面向chatGPT开发随记

Q

运单是一次运输的记录，以下为java环境，现有一个shipment的list。
shipment有以下字段，运单号code，承运商号carrierCode，车辆编号vehicleCode，司机编号driverCode，人员2类型driver2Type，人员2编号driver2Code。
需要统计每个承运商下：
1、单驾-车辆：对只参与单驾驶员(driver2Code为null)的运输的车辆统计个数，车辆编号vehicleCode
2、单驾-司机：对只参与单驾驶员(driver2Code为null)的运输的司机统计个数，司机编号driverCode

chatGPT

你可以通过遍历这个shipment的列表，并使用HashMap来对承运商进行分类和统计。以下是一个基础的示例，用于解释如何进行统计：

import java.util.*;class Shipment {String code;String carrierCode;String vehicleCode;String driverCode;String driver2Type;String driver2Code;// 构造器，getter和setter方法...
}public class ShipmentStatistics {public static void main(String[] args) {List<Shipment> shipments = new ArrayList<>();// 假设shipments已经初始化...Map<String, Set<String>> carrierVehicleMap = new HashMap<>();Map<String, Set<String>> carrierDriverMap = new HashMap<>();for (Shipment shipment : shipments) {if (shipment.getDriver2Code() == null) { // 单驾驶员String carrier = shipment.getCarrierCode();// 统计车辆Set<String> vehicleSet = carrierVehicleMap.getOrDefault(carrier, new HashSet<>());vehicleSet.add(shipment.getVehicleCode());carrierVehicleMap.put(carrier, vehicleSet);// 统计司机Set<String> driverSet = carrierDriverMap.getOrDefault(carrier, new HashSet<>());driverSet.add(shipment.getDriverCode());carrierDriverMap.put(carrier, driverSet);}}// 打印结果for (String carrier : carrierVehicleMap.keySet()) {System.out.println("承运商 " + carrier + " 的单驾-车辆数: " + carrierVehicleMap.get(carrier).size());System.out.println("承运商 " + carrier + " 的单驾-司机数: " + carrierDriverMap.get(carrier).size());}}
}

在这个示例中，我们遍历了所有的Shipment对象。如果一个Shipment是单驾驶员运输（driver2Code为null），我们就把这个Shipment的车辆编号和司机编号分别添加到对应承运商的Set中（使用HashMap存储）。这样我们就可以统计每个承运商的单驾-车辆数和单驾-司机数。

注意：在这个示例中，我们使用HashSet来存储车辆编号和司机编号，这是因为Set不包含重复的元素，所以能自动处理可能出现的重复编号。而HashMap的getOrDefault方法则可以方便地处理当承运商还没有被添加到map时的情况。

Q

请注意，我需要统计的不是单驾驶员的运单下面的情况，而是这个车辆/司机只参加过单驾驶员运输，才统计

chatGPT

谢谢你的澄清，理解了你的需求后，我发现确实需要稍微调整原来的逻辑。

我们需要对每一个承运商下的车辆和司机进行两次遍历。在第一次遍历中，我们需要检查哪些车辆和司机仅仅参与了单驾驶员的运输。在第二次遍历中，我们需要移除那些同时参与了单驾和双驾驶员运输的车辆和司机。

以下是修改后的代码：

import java.util.*;class Shipment {String code;String carrierCode;String vehicleCode;String driverCode;String driver2Type;String driver2Code;// 构造器，getter和setter方法...
}public class ShipmentStatistics {public static void main(String[] args) {List<Shipment> shipments = new ArrayList<>();// 假设shipments已经初始化...Map<String, Set<String>> carrierSingleVehicleMap = new HashMap<>();Map<String, Set<String>> carrierSingleDriverMap = new HashMap<>();Map<String, Set<String>> carrierDoubleVehicleMap = new HashMap<>();Map<String, Set<String>> carrierDoubleDriverMap = new HashMap<>();for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();if (shipment.getDriver2Code() == null) { // 单驾驶员// 统计车辆Set<String> vehicleSet = carrierSingleVehicleMap.getOrDefault(carrier, new HashSet<>());vehicleSet.add(shipment.getVehicleCode());carrierSingleVehicleMap.put(carrier, vehicleSet);// 统计司机Set<String> driverSet = carrierSingleDriverMap.getOrDefault(carrier, new HashSet<>());driverSet.add(shipment.getDriverCode());carrierSingleDriverMap.put(carrier, driverSet);} else { // 双驾驶员// 统计车辆Set<String> vehicleSet = carrierDoubleVehicleMap.getOrDefault(carrier, new HashSet<>());vehicleSet.add(shipment.getVehicleCode());carrierDoubleVehicleMap.put(carrier, vehicleSet);// 统计司机Set<String> driverSet = carrierDoubleDriverMap.getOrDefault(carrier, new HashSet<>());driverSet.add(shipment.getDriverCode());carrierDoubleDriverMap.put(carrier, driverSet);}}// 移除同时参与了单驾和双驾驶员运输的车辆和司机for (String carrier : carrierSingleVehicleMap.keySet()) {carrierSingleVehicleMap.get(carrier).removeAll(carrierDoubleVehicleMap.get(carrier));carrierSingleDriverMap.get(carrier).removeAll(carrierDoubleDriverMap.get(carrier));}// 打印结果for (String carrier : carrierSingleVehicleMap.keySet()) {System.out.println("承运商 " + carrier + " 的单驾-车辆数: " + carrierSingleVehicleMap.get(carrier).size());System.out.println("承运商 " + carrier + " 的单驾-司机数: " + carrierSingleDriverMap.get(carrier).size());}}
}

在这个代码中，我们首先统计所有单驾驶员和双

驾驶员的运输任务，并将它们分别存储在两个不同的Map中。然后，我们从单驾驶员的Map中移除那些同时参与了单驾和双驾驶员运输的车辆和司机。最后，我们就可以得到只参与了单驾驶员运输的车辆和司机的数量。

Q

carrierSingleVehicleMap.get(carrier).removeAll(carrierDoubleVehicleMap.get(carrier)); 这一行空指针了

chatGPT

对不起，我疏忽了这个问题。如果承运商仅参与了单驾驶员的运输任务，但没有参与双驾驶员的运输任务，那么在carrierDoubleVehicleMap中将找不到对应的承运商，这就会导致Null Pointer Exception。

我们可以通过使用getOrDefault方法来解决这个问题，当在carrierDoubleVehicleMap中找不到承运商时，返回一个空的HashSet。下面是修改后的代码：

// 移除同时参与了单驾和双驾驶员运输的车辆和司机
for (String carrier : carrierSingleVehicleMap.keySet()) {carrierSingleVehicleMap.get(carrier).removeAll(carrierDoubleVehicleMap.getOrDefault(carrier, new HashSet<>()));carrierSingleDriverMap.get(carrier).removeAll(carrierDoubleDriverMap.getOrDefault(carrier, new HashSet<>()));
}

这样，当在carrierDoubleVehicleMap和carrierDoubleDriverMap中找不到承运商时，`

Q

在前面的基础上，我要修改我的要求。运单是一次运输的记录，以下为java环境，现有一个shipment的list。
shipment有以下字段，运单号code，承运商号carrierCode，车辆编号vehicleCode，司机编号driverCode，人员2类型driver2Type，人员2编号driverCode2。
单驾运输：(driver2Type为null)的运输
双驾运输：(driver2Type为2)的运输
单押运输：(driver2Type为3、4)的运输
需要统计每个承运商下：
1.1、单驾-车辆：对只参加过单驾运输的车辆统计个数，车辆编号vehicleCode去重
1.2、单驾-司机：对只参加过单驾运输的司机统计个数，司机编号driverCode去重
2.1、双驾-车辆：对只参加过双驾运输的车辆统计个数，车辆编号vehicleCode去重
2.2、双驾-司机：对只参加过双驾运输的司机统计个数，司机编号driverCode去重
3.1、单押-车辆：对只参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
3.2、单押-司机：对只参加过单押运输的司机统计个数，司机编号driverCode去重
4.1、混合单驾双驾-车辆：对参加过单押运输并且参加过双驾运输的车辆统计个数，车辆编号vehicleCode去重
4.2、混合单驾双驾-司机：对参加过单押运输并且参加过双驾运输的司机统计个数，司机编号driverCode去重
5.1、混合单驾单押-车辆：对参加过单押运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
5.2、混合单驾单押-司机：对参加过单押运输并且参加过单押运输的司机统计个数，司机编号driverCode去重
6.1、混合双驾单押-车辆：对参加过双驾运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
6.2、混合双驾单押-司机：对参加过双驾运输并且参加过单押运输的司机统计个数，司机编号driverCode去重
7.1、全混合-车辆：对参加过单押运输并且参加过双驾运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
7.2、全混合-司机：对参加过单押运输并且参加过双驾运输并且参加过单押运输的司机统计个数，司机编号driverCode去重

chatGPT

这个问题的难度相比之前提高了许多，因为现在需要考虑更多的运输类型以及它们的组合。首先，我们需要将所有的运输类型和它们的组合定义出来。接着，我们需要为每一个承运商和每一种运输类型分别创建一个存储车辆和司机编号的HashSet。最后，我们需要遍历所有的运输记录，根据运输类型将车辆和司机编号添加到对应的HashSet中。遍历完成后，我们需要根据运输类型的组合创建新的HashSet，用于存储满足特定组合条件的车辆和司机编号。

由于代码相对复杂，我将会将其分解成多个步骤。以下是首个步骤，它创建了所有需要的数据结构，并初始化了它们：

class Shipment {String code;String carrierCode;String vehicleCode;String driverCode;String driver2Type;String driver2Code;// 构造函数，getters和setters...
}enum ShipmentType {SINGLE_DRIVE,DOUBLE_DRIVE,SINGLE_ESCORT,MIX_SINGLE_DOUBLE,MIX_SINGLE_ESCORT,MIX_DOUBLE_ESCORT,MIX_ALL
}Map<ShipmentType, Map<String, Set<String>>> vehicleMap = new HashMap<>();
Map<ShipmentType, Map<String, Set<String>>> driverMap = new HashMap<>();for (ShipmentType type : ShipmentType.values()) {vehicleMap.put(type, new HashMap<>());driverMap.put(type, new HashMap<>());
}

现在，我们有了用于存储每种运输类型和承运商的车辆和司机编号的数据结构。接下来，我们需要遍历所有的运输记录，并根据运输类型将车辆和司机编号添加到对应的HashSet中。以下是下一个步骤，它执行了这个任务：

List<Shipment> shipments = new ArrayList<>(); // 假设shipments已经初始化...for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();ShipmentType type = null;if (shipment.getDriver2Type() == null) { // 单驾驶员type = ShipmentType.SINGLE_DRIVE;} else if (shipment.getDriver2Type().equals("2")) { // 双驾驶员type = ShipmentType.DOUBLE_DRIVE;} else if (shipment.getDriver2Type().equals("3") || shipment.getDriver2Type().equals("4")) { // 单押运输type = ShipmentType.SINGLE_ESCORT;}if (type != null) {// 添加车辆编号Set<String> vehicleSet = vehicleMap.get(type).getOrDefault(carrier, new HashSet<>());vehicleSet.add(shipment.getVehicleCode());vehicleMap.get(type).put(carrier, vehicleSet);// 添加司机编号Set<String> driverSet = driverMap.get(type).getOrDefault(carrier, new HashSet<>());driverSet.add(shipment.getDriverCode());driverMap.get(type).put(carrier, driverSet);}
}

接下来的步骤是通过运输类型的组合来创建新的HashSet，存储满足特定组合条件的车辆和司机编号。在这个步骤中，我们需要遍历所有的承运商，并将满足特定组合条件的车辆和司机编号添加到新的HashSet中。这个步骤会涉及到许多的代码，因此我建议您先尝试实现上述的步骤，并确保它们正确无误。在您准备好继续下一个步骤时，我会继续提供帮助。

Q

把刚才的代码放到一个方法里，再次压缩代码

chatGPT

好的，我会将这些代码整合成一个方法，并简化其中一些冗余的代码。在下面的实现中，我会创建一个calculateShipmentStats方法，这个方法会接收一个List<Shipment>参数，并返回一个包含所有结果的Map。

public class ShipmentStatsCalculator {enum ShipmentType {SINGLE_DRIVE,DOUBLE_DRIVE,SINGLE_ESCORT// 对应的组合类型在后面的计算中增加}public Map<String, Map<ShipmentType, Map<String, Integer>>> calculateShipmentStats(List<Shipment> shipments) {Map<String, Map<ShipmentType, Map<String, Set<String>>>> carrierShipmentStats = new HashMap<>();for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();ShipmentType type = determineShipmentType(shipment);if (type != null) {carrierShipmentStats.putIfAbsent(carrier, new HashMap<>());Map<ShipmentType, Map<String, Set<String>>> typeMap = carrierShipmentStats.get(carrier);addShipmentToTypeMap(typeMap, type, shipment

Q

我的环境是java8，把刚才的代码放到一个方法里，再次压缩代码

chatGPT

对不起，我疏忽了你的环境是Java 8，因为 Map 的 putIfAbsent, computeIfAbsent 等函数是在 Java 8 之后的版本中才引入的。让我们对代码进行一些修改以使其兼容 Java 8。以下是使用 Java 8 的语法创建 calculateShipmentStats 方法的新版本：

public class ShipmentStatsCalculator {enum ShipmentType {SINGLE_DRIVE,DOUBLE_DRIVE,SINGLE_ESCORT}private ShipmentType determineShipmentType(Shipment shipment) {if (shipment.getDriver

Q

我的环境是java8，不支持本地枚举，把刚才的代码放到一个方法里，再次压缩代码

chatGPT

对不起，我疏忽了你的环境限制。你可以将枚举转换成字符串常量来进行处理。这里是使用字符串常量进行修改的新版本：

import java.util.*;public class ShipmentStatsCalculator {private static final String SINGLE_DRIVE = "SINGLE_DRIVE";private static final String DOUBLE_DRIVE = "DOUBLE_DRIVE";private static final String SINGLE_ESCORT = "SINGLE_ESCORT";public Map<String, Map<String, Map<String, Set<String>>>> calculateShipmentStats(List<Shipment> shipments) {Map<String, Map<String, Map<String, Set<String>>>> carrierShipmentStats = new HashMap<>();for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();String type = determineShipmentType(shipment);if (type != null) {if (!carrierShipmentStats.containsKey(carrier)) {carrierShipmentStats.put(carrier, new HashMap<>());}Map<String, Map<String, Set<String>>> typeMap = carrierShipmentStats.get(carrier);addShipmentToTypeMap(typeMap, type, shipment);}}// 进行后续的处理，例如统计各种类型组合的情况等return carrierShipmentStats;}private String determineShipmentType(Shipment shipment) {if (shipment.getDriver2Type() == null) {return SINGLE_DRIVE;} else if ("2".equals(shipment.getDriver2Type())) {return DOUBLE_DRIVE;} else if ("3".equals(shipment.getDriver2Type()) || "4".equals(shipment.getDriver2Type())) {return SINGLE_ESCORT;} else {return null;}}private void addShipmentToTypeMap(Map<String, Map<String, Set<String>>> typeMap, String type, Shipment shipment) {if (!typeMap.containsKey(type)) {typeMap.put(type

Q

运单是一次运输的记录，以下为java8环境，现有一个shipment的list。
shipment有以下字段，运单号code，承运商号carrierCode，车辆编号vehicleCode，司机编号driverCode，人员2类型driver2Type，人员2编号driverCode2。
单驾运输：(driver2Type为null)的运输
双驾运输：(driver2Type为2)的运输
单押运输：(driver2Type为3、4)的运输
需要统计每个承运商下：
1.1、单驾-车辆：对只参加过单驾运输的车辆统计个数，车辆编号vehicleCode去重
1.2、单驾-司机：对只参加过单驾运输的司机统计个数，司机编号driverCode去重
2.1、双驾-车辆：对只参加过双驾运输的车辆统计个数，车辆编号vehicleCode去重
2.2、双驾-司机：对只参加过双驾运输的司机统计个数，司机编号driverCode去重
3.1、单押-车辆：对只参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
3.2、单押-司机：对只参加过单押运输的司机统计个数，司机编号driverCode去重
4.1、混合单驾双驾-车辆：对参加过单押运输并且参加过双驾运输的车辆统计个数，车辆编号vehicleCode去重
4.2、混合单驾双驾-司机：对参加过单押运输并且参加过双驾运输的司机统计个数，司机编号driverCode去重
5.1、混合单驾单押-车辆：对参加过单押运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
5.2、混合单驾单押-司机：对参加过单押运输并且参加过单押运输的司机统计个数，司机编号driverCode去重
6.1、混合双驾单押-车辆：对参加过双驾运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
6.2、混合双驾单押-司机：对参加过双驾运输并且参加过单押运输的司机统计个数，司机编号driverCode去重
7.1、全混合-车辆：对参加过单押运输并且参加过双驾运输并且参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
7.2、全混合-司机：对参加过单押运输并且参加过双驾运输并且参加过单押运输的司机统计个数，司机编号driverCode去重
请注意，比如1.1我需要统计的不是单驾驶员的运单下面的情况，而是这个车辆/司机只参加过单驾驶员运输，才统计。

chatGPT

这个问题可以通过使用一个嵌套的 HashMap 解决，以车辆编号和司机编号为键，每个键关联一个 HashSet 来存储每个车辆和司机参与的运输类型。我们可以在遍历 shipment 列表的过程中建立这个映射，然后通过检查每个车辆和司机的运输类型集合来得到所需的统计信息。以下是基于这个思路的 Java 代码示例：

import java.util.*;public class ShipmentStatsCalculator {private static final String SINGLE_DRIVE = "SINGLE_DRIVE";private static final String DOUBLE_DRIVE = "DOUBLE_DRIVE";private static final String SINGLE_ESCORT = "SINGLE_ESCORT";private static final String DRIVER = "DRIVER";private static final String VEHICLE = "VEHICLE";public Map<String, Map<String, Integer>> calculateShipmentStats(List<Shipment> shipments) {Map<String, Map<String, Set<String>>> carrierVehicleTypes = new HashMap<>();Map<String, Map<String, Set<String>>> carrierDriverTypes = new HashMap<>();// Step 1: Record the shipment types that each vehicle and driver have participated in.for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();String vehicle = shipment.getVehicleCode();String driver = shipment.getDriverCode();String type = determineShipmentType(shipment);if (type != null) {if (!carrierVehicleTypes.containsKey(carrier)) {carrierVehicleTypes.put(carrier, new HashMap<>());carrierDriverTypes.put(carrier, new HashMap<>());}Map<String, Set<String>> vehicleTypes = carrierVehicleTypes.get(carrier);Map<String, Set<String>> driverTypes = carrierDriverTypes.get(carrier);if (!vehicleTypes.containsKey(vehicle)) {vehicleTypes.put(vehicle, new HashSet<>());}if (!driverTypes.containsKey(driver)) {driverTypes.put(driver, new HashSet<>());}vehicleTypes.get(vehicle).add(type);driverTypes.get(driver).add(type);}}// Step 2: Compute the statistics based on the recorded shipment types.Map<String, Map<String, Integer>> stats = new HashMap<>();for (String carrier : carrierVehicleTypes.keySet()) {Map<String, Set<String>> vehicleTypes = carrierVehicleTypes.get(carrier);Map<String, Set<String>> driverTypes = carrierDriverTypes.get(carrier);int singleDriveVehicleCount = 0, doubleDriveVehicleCount = 0, singleEscortVehicleCount = 0;int singleDriveDriverCount = 0, doubleDriveDriverCount = 0, singleEscortDriverCount = 0;// TODO: 计算混合类型的情况for (Set<String> types : vehicleTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveVehicleCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveVehicleCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortVehicleCount++;}}}for (Set<String> types : driverTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveDriverCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveDriverCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortDriverCount++;}}}// TODO: 将计算的结果加入 stats}return stats;}private String determineShipmentType(Shipment shipment) {if (shipment.getDriver2Type() == null) {return SINGLE_DRIVE;} else if ("2".equals(shipment.getDriver2Type())) {return DOUBLE_DRIVE;} else if ("3".equals(shipment.getDriver2Type()) || "4".equals(shipment.getDriver2Type())) {return SINGLE_ESCORT;} else {return null;}}
}

注意，上面的代码还没有完成混合类型的计算，这部分需要根据具体的业务逻辑来判断如何划分混合类型。比如，“混合单驾双驾-车辆”可能是指这个车辆参与过的运输类型只包括单驾和双驾，但没有包括单押。如果是这样，你可以在第二步中添加相应的判断逻辑。

此外，将计算的结果加入 stats 的部分也需要你根据实际需求来实现，你可能需要创建一个复杂的数据结构来存储这些统计信息。你可以考虑使用一个类或者 Map 的嵌套来存储这些信息。

Q

混合部分为多种都参与过的情况，请补全代码
4.1、混合单驾双驾-车辆：对参加过单押运输,并且也参加过双驾运输的车辆统计个数，车辆编号vehicleCode去重
4.2、混合单驾双驾-司机：对参加过单押运输,并且也参加过双驾运输的司机统计个数，司机编号driverCode去重
5.1、混合单驾单押-车辆：对参加过单押运输,并且也参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
5.2、混合单驾单押-司机：对参加过单押运输,并且也参加过单押运输的司机统计个数，司机编号driverCode去重
6.1、混合双驾单押-车辆：对参加过双驾运输,并且也参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
6.2、混合双驾单押-司机：对参加过双驾运输,并且也参加过单押运输的司机统计个数，司机编号driverCode去重
7.1、全混合-车辆：对参加过单押运输,并且也参加过双驾运输,并且也参加过单押运输的车辆统计个数，车辆编号vehicleCode去重
7.2、全混合-司机：对参加过单押运输,并且也参加过双驾运输,并且也参加过单押运输的司机统计个数，司机编号driverCode去重

chatGPT

了解了，我们可以为混合类型的统计添加一些额外的逻辑。具体的代码可能像下面这样：

    // Step 2: Compute the statistics based on the recorded shipment types.Map<String, Map<String, Integer>> stats = new HashMap<>();for (String carrier : carrierVehicleTypes.keySet()) {Map<String, Set<String>> vehicleTypes = carrierVehicleTypes.get(carrier);Map<String, Set<String>> driverTypes = carrierDriverTypes.get(carrier);int singleDriveVehicleCount = 0, doubleDriveVehicleCount = 0, singleEscortVehicleCount = 0;int singleDriveDriverCount = 0, doubleDriveDriverCount = 0, singleEscortDriverCount = 0;int mixedDriveEscortVehicleCount = 0, mixedDriveEscortDriverCount = 0;int mixedDoubleEscortVehicleCount = 0, mixedDoubleEscortDriverCount = 0;int mixedSingleDoubleVehicleCount = 0, mixedSingleDoubleDriverCount = 0;int mixedAllVehicleCount = 0, mixedAllDriverCount = 0;for (Set<String> types : vehicleTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveVehicleCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveVehicleCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortVehicleCount++;}} else if (types.size() == 2) {if (types.contains(SINGLE_DRIVE) && types.contains(DOUBLE_DRIVE)) {mixedSingleDoubleVehicleCount++;} else if (types.contains(SINGLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDriveEscortVehicleCount++;} else if (types.contains(DOUBLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDoubleEscortVehicleCount++;}} else if (types.size() == 3) {mixedAllVehicleCount++;}}for (Set<String> types : driverTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveDriverCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveDriverCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortDriverCount++;}} else if (types.size() == 2) {if (types.contains(SINGLE_DRIVE) && types.contains(DOUBLE_DRIVE)) {mixedSingleDoubleDriverCount++;} else if (types.contains(SINGLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDriveEscortDriverCount++;} else if (types.contains(DOUBLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDoubleEscortDriverCount++;}} else if (types.size() == 3) {mixedAllDriverCount++;}}// TODO: 将计算的结果加入 stats}return stats;

注意，我在代码中假设的是，如果一个车辆或司机参与了两种运输类型，那么它们就是混合类型。如果参与了三种运输类型，那么它们就是全混合类型。根据你的具体需求，这部分的逻辑可能需要

做出相应的调整。

最后，你还需要实现如何将这些统计结果加入到 stats 中。你可能需要创建一个类来表示统计结果，或者使用一个 Map 的嵌套结构来存储这些信息。你可能需要的键可能包括"carrier", “shipmentType”（如"singleDrive", “doubleDrive”, “singleEscort"等）和"role”（如"vehicle", “driver”）。

Q

不要再代码里写todo了，后面的这种情况都需要补充好完整的代码。现在，再次输出完整代码

chatGPT

明白了，我已经为每个承运商创建了一个映射来存储这些统计数据。这里是完整的代码：

import java.util.*;public class ShipmentStatistics {// Constants for shipment typesprivate static final String SINGLE_DRIVE = "SINGLE_DRIVE";private static final String DOUBLE_DRIVE = "DOUBLE_DRIVE";private static final String SINGLE_ESCORT = "SINGLE_ESCORT";public static Map<String, Map<String, Integer>> computeStatistics(List<Shipment> shipments) {// Step 1: Record the types of shipments each vehicle and driver has participated in.Map<String, Map<String, Set<String>>> carrierVehicleTypes = new HashMap<>();Map<String, Map<String, Set<String>>> carrierDriverTypes = new HashMap<>();for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();String vehicle = shipment.getVehicleCode();String driver = shipment.getDriverCode();String shipmentType;if (shipment.getDriver2Type() == null) {shipmentType = SINGLE_DRIVE;} else if (shipment.getDriver2Type() == 2) {shipmentType = DOUBLE_DRIVE;} else {shipmentType = SINGLE_ESCORT;}carrierVehicleTypes.computeIfAbsent(carrier, k -> new HashMap<>()).computeIfAbsent(vehicle, k -> new HashSet<>()).add(shipmentType);carrierDriverTypes.computeIfAbsent(carrier, k -> new HashMap<>()).computeIfAbsent(driver, k -> new HashSet<>()).add(shipmentType);}// Step 2: Compute the statistics based on the recorded shipment types.Map<String, Map<String, Integer>> stats = new HashMap<>();for (String carrier : carrierVehicleTypes.keySet()) {Map<String, Set<String>> vehicleTypes = carrierVehicleTypes.get(carrier);Map<String, Set<String>> driverTypes = carrierDriverTypes.get(carrier);int singleDriveVehicleCount = 0, doubleDriveVehicleCount = 0, singleEscortVehicleCount = 0;int singleDriveDriverCount = 0, doubleDriveDriverCount = 0, singleEscortDriverCount = 0;int mixedDriveEscortVehicleCount = 0, mixedDriveEscortDriverCount = 0;int mixedDoubleEscortVehicleCount = 0, mixedDoubleEscortDriverCount = 0;int mixedSingleDoubleVehicleCount = 0, mixedSingleDoubleDriverCount = 0;int mixedAllVehicleCount = 0, mixedAllDriverCount = 0;for (Set<String> types : vehicleTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveVehicleCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveVehicleCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortVehicleCount++;}} else if (types.size() == 2) {if (types.contains(SINGLE_DRIVE) && types.contains(DOUBLE_DRIVE)) {mixedSingleDoubleVehicleCount++;} else if (types.contains(SINGLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDriveEscortVehicleCount++;} else if (types.contains(DOUBLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDoubleEscortVehicleCount++;}} else if (types.size() == 3) {mixedAllVehicleCount++;}}for (Set<String> types : driverTypes.values()) {if (types.size() == 1) {String type = types.iterator().next();if (SINGLE_DRIVE.equals(type)) {singleDriveDriverCount++;} else if (DOUBLE_DRIVE.equals(type)) {doubleDriveDriverCount++;} else if (SINGLE_ESCORT.equals(type)) {singleEscortDriverCount++;}} else if (types.size() == 2) {if (types.contains(SINGLE_DRIVE) && types.contains(DOUBLE_DRIVE)) {mixedSingleDoubleDriverCount++;} else if (types.contains(SINGLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDriveEscortDriverCount++;} else if (types.contains(DOUBLE_DRIVE) && types.contains(SINGLE_ESCORT)) {mixedDoubleEscortDriverCount++;}} else if (types.size() == 3) {mixedAllDriverCount++;}}Map<String, Integer> carrierStats = new HashMap<>();carrierStats.put("singleDriveVehicleCount", singleDriveVehicleCount);carrierStats.put("doubleDriveVehicleCount", doubleDriveVehicleCount);carrierStats.put("singleEscortVehicleCount", singleEscortVehicleCount);carrierStats.put("singleDriveDriverCount", singleDriveDriverCount);carrierStats.put("doubleDriveDriverCount", doubleDriveDriverCount);carrierStats.put("singleEscortDriverCount", singleEscortDriverCount);carrierStats.put("mixedDriveEscortVehicleCount", mixedDriveEscortVehicleCount);carrierStats.put("mixedDriveEscortDriverCount", mixedDriveEscortDriverCount);carrierStats.put("mixedDoubleEscortVehicleCount", mixedDoubleEscortVehicleCount);carrierStats.put("mixedDoubleEscortDriverCount", mixedDoubleEscortDriverCount);carrierStats.put("mixedSingleDoubleVehicleCount", mixedSingleDoubleVehicleCount);carrierStats.put("mixedSingleDoubleDriverCount", mixedSingleDoubleDriverCount);carrierStats.put("mixedAllVehicleCount", mixedAllVehicleCount);carrierStats.put("mixedAllDriverCount", mixedAllDriverCount);stats.put(carrier, carrierStats);}return stats;}
}

这段代码首先遍历每个运单，记录每个承运商的车辆和司机参与的运输类型。然后，再根据记录的运输类型计算每个承运商的统计数据。

注意，这段代码还没有处理可能的空值。例如，如果一个运单没有司机编号或者车辆编号，这段代码可能会出现空指针异常。在实际使用这段代码时，你可能需要做一些额外的检查和处理。

Q

你的代码很棒，能不能优化一下格式和性能

chatGPT

我很高兴你喜欢这段代码！现在来优化代码的性能和格式。

首先，对于性能的优化，由于我们使用的是 HashMap 和 HashSet 这样的数据结构，时间复杂度已经是 O(n)（n 为运单数量），这已经是最优的时间复杂度。对于内存优化，由于需要存储所有运单的车辆、司机和类型信息，空间复杂度也是 O(n)，也是相对较优的。

不过，我们可以在代码的可读性和简洁性方面进行一些优化。例如，我们可以使用 Java 8 的 Stream API 来简化和美化代码：

import java.util.*;
import java.util.stream.Collectors;public class ShipmentStatistics {// Constants for shipment typesprivate static final String SINGLE_DRIVE = "SINGLE_DRIVE";private static final String DOUBLE_DRIVE = "DOUBLE_DRIVE";private static final String SINGLE_ESCORT = "SINGLE_ESCORT";private static final Set<String> ALL_TYPES = new HashSet<>(Arrays.asList(SINGLE_DRIVE, DOUBLE_DRIVE, SINGLE_ESCORT));public static Map<String, Map<String, Integer>> computeStatistics(List<Shipment> shipments) {// Record the types of shipments each vehicle and driver has participated inMap<String, Map<String, Set<String>>> carrierVehicleTypes = new HashMap<>();Map<String, Map<String, Set<String>>> carrierDriverTypes = new HashMap<>();for (Shipment shipment : shipments) {String carrier = shipment.getCarrierCode();String vehicle = shipment.getVehicleCode();String driver = shipment.getDriverCode();String shipmentType;if (shipment.getDriver2Type() == null) {shipmentType = SINGLE_DRIVE;} else if (shipment.getDriver2Type() == 2) {shipmentType = DOUBLE_DRIVE;} else {shipmentType = SINGLE_ESCORT;}carrierVehicleTypes.computeIfAbsent(carrier, k -> new HashMap<>()).computeIfAbsent(vehicle, k -> new HashSet<>()).add(shipmentType);carrierDriverTypes.computeIfAbsent(carrier, k -> new HashMap<>()).computeIfAbsent(driver, k -> new HashSet<>()).add(shipmentType);}// Compute the statistics based on the recorded shipment typesreturn carrierVehicleTypes.keySet().stream().collect(Collectors.toMap(carrier -> carrier,carrier -> {Map<String, Set<String>> vehicleTypes = carrierVehicleTypes.get(carrier);Map<String, Set<String>> driverTypes = carrierDriverTypes.get(carrier);Map<String, Integer> carrierStats = new HashMap<>();carrierStats.put("singleDriveVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.size() == 1 && types.contains(SINGLE_DRIVE)).count());carrierStats.put("doubleDriveVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.size() == 1 && types.contains(DOUBLE_DRIVE)).count());carrierStats.put("singleEscortVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.size() == 1 && types.contains(SINGLE_ESCORT)).count());carrierStats.put("singleDriveDriverCount", (int) driverTypes.values().stream().filter(types -> types.size() == 1 && types.contains(SINGLE_DRIVE)).count());carrierStats.put("doubleDriveDriverCount", (int) driverTypes.values().stream().filter(types -> types.size() == 1 && types.contains(DOUBLE_DRIVE)).count());carrierStats.put("singleEscortDriverCount", (int) driverTypes.values().stream().filter(types -> types.size() == 1 && types.contains(SINGLE_ESCORT)).count());carrierStats.put("mixedSingleDoubleVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(SINGLE_DRIVE, DOUBLE_DRIVE))).count());carrierStats.put("mixedSingleDoubleDriverCount", (int) driverTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(SINGLE_DRIVE, DOUBLE_DRIVE))).count());carrierStats.put("mixedDriveEscortVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(SINGLE_DRIVE, SINGLE_ESCORT))).count());carrierStats.put("mixedDriveEscortDriverCount", (int) driverTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(SINGLE_DRIVE, SINGLE_ESCORT))).count());carrierStats.put("mixedDoubleEscortVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(DOUBLE_DRIVE, SINGLE_ESCORT))).count());carrierStats.put("mixedDoubleEscortDriverCount", (int) driverTypes.values().stream().filter(types -> types.containsAll(Arrays.asList(DOUBLE_DRIVE, SINGLE_ESCORT))).count());carrierStats.put("mixedAllVehicleCount", (int) vehicleTypes.values().stream().filter(types -> types.containsAll(ALL_TYPES)).count());carrierStats.put("mixedAllDriverCount", (int) driverTypes.values().stream().filter(types -> types.containsAll(ALL_TYPES)).count());return carrierStats;}));}
}

这个版本的代码使用 Stream API 来更简洁地统计各种类型的车辆和司机数量。这也使得代码更加清晰和易于阅读。然而，这并没有实质性的改变算法的时间复杂度和空间复杂度。