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JS解析XML--实现省市县级联

蚌埠市"> <district name

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java之XStream使用方法

; public Address(String add, String zipcode) { this.add = add; this.zipcode = zipcode; } public...String toString() { return "Address{" + "add='" + add + '\'' + ", zipcode='" + zipcode + '\''...>450001 西安市雁塔路 710002...>450001 西安市雁塔路 710002450001 西安市雁塔路 710002</zipcode

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MySQL 8.0 新特性:多值索引 --如何给JSON数组添加索引（三）

下表中的示例显示了在名为customers的表中的JSON列custinfo上的数组$.zipcode上创建多值索引zips的三种不同方法。...":[94582,94536]}'), -> (NULL, NOW(), '{"user":"Jill","user_id":22,"zipcode":[94568,94507,94582..., NOW(), '{"user":"Mary","user_id":72,"zipcode":[94536]}'), -> (NULL, NOW(), '{"user":"Ted","...user_id":56,"zipcode":[94507,94582]}'); Query OK, 5 rows affected (0.00 sec) Records: 5 Duplicates:...": [94582, 94536]} | | 2 | 2021-05-24 13:37:29 | {"user": "Jill", "user_id": 22, "zipcode": [

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泛型

Info{ // 表示联系方式 private String address ; // 联系地址 private String telphone ; // 联系方式 private String zipcode...; // 邮政编码 public Contact(String address,String telphone,String zipcode){ this.setAddress(address)...; this.setTelphone(telphone) ; this.setZipcode(zipcode) ; } public void setAddress(String address...){ this.zipcode = zipcode ; } public String getAddress(){ return this.address ; } public String...getTelphone(){ return this.telphone ; } public String getZipcode(){ return this.zipcode ; }

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如何在Java和Swift中避免空引用异常？

var zipCode = nil // won’t compile, because zipCode is not optional var zipCode : String = nil // same...zipCode : String?...zipCode?....zipCode if let zipCode = zipCode { print(zipCode) } } func findZipCodeFor(userId: String, inCountry country...address, let zipCode = address.zipCode, address.country == inCountry { return zipCode } return nil }

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MySQL 之 JSON 支持（二）—— JSON 索引

{ "user":"Bob", "user_id":31, "zipcode":[94477,94536] } 1....以下列表中的示例显示了在名为 customers 表的 custinfo JSON 列的 $.zipcode 数组上创建多值索引 zips 的三种不同方式。...":[94582,94536]}'), -> (NULL, NOW(), '{"user":"Jill","user_id":22,"zipcode":[94568,94507,94582..., NOW(), '{"user":"Mary","user_id":72,"zipcode":[94536]}'), -> (NULL, NOW(), '{"user":"Ted","...user_id":56,"zipcode":[94507,94582]}'); Query OK, 5 rows affected (0.07 sec) Records: 5 Duplicates:

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什么是索引下推？

索引下推直接用官方的例子说明：有一个索引 INDEX (zipcode, lastname, firstname) 有一个查询如下： SELECT * FROM people WHERE zipcode...lastname LIKE '%etrunia%' AND address LIKE '%Main Street%'; 本来是不能命中全部索引的，因为后面两个条件是左 % LIKE，当然最左匹配原则可以先利用 zipcode...MySQL can use the index to scan through people with zipcode='95054'....without Index Condition Pushdown, this query must retrieve full table rows for all people who have zipcode...This avoids reading full rows corresponding to index tuples that match the zipcode condition but not

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将特性与Mixin类混合

= zipcode def __str__(self): lines = [self.street] if self.street2:...lines.append(self.street2) lines.append(f'{self.city}, {self.state} {self.zipcode}')...", "street2": "", "city": "Concord", "state": "NH", "zipcode": "03301" } } { "id"...B-1", "city": "Concord", "state": "NH", "zipcode": "03301" } } { "id": "4", "name":...", "street2": "", "city": "Concord", "state": "NH", "zipcode": "03301" } }

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PySpark 读写 JSON 文件到 DataFrame

传送门： https://github.com/spark-examples/pyspark-examples/blob/master/resources/multiline-zipcode.json...[{ "RecordNumber": 2, "Zipcode": 704, "ZipCodeType": "STANDARD", "City": "PASEO COSTA DEL SUR...", "State": "PR" }, { "RecordNumber": 10, "Zipcode": 709, "ZipCodeType": "STANDARD", "City"....json', 'resources/zipcode2.json']) df2.show() 读取目录中的所有文件只需将目录作为json()方法的路径传递给该方法，我们就可以将目录中的所有...USING json OPTIONS" + " (path 'PyDataStudio/zipcodes.json')") spark.sql("select * from zipcode

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Bazel 构建 protobuf

option go_package = "github.com/jun06t/bazel-sample/protobuf/proto;user";package user;import "proto/zipcode.proto...";message Address { string city = 1; ZipCode zip_code = 2;}:::::::::::::: proto/user.proto :...= 2; Address address = 3; google.protobuf.Any tags = 4;}:::::::::::::: proto/zipcode.proto...proto3";option go_package = "github.com/jun06t/bazel-sample/protobuf/proto;user";package user;message ZipCode...proto/zipcode.proto 对比生成的3个 .pb.go 文件 ⚡ root@localhost  ~/bazel-sample/protobuf   main ±  diff

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android 省市区三级联动

"]"; } } 区的modeL public class DistrictInfoModel { private String name; private String zipcode...public DistrictInfoModel() { super(); } public DistrictInfoModel(String name, String zipcode...) { super(); this.name = name; this.zipcode = zipcode; } public String...; } public void setZipcode(String zipcode) { this.zipcode = zipcode; } @Override...public String toString() { return "DistrictInfoModel [name=" + name + ", zipcode=" + zipcode

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python与zmq系列（2）

context = zmq.Context() socket = context.socket(zmq.PUB) socket.bind("tcp://*:5556") while True: zipcode...temperature = randrange(-80, 135) relhumidity = randrange(10, 60) socket.send("%i %i %i" % (zipcode..."Collecting updates from weather server...") socket.connect("tcp://localhost:5556") # Subscribe to zipcode...updates total_temp = 0 for update_nbr in range(5): string = socket.recv() print string zipcode..."Collecting updates from weather server...") socket.connect("tcp://localhost:5556") # Subscribe to zipcode

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SQL 模糊查询（like）「建议收藏」

下面这句查询字符串是我以前写的，根据变量 zipcode_key 在邮政编码表 zipcode 中查询对应的数据，这句是判断变量 zipcode_key 为非数字时的查询语句，用 % 来匹配任意长度的字符串...sql = “select * from zipcode where (address like’%” & zipcode_key & “%’) or (city like’%” & zipcode_key...& “%’) or (province like’%” & zipcode_key & “%’)order by province,city,address” 详细介绍：一般模糊查询语句：...————————————————- 下面这句查询字符串是我以前写的，根据变量 zipcode_key 在邮政编码表 zipcode 中查询对应的数据，这句是判断变量zipcode_key 为非数字时的查询语句...sql = “select * from zipcode where (address like’%”& zipcode_key & “%’) or (city like’%” & zipcode_key

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C# 9.0中引入的新特性init和record的使用思考

private set; } public Address(string street, string city, string state, string country, string zipcode...= zipcode; } protected override IEnumerable GetEqualityComponents() { /...: {ZipCode}"; } } main方法如下： static void Main(string[] args) { Address address1 = new Address...: fff address2: Street: aaa, City: bbb, State: ccc, Country: ddd, ZipCode: fff address1 == address2:...: fff address2: Street: aaa, City: bbb, State: ccc, Country: ddd, ZipCode: fff address1 == address2:

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Spring Data（二）查询

你也可以通过嵌套属性定义约束，假设一个Person类有一个Address类，Address类有一个ZipCode类，方法的命名如下： List findByAddressZipCode(...ZipCode zipCode); 生成的属性嵌套为：x.address.zipCode。...如果第一次分割没有匹配成功，将分割点左移（Address和ZipCode）并继续。虽然这中逻辑可以为大多数情况下工作，但是它也有可能选择错误的属性。...所以我们的方法名字如下： List findByAddress_ZipCode(ZipCode zipCode); 我们将下划线作为保留字段，我们强烈建议使用java标准的命名规则。

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MongoDB中如何返回数组对象中第一个对象

区别在是根据查询中条件来，而elemMatch是需要显示指定一个条件, 【构造数据】 db.xiaoxu.find().pretty(); { "_id" : 1, "zipcode...db.xiaoxu.find({"students.age":{$gt:10}}).pretty(); { "_id" : 1, "zipcode" : "63109",...等于13000里面第一个学生信息--这个符合预期 db.xiaoxu.find({zipcode:"13000"},{"students":{$slice:1}}).pretty(); {..."_id" : 1, "zipcode" : "13000", "students" : [ {...【针对多数组查询条件--导致意外结果】 db.xiaoxu.find({"students.school":102}).pretty(); { "_id" : 1, "zipcode

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使用Python制作3个简易地图

dataframe to store this new data numStoresByZip = pd.DataFrame() #populate the new dataframe with a 'zipcode...' column and a 'numStores' column numStoresByZip['zipcode'] = [str(i) for i in numStoresSeries.index]...#This is how python knows which dataframe row matches up to which zipcode in the geojson laMap.choropleth...(geo_path='laZips.geojson', data=numStoresByZip, columns=['zipcode', 'numStores'], \...key_on='feature.properties.zipcode', fill_color='YlGn', fill_opacity=1) laMap.save('laChoropleth.html

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Postman(使用指南)

"Victor Plains", "suite": "Suite 879", "city": "Wisokyburgh", "zipcode...": "Skiles Walks", "suite": "Suite 351", "city": "Roscoeview", "zipcode..."Ellsworth Summit", "suite": "Suite 729", "city": "Aliyaview", "zipcode..."Dayna Park", "suite": "Suite 449", "city": "Bartholomebury", "zipcode...Kattie Turnpike", "suite": "Suite 198", "city": "Lebsackbury", "zipcode

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MySQL 8.0中的JSON增强

]}' ), ('{"id": "3", "name": "Jack"}' , '{"user":"Jack", "user_id":3, "zipcode":[34473,34533]}' )..., ('{"id": "4", "name": "Betty"}', '{"user":"Betty", "user_id":4, "zipcode":[44474,44534]}' ); Query...直接接口:MEMBER OF(),JSON_CONTAINS(),JSON_OVERLAPS() mysql> ALTER TABLE jemp ADD INDEX zips( (CAST(d->'$.zipcode...1 warning (0.00 sec) #JSON_CONTAINS mysql> EXPLAIN SELECT * FROM jemp WHERE JSON_CONTAINS(d->'$.zipcode...1 warning (0.00 sec) #JSON_OVERLAPS mysql> EXPLAIN SELECT * FROM jemp WHERE JSON_OVERLAPS(d->'$.zipcode

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几个常用的用正则表达式验证字符串的函数

--ZipCode check function--> function TestZipCode(src) {...var ZipCode,regex; ZipCode="^[\\d]{6}$" regex=new RegExp(ZipCode); return regex.test(src); } <

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