问题描述
性能?
我认为 api
需要更多内存,因为 gradle 将快照该 transitive module 中的每个类,反之亦然implementation
是首选配置,因为(如上所述)它用于自己的内部实现.
The docs mention that implementation
provides significant build time improvements over compile
/api
. What about compileOnly
?
My use case is a multi-module (sorry I don't like Gradle's multi-project terminology) project, where I have an Android app, and multiple libraries that the app depends on (implementation
). Some of the libraries also depend on one another. Should I use implementation
or compileOnly
when declaring dependencies in the library modules? My app module will be using implementation
to depend on those artifacts, so I don't need them to be transitive through the library modules.
The api
configuration should be used for dependencies that are exported to external modules
(transitive dependency). Vice-Versa implementation
configuration should be used for dependencies that are internal to the component (not transitive dependency).
implementation vs compileOnly:
There is no similarity in their job, compileOnly
is
- a configuration inherited from java-plugin
- required at compile time
- also not included in the runtime classpath or exposed to dependent projects.
So compileOnly
doesn't replace the implementation
configuration job e.g:
implementation 'com.android.support:appcompat-v7:25.1.0' // can't use compileOnly here
testCompile 'junit:junit:4.12'
compile "com.google.dagger:dagger:2.8" // can't use here also
annotationProcessor "com.google.dagger:dagger-compiler:2.8" // can't use here also
compileOnly 'javax.annotation:jsr250-api:1.0' // we can use compileOnly here because it's required on run time only.
Since your case is a "multi-module", you have to use the api
configuration, until you reach the final module it's better to use implementation
.
Following graph describe those configurations:
Performance?
I think api
requires more memory because gradle will snapshot every class in that transitive module, vice versa implementation
is a preferred configuration because (as mentioned above) it's used for its own internal implementations.
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