Kotlin Flow数据流的3种使用场景详解

  //NOTE: 下面的示例是错误写法
  lifecycleScope.launch { 
        mFlowModel.caseFlow1
            .flowWithLifecycle(lifecycle, Lifecycle.State.STARTED)
            .collect {}

        mFlowModel.caseFlow2
            .flowWithLifecycle(lifecycle, Lifecycle.State.STARTED)
            .collect {}
  }

  lifecycleScope.launch {
        launch {
            mFlowModel.caseFlow1
                .flowWithLifecycle(lifecycle, Lifecycle.State.STARTED)
                .collect {}
       }

        launch {
            mFlowModel.caseFlow2
                .flowWithLifecycle(lifecycle, Lifecycle.State.STARTED)
                .collect {}
        }
    }

// assets目录下person.json
{
	"name": "小马快跑",
	"age": 18,
	"interest": "money! lots of money!"
}

/**
 * 通过Flow方式，获取本地文件
 */
 private fun getFileInfo() {
      lifecycleScope.launch {
            flow {
                //解析本地json文件，并生成对应字符串
                val configStr = getAssetJsonInfo(requireContext(), "person.json")
                //最后将得到的实体类发送到下游
                emit(configStr)
            }
                .map { json ->
                    Gson().fromJson(json, PersonModel::class.java) //通过Gson将字符串转为实体类
                }
                .flowOn(Dispatchers.IO) //在flowOn之上的所有操作都是在IO线程中进行的
                .onStart { log("onStart") }
                .filterNotNull()
                .onCompletion { log("onCompletion") }
                .catch { ex -> log("catch:${ex.message}") }
                .collect {
                    log("collect parse result:$it")
                }
        }
  }

/**
 * 读取Assets下的json文件
 */
private fun getAssetJsonInfo(context: Context, fileName: String): String {
        val strBuilder = StringBuilder()
        var input: InputStream? = null
        var inputReader: InputStreamReader? = null
        var reader: BufferedReader? = null
        try {
            input = context.assets.open(fileName, AssetManager.ACCESS_BUFFER)
            inputReader = InputStreamReader(input, StandardCharsets.UTF_8)
            reader = BufferedReader(inputReader)
            var line: String?
            while ((reader.readLine().also { line = it }) != null) {
                strBuilder.append(line)
            }
        } catch (ex: Exception) {
            ex.printStackTrace()
        } finally {
            try {
                input?.close()
                inputReader?.close()
                reader?.close()
            } catch (e: IOException) {
                e.printStackTrace()
            }
        }
    return strBuilder.toString()
}

lifecycleScope.launch {
     lifecycle.repeatOnLifecycle(Lifecycle.State.STARTED) {
                 //将两个flow串联起来 先搜索目的地，然后到达目的地
                mFlowModel.getSearchFlow()
                    .flatMapConcat {
                        //第二个flow依赖第一个的结果
                        mFlowModel.goDestinationFlow(it)
                    }.collect {
                        mTvCallbackFlow.text = it ?: "error"
                    }
     }
}

  //ViewModel中
  //分别请求电费、水费、网费，Flow之间是并行关系
  suspend fun requestElectricCost(): Flow<ExpendModel> =
        flow {
            delay(500)
            emit(ExpendModel("电费", 10f, 500))
        }.flowOn(Dispatchers.IO)

  suspend fun requestWaterCost(): Flow<ExpendModel> =
        flow {
            delay(1000)
            emit(ExpendModel("水费", 20f, 1000))
        }.flowOn(Dispatchers.IO)

  suspend fun requestInternetCost(): Flow<ExpendModel> =
        flow {
            delay(2000)
            emit(ExpendModel("网费", 30f, 2000))
        }.flowOn(Dispatchers.IO)

  data class ExpendModel(val type: String, val cost: Float, val apiTime: Int) {
    fun info(): String {
        return "${type}: ${cost}, 接口请求耗时约$apiTime ms"
    }
}

    //UI层
    mBtnZip.setOnClickListener {
        lifecycleScope.launch {
            val electricFlow = mFlowModel.requestElectricCost()
            val waterFlow = mFlowModel.requestWaterCost()
            val internetFlow = mFlowModel.requestInternetCost()

            val builder = StringBuilder()
            var totalCost = 0f
            val startTime = System.currentTimeMillis()
            //NOTE:注意这里可以多个zip操作符来合并Flow，且多个Flow之间是并行关系
            electricFlow.zip(waterFlow) { electric, water ->
                totalCost = electric.cost + water.cost
                builder.append("${electric.info()},\n").append("${water.info()},\n")
            }.zip(internetFlow) { two, internet ->
                totalCost += internet.cost
                two.append(internet.info()).append(",\n\n总花费：$totalCost")
            }.collect {
                mTvZipResult.text = it.append("，总耗时：${System.currentTimeMillis() - startTime} ms")
            }
        }
    }