain=True)
@click.argument("name")
@pass_ns
def cli(ns, name):
    ns["name"] = name

@cli.command
@pass_ns
def lower(ns):
    ns["name"] = ns["name"].lower()

@cli.command
@pass_ns
def show(ns):
    click.echo(ns["name"])

$ process Click show lower show
Click
click

Another way to do this is to collect data returned by each command, then process it at the end of the chain. Use the group’s result_callback() decorator to register a function that is called after the chain is finished. It is passed the list of return values as well as any parameters registered on the group.

A command can return anything, including a function. Here’s an example of that, where each subcommand creates a function that processes the input, then the result callback calls each function. The command takes a file, processes each line, then outputs it. If no subcommands are given, it outputs the contents of the file unchanged.

@click.group(chain=True, invoke_without_command=True)
@click.argument("fin", type=click.File("r"))
def cli(fin):
    pass

@cli.result_callback()
def process_pipeline(processors, fin):
    iterator = (x.rstrip("\r\n") for x in input)

    for processor in processors:
        iterator = processor(iterator)

    for item in iterator:
        click.echo(item)

@cli.command("upper")
def make_uppercase():
    def processor(iterator):
        for line in iterator:
            yield line.upper()
    return processor

@cli.command("lower")
def make_lowercase():
    def processor(iterator):
        for line in iterator:
            yield line.lower()
    return processor

@cli.command("strip")
def make_strip():
    def processor(iterator):
        for line in iterator:
            yield line.strip()
    return processor

That’s a lot in one go, so let’s go through it step by step.

  1. The first thing is to make a group() that is chainable. In addition to that we also instruct Click to invoke even if no subcommand is defined. If this would not be done, then invoking an empty pipeline would produce the help page instead of running the result callbacks.

  2. The next thing we do is to register a result callback on our group. This callback will be invoked with an argument which is the list of all return values of all subcommands and then the same keyword parameters as our group itself. This means we can access the input file easily there without having to use the context object.

  3. In this result callback we create an iterator of all the lines in the input file and then pass this iterator through all the returned callbacks from all subcommands and finally we print all lines to stdout.

After that point we can register as many subcommands as we want and each subcommand can return a processor function to modify the stream of lines.

One important thing of note is that Click shuts down the context after each callback has been run. This means that for instance file types cannot be accessed in the processor functions as the files will already be closed there. This limitation is unlikely to change because it would make resource handling much more complicated. For such it’s recommended to not use the file type and manually open the file through open_file().

For a more complex example that also improves upon handling of the pipelines, see the imagepipe example in the Click repository. It implements a pipeline based image editing tool that has a nice internal structure.

Overriding Defaults

By default, the default value for a parameter is pulled from the default flag that is provided when it’s defined, but that’s not the only place defaults can be loaded from. The other place is the Context.default_map (a dictionary) on the context. This allows defaults to be loaded from a configuration file to override the regular defaults.

This is useful if you plug in some commands from another package but you’re not satisfied with the defaults.

The default map can be nested arbitrarily for each subcommand:

default_map = {
    "debug": True,  # default for a top level option
    "runserver": {"port": 5000}  # default for a subcommand
}

The default map can be provided when the script is invoked, or overridden at any point by commands. For instance, a top-level command could load the defaults from a configuration file.

Example usage:

import click

@click.group()
def cli():
    pass

@cli.command()
@click.option('--port', default=8000)
def runserver(port):
    click.echo(f"Serving on http://127.0.0.1:{port}/")

if __name__ == '__main__':
    cli(default_map={
        'runserver': {
            'port': 5000
        }
    })

And in action:

$ cli runserver
Serving on http://127.0.0.1:5000/

Context Defaults

Changelog

Added in version 2.0.

Starting with Click 2.0 you can override defaults for contexts not just when calling your script, but also in the decorator that declares a command. For instance given the previous example which defines a custom default_map this can also be accomplished in the decorator now.

This example does the same as the previous example:

import click

CONTEXT_SETTINGS = dict(
    default_map={'runserver': {'port': 5000}}
)

@click.group(context_settings=CONTEXT_SETTINGS)
def cli():
    pass

@cli.command()
@click.option('--port', default=8000)
def runserver(port):
    click.echo(f"Serving on http://127.0.0.1:{port}/")

if __name__ == '__main__':
    cli()

And again the example in action:

$ cli runserver
Serving on http://127.0.0.1:5000/

Command Return Values

Changelog

Added in version 3.0.

One of the new introductions in Click 3.0 is the full support for return values from command callbacks. This enables a whole range of features that were previously hard to implement.

In essence any command callback can now return a value. This return value is bubbled to certain receivers. One usecase for this has already been show in the example of Command Chaining where it has been demonstrated that chained groups can have callbacks that process all return values.

When working with command return values in Click, this is what you need to know:

  • The return value of a command callback is generally returned from the Command.invoke() method. The exception to this rule has to do with Groups:

    • In a group the return value is generally the return value of the subcommand invoked. The only exception to this rule is that the return value is the return value of the group callback if it’s invoked without arguments and invoke_without_command is enabled.

    • If a group is set up for chaining then the return value is a list of all subcommands’ results.

    • Return values of groups can be processed through a Group.result_callback. This is invoked with the list of all return values in chain mode, or the single return value in case of non chained commands.

  • The return value is bubbled through from the Context.invoke() and Context.forward() methods. This is useful in situations where you internally want to call into another command.

  • Click does not have any hard requirements for the return values and does not use them itself. This allows return values to be used for custom decorators or workflows (like in the command chaining example).

  • When a Click script is invoked as command line application (through Command.main()) the return value is ignored unless the standalone_mode is disabled in which case it’s bubbled through.