Hooks API#
Hooks are functions that allow you to “hook into” the life cycle events and state of Components. Their usage should always follow the Rules of Hooks. For most use cases the Basic Hooks should be enough, however the remaining Supplementary Hooks should fulfill less common scenarios.
Basic Hooks#
Use State#
state, set_state = use_state(initial_state)
Returns a stateful value and a function to update it.
During the first render the state
will be identical to the initial_state
passed
as the first argument. However in subsequent renders state
will take on the value
passed to set_state
.
set_state(new_state)
The set_state
function accepts a new_state
as its only argument and schedules a
re-render of the component where use_state
was initially called. During these
subsequent re-renders the state
returned by use_state
will take on the value
of new_state
.
Note
The identity of set_state
is guaranteed to be preserved across renders. This
means it can safely be omitted from dependency lists in Use Effect or
Use Callback.
Functional Updates#
If the new state is computed from the previous state, you can pass a function which accepts a single argument (the previous state) and returns the next state. Consider this simply use case of a counter where we’ve pulled out logic for increment and decremented the count:
import reactpy
def increment(last_count):
return last_count + 1
def decrement(last_count):
return last_count - 1
@reactpy.component
def Counter():
initial_count = 0
count, set_count = reactpy.hooks.use_state(initial_count)
return reactpy.html.div(
f"Count: {count}",
reactpy.html.button(
{"on_click": lambda event: set_count(initial_count)}, "Reset"
),
reactpy.html.button({"on_click": lambda event: set_count(increment)}, "+"),
reactpy.html.button({"on_click": lambda event: set_count(decrement)}, "-"),
)
reactpy.run(Counter)
We use the functional form for the “+” and “-” buttons since the next count
depends
on the previous value, while for the “Reset” button we simple assign the
initial_count
since it is independent of the prior count
. This is a trivial
example, but it demonstrates how complex state logic can be factored out into well
defined and potentially reusable functions.
Lazy Initial State#
In cases where it is costly to create the initial value for use_state
, you can pass
a constructor function that accepts no arguments instead - it will be called on the
first render of a component, but will be disregarded in all following renders:
state, set_state = use_state(lambda: some_expensive_computation(a, b, c))
Skipping Updates#
If you update a State Hook to the same value as the current state then the component which
owns that state will not be rendered again. We check if new_state is current_state
in order to determine whether there has been a change. Thus the following would not
result in a re-render:
state, set_state = use_state([])
set_state(state)
Use Effect#
use_effect(did_render)
The use_effect
hook accepts a function which may be imperative, or mutate state. The
function will be called immediately after the layout has fully updated.
Asynchronous actions, mutations, subscriptions, and other side effects can cause
unexpected bugs if placed in the main body of a component’s render function. Thus the
use_effect
hook provides a way to safely escape the purely functional world of
component render functions.
Note
Normally in React the did_render
function is called once an update has been
committed to the screen. Since no such action is performed by ReactPy, and the time
at which the update is displayed cannot be known we are unable to achieve parity
with this behavior.
Cleaning Up Effects#
If the effect you wish to enact creates resources, you’ll probably need to clean them
up. In such cases you may simply return a function that addresses this from the
did_render
function which created the resource. Consider the case of opening and
then closing a connection:
def establish_connection():
connection = open_connection()
return lambda: close_connection(connection)
use_effect(establish_connection)
The clean-up function will be run before the component is unmounted or, before the next effect is triggered when the component re-renders. You can conditionally fire events to avoid triggering them each time a component renders.
Conditional Effects#
By default, effects are triggered after every successful render to ensure that all state
referenced by the effect is up to date. However, when an effect function references
non-global variables, the effect will only if the value of that variable changes. For
example, imagine that we had an effect that connected to a url
state variable:
url, set_url = use_state("https://example.com")
def establish_connection():
connection = open_connection(url)
return lambda: close_connection(connection)
use_effect(establish_connection)
Here, a new connection will be established whenever a new url
is set.
Async Effects#
A behavior unique to ReactPy’s implementation of use_effect
is that it natively
supports async
functions:
async def non_blocking_effect():
resource = await do_something_asynchronously()
return lambda: blocking_close(resource)
use_effect(non_blocking_effect)
There are three important subtleties to note about using asynchronous effects:
The cleanup function must be a normal synchronous function.
Asynchronous effects which do not complete before the next effect is created following a re-render will be cancelled. This means an
CancelledError
will be raised somewhere in the body of the effect.An asynchronous effect may occur any time after the update which added this effect and before the next effect following a subsequent update.
Manual Effect Conditions#
In some cases, you may want to explicitly declare when an effect should be triggered.
You can do this by passing dependencies
to use_effect
. Each of the following
values produce different effect behaviors:
use_effect(..., dependencies=None)
- triggers and cleans up on every render.use_effect(..., dependencies=[])
- only triggers on the first and cleans up after the last render.use_effect(..., dependencies=[x, y])
- triggers on the first render and on subsequent renders ifx
ory
have changed.
Use Context#
value = use_context(MyContext)
Accepts a context object (the value returned from
reactpy.core.hooks.create_context()
) and returns the current context value for that
context. The current context value is determined by the value
argument passed to the
nearest MyContext
in the tree.
When the nearest <MyContext.Provider> above the component updates, this Hook will trigger a rerender with the latest context value passed to that MyContext provider. Even if an ancestor uses React.memo or shouldComponentUpdate, a rerender will still happen starting at the component itself using useContext.
Supplementary Hooks#
Use Reducer#
state, dispatch_action = use_reducer(reducer, initial_state)
An alternative and derivative of Use State the use_reducer
hook, instead of
directly assigning a new state, allows you to specify an action which will transition
the previous state into the next state. This transition is defined by a reducer function
of the form (current_state, action) -> new_state
. The use_reducer
hook then
returns the current state and a dispatch_action
function that accepts an action
and causes a transition to the next state via the reducer
.
use_reducer
is generally preferred to use_state
if logic for transitioning from
one state to the next is especially complex or involves nested data structures.
use_reducer
can also be used to collect several use_state
calls together - this
may be slightly more performant as well as being preferable since there is only one
dispatch_action
callback versus the many set_state
callbacks.
We can rework the Functional Updates counter example to use use_reducer
:
import reactpy
def reducer(count, action):
if action == "increment":
return count + 1
elif action == "decrement":
return count - 1
elif action == "reset":
return 0
else:
msg = f"Unknown action '{action}'"
raise ValueError(msg)
@reactpy.component
def Counter():
count, dispatch = reactpy.hooks.use_reducer(reducer, 0)
return reactpy.html.div(
f"Count: {count}",
reactpy.html.button({"on_click": lambda event: dispatch("reset")}, "Reset"),
reactpy.html.button({"on_click": lambda event: dispatch("increment")}, "+"),
reactpy.html.button({"on_click": lambda event: dispatch("decrement")}, "-"),
)
reactpy.run(Counter)
Note
The identity of the dispatch_action
function is guaranteed to be preserved
across re-renders throughout the lifetime of the component. This means it can safely
be omitted from dependency lists in Use Effect or Use Callback.
Use Callback#
memoized_callback = use_callback(lambda: do_something(a, b))
A derivative of Use Memo, the use_callback
hook returns a
memoized callback. This is useful when passing callbacks to child
components which check reference equality to prevent unnecessary renders. The
memoized_callback
will only change when any local variables is references do.
Note
You may manually specify what values the callback depends on in the same way
as effects using the dependencies
parameter.
Use Memo#
memoized_value = use_memo(lambda: compute_something_expensive(a, b))
Returns a memoized value. By passing a constructor function accepting
no arguments and an array of dependencies for that constructor, the use_callback
hook will return the value computed by the constructor. The memoized_value
will only
be recomputed if a local variable referenced by the constructor changes (e.g. a
or
b
here). This optimizes performance because you don’t need to
compute_something_expensive
on every render.
Unlike use_effect
the constructor function is called during each render (instead of
after) and should not incur side effects.
Warning
Remember that you shouldn’t optimize something unless you know it’s a performance
bottleneck. Write your code without use_memo
first and then add it to targeted
sections that need a speed-up.
Note
You may manually specify what values the callback depends on in the same way
as effects using the dependencies
parameter.
Use Ref#
ref_container = use_ref(initial_value)
Returns a mutable Ref
object that has a single
current
attribute that at first contains the initial_state
.
The identity of the Ref
object will be preserved for the lifetime of the component.
A Ref
is most useful if you need to incur side effects since updating its
.current
attribute doesn’t trigger a re-render of the component. You’ll often use this
hook alongside Use Effect or in response to component event handlers.
Rules of Hooks#
Hooks are just normal Python functions, but there’s a bit of magic to them, and in order for that magic to work you’ve got to follow two rules. Thankfully we supply a Flake8 Plugin to help enforce them.
Only call outside flow controls#
Don’t call hooks inside loops, conditions, or nested functions. Instead you must
always call hooks at the top level of your functions. By adhering to this rule you
ensure that hooks are always called in the exact same order. This fact is what allows
ReactPy to preserve the state of hooks between multiple calls to useState
and
useEffect
calls.
Only call in render functions#
Don’t call hooks from regular Python functions. Instead you should:
✅ Call Hooks from a component’s render function.
✅ Call Hooks from another custom hook
Following this rule ensures stateful logic for ReactPy component is always clearly separated from the rest of your codebase.
Flake8 Plugin#
We provide a Flake8 plugin called flake8-reactpy-hooks that helps
to enforce the two rules described above. You can pip
install it directly, or with
the lint
extra for ReactPy:
pip install flake8-reactpy-hooks
Once installed running, flake8
on your code will start catching errors. For example:
flake8 my_reactpy_components.py
Might produce something like the following output:
./my_reactpy_components:10:8 ROH102 hook 'use_effect' used inside if statement
./my_reactpy_components:23:4 ROH102 hook 'use_state' used outside component or hook definition
See the Flake8 docs for more info.