Ekhlass/flutter_docs · Datasets at Hugging Face

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and receive responses to those messages.
however, you can’t receive unsolicited messages from the host platform.
as an example,
you can’t set up a long-lived firestore listener in a background isolate,
because firestore uses platform channels to push updates to flutter,
which are unsolicited.
you can, however, query firestore for a response in the background.
<topic_end>
<topic_start>
more information
for more information on isolates, check out the following resources:
<topic_end>
<topic_start>
performance FAQ
this page collects some frequently asked questions
about evaluating and debugging flutter’s performance.
<topic_end>
<topic_start>
more thoughts about performance
<topic_end>
<topic_start>
what is performance?
performance is a set of quantifiable properties of a performer.
in this context, performance isn’t the execution of an action itself;
it’s how well something or someone performs. therefore, we use the adjective
performant.
while the how well part can, in general, be described in natural languages,
in our limited scope, the focus is on something that is quantifiable as a real
number. real numbers include integers and 0/1 binaries as special cases.
natural language descriptions are still very important. for example, a news
article that heavily criticizes flutter’s performance by just using words
without any numbers (a quantifiable value) could still be meaningful, and it
could have great impacts. the limited scope is chosen only because of our
limited resources.
the required quantity to describe performance is often referred to as a
metric.
to navigate through countless performance issues and metrics, you can categorize
based on performers.
for example, most of the content on this website is about the flutter app
performance, where the performer is a flutter app. infra performance is also
important to flutter, where the performers are build bots and CI task runners:
they heavily affect how fast flutter can incorporate code changes, to improve
the app’s performance.
here, the scope was intentionally broadened to include performance issues other
than just app performance issues because they can share many tools regardless of
who the performers are. for example, flutter app performance and infra
performance might share the same dashboard and similar alert mechanisms.
broadening the scope also allows performers to be included that traditionally
are easy to ignore. document performance is such an example. the performer
could be an API doc of the SDK, and a metric could be: the percentage of readers
who find the API doc useful.
<topic_end>
<topic_start>
why is performance important?
answering this question is not only crucial for validating the work in
performance, but also for guiding the performance work in order to be more
useful. the answer to “why is performance important?” often is also the answer
to “how is performance useful?”
simply speaking, performance is important and useful because, in the scope,
performance must have quantifiable properties or metrics. this implies:
not that non-performance, or non-measurable issues or descriptions are not
important. they’re meant to highlight the scenarios where performance can be
more useful.
<topic_end>
<topic_start>
1. a performance report is easy to consume
performance metrics are numbers. reading a number is much easier than reading a
passage. for example, it probably takes an engineer 1 second to consume the
performance rating as a number from 1 to 5. it probably takes the same engineer
at least 1 minute to read the full, 500-word feedback summary.
if there are many numbers, it’s easy to summarize or visualize them for quick
consumption. for example, you can quickly consume millions of numbers by
looking at its histogram, average, quantiles, and so on. if a metric has a
history of thousands of data points, then you can easily plot a timeline to
read its trend.
on the other hand, having n number of 500-word texts almost guarantees an
n-time cost to consume those texts. it would be a daunting task to analyze
thousands of historical descriptions, each having 500 words.
<topic_end>
<topic_start>
2. performance has little ambiguity
another advantage of having performance as a set of numbers is its unambiguity.
when you want an animation to have a performance of 20 ms per frame or
50 fps, there’s little room for different interpretations about the numbers. on
the other hand, to describe the same animation in words, someone might call it
good, while someone else might complain that it’s bad. similarly, the same
word or phrase could be interpreted differently by different people. you might
interpret an OK frame rate to be 60 fps, while someone else might interpret it
to be 30 fps.
numbers can still be noisy. for example, the measured time per frame might
be a true computation time of this frame, plus a random amount of time (noise)
that CPU/GPU spends on some unrelated work. hence, the metric fluctuates.
nevertheless, there’s no ambiguity of what the number means. and, there are
also rigorous theory and testing tools to handle such noise. for example, you
could take multiple measurements to estimate the distribution of a random
variable, or you could take the average of many measurements to eliminate the
noise by the law of large numbers.
<topic_end>
<topic_start>
3. performance is comparable and convertible

and receive responses to those messages.

however, you can’t receive unsolicited messages from the host platform.

as an example,

you can’t set up a long-lived firestore listener in a background isolate,

because firestore uses platform channels to push updates to flutter,

which are unsolicited.

you can, however, query firestore for a response in the background.

<topic_end>

<topic_start>

more information

for more information on isolates, check out the following resources:

<topic_end>

<topic_start>

performance FAQ

this page collects some frequently asked questions

about evaluating and debugging flutter’s performance.

<topic_end>

<topic_start>

more thoughts about performance

<topic_end>

<topic_start>

what is performance?

performance is a set of quantifiable properties of a performer.

in this context, performance isn’t the execution of an action itself;

it’s how well something or someone performs. therefore, we use the adjective

performant.

while the how well part can, in general, be described in natural languages,

in our limited scope, the focus is on something that is quantifiable as a real

number. real numbers include integers and 0/1 binaries as special cases.

natural language descriptions are still very important. for example, a news

article that heavily criticizes flutter’s performance by just using words

without any numbers (a quantifiable value) could still be meaningful, and it

could have great impacts. the limited scope is chosen only because of our

limited resources.

the required quantity to describe performance is often referred to as a

metric.

to navigate through countless performance issues and metrics, you can categorize

based on performers.

for example, most of the content on this website is about the flutter app

performance, where the performer is a flutter app. infra performance is also

important to flutter, where the performers are build bots and CI task runners:

they heavily affect how fast flutter can incorporate code changes, to improve

the app’s performance.

here, the scope was intentionally broadened to include performance issues other

than just app performance issues because they can share many tools regardless of

who the performers are. for example, flutter app performance and infra

performance might share the same dashboard and similar alert mechanisms.

broadening the scope also allows performers to be included that traditionally

are easy to ignore. document performance is such an example. the performer

could be an API doc of the SDK, and a metric could be: the percentage of readers

who find the API doc useful.

<topic_end>

<topic_start>

why is performance important?

answering this question is not only crucial for validating the work in

performance, but also for guiding the performance work in order to be more

useful. the answer to “why is performance important?” often is also the answer

to “how is performance useful?”

simply speaking, performance is important and useful because, in the scope,

performance must have quantifiable properties or metrics. this implies:

not that non-performance, or non-measurable issues or descriptions are not

important. they’re meant to highlight the scenarios where performance can be

more useful.

<topic_end>

<topic_start>

1. a performance report is easy to consume

performance metrics are numbers. reading a number is much easier than reading a

passage. for example, it probably takes an engineer 1 second to consume the

performance rating as a number from 1 to 5. it probably takes the same engineer

at least 1 minute to read the full, 500-word feedback summary.

if there are many numbers, it’s easy to summarize or visualize them for quick

consumption. for example, you can quickly consume millions of numbers by

looking at its histogram, average, quantiles, and so on. if a metric has a

history of thousands of data points, then you can easily plot a timeline to

read its trend.

on the other hand, having n number of 500-word texts almost guarantees an

n-time cost to consume those texts. it would be a daunting task to analyze

thousands of historical descriptions, each having 500 words.

<topic_end>

<topic_start>

2. performance has little ambiguity

another advantage of having performance as a set of numbers is its unambiguity.

when you want an animation to have a performance of 20 ms per frame or

50 fps, there’s little room for different interpretations about the numbers. on

the other hand, to describe the same animation in words, someone might call it

good, while someone else might complain that it’s bad. similarly, the same

word or phrase could be interpreted differently by different people. you might

interpret an OK frame rate to be 60 fps, while someone else might interpret it

to be 30 fps.

numbers can still be noisy. for example, the measured time per frame might

be a true computation time of this frame, plus a random amount of time (noise)

that CPU/GPU spends on some unrelated work. hence, the metric fluctuates.

nevertheless, there’s no ambiguity of what the number means. and, there are

also rigorous theory and testing tools to handle such noise. for example, you

could take multiple measurements to estimate the distribution of a random

variable, or you could take the average of many measurements to eliminate the

noise by the law of large numbers.

<topic_end>

<topic_start>

3. performance is comparable and convertible