問題描述

性能?

我認為 api 需要更多內(nèi)存，因為 gradle 將快照該 transitive module 中的每個類，反之亦然implementation 是首選配置，因為(如上所述)它用于自己的內(nèi)部實現(xiàn).

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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