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build/index.min.js"},"repository":{"type":"git","url":"git+https://github.com/svonme/DBList.git"},"keywords":["db","list"],"author":{"name":"svon.me@gmail.com"},"license":"MIT","bugs":{"url":"https://github.com/svonme/DBList/issues"},"homepage":"https://github.com/svonme/DBList#readme","dependencies":{"lodash":"^4.17.15"},"devDependencies":{"@types/lodash":"^4.14.155","@types/node":"^14.0.13","uglify-js":"^3.9.4"},"readme":"# DBList\n\n对一组有规则的列表数据进行增删改查\n\n`$ npm install @fengqiaogang/dblist`\n\n```\nconst list = [{\n name: '张三',\n age: 20,\n sex: '男',\n hobby: ['上网', '玩游戏']\n}, {\n name: '张六',\n age: 20,\n sex: '男',\n hobby: ['上网', '玩游戏']\n}, {\n name: '李四',\n age: 20,\n sex: '男',\n hobby: ['上网', '唱歌']\n}, {\n name: '王五',\n age: 20,\n sex: '男',\n hobby: ['上网', '玩游戏']\n}, {\n name: '静静',\n age: 18,\n sex: '女',\n hobby: ['游泳', '唱歌']\n}, {\n name: '夏琪',\n age: 19,\n sex: '女',\n hobby: ['游泳', '跳舞']\n}, {\n name: '游勇',\n age: 22,\n sex: '男',\n hobby: ['下棋', '玩游戏']\n}]\n```\n\n\n\n这样的有规则数据大家都很熟悉，假如我们要想知道数据中包含 age = 19 或者 age = 20 的数据有那些\n\n生成一个 dblist 对象\n```\nconst db = new DBList('db name', list)\n或者\nconst db = new DBList('db name')\ndb.insert(list)\n```\n\n## select 查询\n\n匹配 age = 19 的所有数据\n```\ndb.select({ age: 19 })\n\n[\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '夏琪', age: 19, sex: '女', hobby: [ '游泳', '跳舞' ] }\n]\n```\n\n匹配 id = 2 或者 age = 20 的所有数据\n```\ndb.select({ age: [19, 20] });\n\n[\n { name: '张三', age: 20, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '李四', age: 20, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '夏琪', age: 19, sex: '女', hobby: [ '游泳', '跳舞' ] }\n]\n```\n\n匹配 age = 19 并且 hobby = 玩游戏 的所有数据\n```\ndb.select({ age: 19, hobby: '玩游戏' });\n\n[\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] }\n]\n```\n\n---\n\n## insert 添加\n\n添加单条数据\n\n```\nconst value = { id: 5, value: '重庆' }\n\ndb.insert(value)\n```\n\n添加多条数据\n\n```\nconst values = [{ id: 6, value: '上海' }, { id: 7, value: '天津' }]\n\ndb.insert(values)\n```\n\n\n## update 修改\n\n把所有 name = 静静 的数据中的 age 修改为 19\n\n```\nconst where = { name: '静静' } // 匹配条件\nconst newData = { age: 19 } // 修改的数据\n\ndb.update(where, newData)\n```\n\n## remove 删除\n\n删除 age = 21 的数据\n\n```\nconst where = { age: 21 } // 匹配条件，匹配那些数据需要删除\ndb.remove(where)\n```\n\n删除 name = 夏琪 或者 name = 游勇 的数据\n\n```\nconst where = { name: ['夏琪', '游勇'] }\ndb.remove(where)\n```\n\n## flatten 处理递归数据\n\n```\nconst list = [\n {\n id: 1,\n value: '北京',\n children: [\n {\n id: 2,\n value: '朝阳区',\n children: [\n {\n id: 4,\n value: '三里屯'\n }\n ]\n },\n {\n id: 3,\n value: '东城区'\n }\n ]\n },\n ...\n]\n```\n\n解构上面的递归结构数据\n\n```\nconst db = new DBList('db flatten', [], 'id', 'pid')\nconst data = db.flatten(list, 'children') // children 为数据结构中的递归字段\n\n[\n { id: 1, value: '北京', pid: 0 },\n { id: 2, value: '朝阳区', pid: 1 },\n { id: 4, value: '三里屯', pid: 2 },\n { id: 3, value: '东城区', pid: 1 }\n]\n\npid 为自动生成的外键关系数据，详情参考下面的介绍\n\n```\n\n## 构造参数\n\n```\nnew DBList(name, list, primaryKey, foreignKey)\n```\n\n| 字段 | 是否可以为空 | 说明 | 默认值 |\n| ------------ | ------------ | ------------ | ------------ |\n| name | 否 | 对象名称 | - |\n| list | 否 | 实列化时默认执行一次 insert 方法 | [] |\n| primaryKey | 否 | 主键 , 用于标识别当前数据 | \"id\" |\n| foreignKey | 否 | 外键, 用于与哪条数据进行关联 | \"pid\" \"\n| fristForeignValue | 否 | 第一层外键的值 | \"0\" |\n\n\n\n## children 查询子级数据\n\n查询 id = 1 的子级数据 (查询所有与 id = 1 有关联的数据)\n\n```\nconst where = { id: 1 }\ndb.children(where)\n\n[\n { id: 1, value: '北京' },\n { id: 2, value: '朝阳区' },\n { id: 3, value: '东城区' }\n]\n```\n\n## parent 查询父级数据\n\n查询 id = 2 的父级数据 (查询所有与 id = 2 有关联的数据)\n\n```\nconst where = { id: 2 }\ndb.parent(where)\n\n[\n { id: 2, value: '朝阳区' },\n { id: 1, value: '北京' }\n]\n```\n\n## childrenDeep 递归查询子级数据\n\n该方法与 children 类似, children 只会查询一层子级数据，childrenDeep 则会进行递归查询\n\n```\nconst where = { id: 1 }\ndb.children(where)\n\n[\n { id: 1, value: '北京' },\n { id: 2, value: '朝阳区' },\n { id: 3, value: '东城区' },\n { id: 4, value: '三里屯' }\n]\n```\n\n## parentDeep 递归查询父级数据\n\n该方法与 parent 类似, parent 只会查询一层父级数据，parentDeep 则会进行递归查询\n\n```\nconst where = { id: 4 }\ndb.parent(where)\n\n[\n { id: 4, value: '三里屯' }\n { id: 2, value: '朝阳区' },\n { id: 1, value: '北京' }\n]\n```\n\n## clone 复制\n\n执行 clone 时会返回一个正常的 Array 数据\n\n```\nconst list = db.clone()\n```\n\n执行 clone 时处理每一条数据\n\n```\nconst list = db.clone(item => {\n\t// todo\n\treturn item;\n});\n```\n\n## like 模糊查询\n\n查询 value 中带 `北` 的数据\n\n```\nconst where = { value: '北' }\ndb.link(where)\n\n[\n { id: 1, value: '北京' }\n]\n```\n\n## selectOne 查询\n\nselectOne 与 select 使用上一样的，selectOne 在匹配到一条数据后则会停止匹配。该方法返回的为数据本身，非数组\n\n查询 id = 5 的数据\n```\nconst where = { id: 5 }\n\ndb.selectOne(where) \n{ id: 5, value: '重庆' }\n```\n如果我们已知需要查询的数据只会存在一条时可以设置查询条数, 尽可能减少匹配次数\n```\nconst where = { id: 5 }\n\ndb.select(where, 1)\n[\n { id: 5, value: '重庆' 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'玩游戏']\n}]\n```\n\n\n\n这样的有规则数据大家都很熟悉，假如我们要想知道数据中包含 age = 19 或者 age = 20 的数据有那些\n\n生成一个 dblist 对象\n```\nconst db = new DBList('db name', list)\n或者\nconst db = new DBList('db name')\ndb.insert(list)\n```\n\n## select 查询\n\n匹配 age = 19 的所有数据\n```\ndb.select({ age: 19 })\n\n[\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '夏琪', age: 19, sex: '女', hobby: [ '游泳', '跳舞' ] }\n]\n```\n\n匹配 id = 2 或者 age = 20 的所有数据\n```\ndb.select({ age: [19, 20] });\n\n[\n { name: '张三', age: 20, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '李四', age: 20, sex: '男', hobby: [ '上网', '玩游戏' ] },\n { name: '夏琪', age: 19, sex: '女', hobby: [ '游泳', '跳舞' ] }\n]\n```\n\n匹配 age = 19 并且 hobby = 玩游戏 的所有数据\n```\ndb.select({ age: 19, hobby: '玩游戏' });\n\n[\n { name: '张六', age: 19, sex: '男', hobby: [ '上网', '玩游戏' ] }\n]\n```\n\n---\n\n## insert 添加\n\n添加单条数据\n\n```\nconst value = { id: 5, value: '重庆' }\n\ndb.insert(value)\n```\n\n添加多条数据\n\n```\nconst values = [{ id: 6, value: '上海' }, { id: 7, value: '天津' }]\n\ndb.insert(values)\n```\n\n\n## update 修改\n\n把所有 name = 静静 的数据中的 age 修改为 19\n\n```\nconst where = { name: '静静' } // 匹配条件\nconst newData = { age: 19 } // 修改的数据\n\ndb.update(where, newData)\n```\n\n## remove 删除\n\n删除 age = 21 的数据\n\n```\nconst where = { age: 21 } // 匹配条件，匹配那些数据需要删除\ndb.remove(where)\n```\n\n删除 name = 夏琪 或者 name = 游勇 的数据\n\n```\nconst where = { name: ['夏琪', '游勇'] }\ndb.remove(where)\n```\n\n## flatten 处理递归数据\n\n```\nconst list = [\n {\n id: 1,\n value: '北京',\n children: [\n {\n id: 2,\n value: '朝阳区',\n children: [\n {\n id: 4,\n value: '三里屯'\n }\n ]\n },\n {\n id: 3,\n value: '东城区'\n }\n ]\n },\n ...\n]\n```\n\n解构上面的递归结构数据\n\n```\nconst db = new DBList('db flatten', [], 'id', 'pid')\nconst data = db.flatten(list, 'children') // children 为数据结构中的递归字段\n\n[\n { id: 1, value: '北京', pid: 0 },\n { id: 2, value: '朝阳区', pid: 1 },\n { id: 4, value: '三里屯', pid: 2 },\n { id: 3, value: '东城区', pid: 1 }\n]\n\npid 为自动生成的外键关系数据，详情参考下面的介绍\n\n```\n\n## 构造参数\n\n```\nnew DBList(name, list, primaryKey, foreignKey)\n```\n\n| 字段 | 是否可以为空 | 说明 | 默认值 |\n| ------------ | ------------ | ------------ | ------------ |\n| name | 否 | 对象名称 | - |\n| list | 否 | 实列化时默认执行一次 insert 方法 | [] |\n| primaryKey | 否 | 主键 , 用于标识别当前数据 | \"id\" |\n| foreignKey | 否 | 外键, 用于与哪条数据进行关联 | \"pid\" \"\n| fristForeignValue | 否 | 第一层外键的值 | \"0\" |\n\n\n\n## children 查询子级数据\n\n查询 id = 1 的子级数据 (查询所有与 id = 1 有关联的数据)\n\n```\nconst where = { id: 1 }\ndb.children(where)\n\n[\n { id: 1, value: '北京' },\n { id: 2, value: '朝阳区' },\n { id: 3, value: '东城区' }\n]\n```\n\n## parent 查询父级数据\n\n查询 id = 2 的父级数据 (查询所有与 id = 2 有关联的数据)\n\n```\nconst where = { id: 2 }\ndb.parent(where)\n\n[\n { id: 2, value: '朝阳区' },\n { id: 1, value: '北京' }\n]\n```\n\n## childrenDeep 递归查询子级数据\n\n该方法与 children 类似, children 只会查询一层子级数据，childrenDeep 则会进行递归查询\n\n```\nconst where = { id: 1 }\ndb.children(where)\n\n[\n { id: 1, value: '北京' },\n { id: 2, value: '朝阳区' },\n { id: 3, value: '东城区' },\n { id: 4, value: '三里屯' }\n]\n```\n\n## parentDeep 递归查询父级数据\n\n该方法与 parent 类似, parent 只会查询一层父级数据，parentDeep 则会进行递归查询\n\n```\nconst where = { id: 4 }\ndb.parent(where)\n\n[\n { id: 4, value: '三里屯' }\n { id: 2, value: '朝阳区' },\n { id: 1, value: '北京' }\n]\n```\n\n## clone 复制\n\n执行 clone 时会返回一个正常的 Array 数据\n\n```\nconst list = db.clone()\n```\n\n执行 clone 时处理每一条数据\n\n```\nconst list = db.clone(item => {\n\t// todo\n\treturn item;\n});\n```\n\n## like 模糊查询\n\n查询 value 中带 `北` 的数据\n\n```\nconst where = { value: '北' }\ndb.link(where)\n\n[\n { id: 1, value: '北京' }\n]\n```\n\n## selectOne 查询\n\nselectOne 与 select 使用上一样的，selectOne 在匹配到一条数据后则会停止匹配。该方法返回的为数据本身，非数组\n\n查询 id = 5 的数据\n```\nconst where = { id: 5 }\n\ndb.selectOne(where) \n{ id: 5, value: '重庆' }\n```\n如果我们已知需要查询的数据只会存在一条时可以设置查询条数, 尽可能减少匹配次数\n```\nconst where = { id: 5 }\n\ndb.select(where, 1)\n[\n { id: 5, value: '重庆' 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new DBList()\ndb.insert(list)\n```\n\n## select 查询\n\n匹配 age = 19 的所有数据\n```\ndb.select({ age: 19 })\n\n[\n { name: '夏琪', age: 19, sex: '女', hobby: [ '游泳', '跳舞' ] }\n]\n```\n\n匹配 age = 19 或者 age = 20 的所有数据\n```\ndb.select({ age: [19, 20] });\n\n[\n { name: '张三', age: 20, sex: '男',hobby: ['上网', '玩游戏'] }, \n { name: '张六', age: 20, sex: '男', hobby: ['上网', '玩游戏'] }, \n { name: '李四', age: 20, sex: '男', hobby: ['上网', '唱歌'] }, \n { name: '王五', age: 20, sex: '男', hobby: ['上网', '玩游戏'] },\n { name: '夏琪', age: 19, sex: '女', hobby: ['游泳', '跳舞'] }\n]\n```\n\n匹配 age = 18 并且 sex = 女 的所有数据\n```\ndb.select({ age: 18, sex: '女' });\n\n[\n { name: '静静', age: 18, sex: '女', hobby: ['游泳', '唱歌'] }\n]\n```\n\n---\n\n## insert 添加\n\n添加数据\n\n```\nconst value = { id: 5, value: '重庆' }\n\nconst key: number[] = db.insert(value) // 返回该条元素的唯一键值\n```\n\n## update 修改\n\n把所有 name = 静静 的数据中的 age 修改为 19\n\n```\nconst where = { name: '静静' } // 匹配条件\nconst newData = { age: 19 } // 修改的数据\n\nconst count: number = db.update(where, newData); // 返回受影响的行数\n```\n\n## remove 删除\n\n删除 age = 22 的数据\n\n```\nconst where = { age: 22 } // 匹配条件，匹配那些数据需要删除\nconst count: number = db.remove(where); // 返回受影响的行数\n```\n\n删除 name = 夏琪 或者 name = 游勇 的数据\n\n```\nconst where = { name: ['夏琪', '游勇'] }\nconst count: number = db.remove(where); \n```\n\n\n## like 模糊查询\n\n查询 name 中带 `张` 的数据\n\n```\ndb.like({ name: '张' })\n\n[\n { name: '张三', age: 20, sex: '男',hobby: ['上网', '玩游戏'] }, \n { name: '张六', age: 20, sex: '男', hobby: ['上网', '玩游戏'] }\n]\n```\n\n## selectOne 查询\n\nselectOne 与 select 使用上一样的，selectOne 在匹配到一条数据后则会停止匹配\n\n查询 age = 20 的第一条数据\n```\n\ndb.selectOne({ age: 20 });\n{ name: '张三', age: 20, sex: '男',hobby: ['上网', '玩游戏'] }\n\n\n```\n如果我们已知需要查询的数据只会存在一条时可以设置查询条数, 尽可能减少匹配次数\n```\nconst where = { id: 5 }\n\ndb.select({ age: 20 }, 1)\n[\n { name: '张三', age: 20, sex: '男',hobby: ['上网', '玩游戏'] }\n]\n```\n\n\n## siblings\n\n根据条件的匹配结果查询其兄弟元素\n\n```\n\ndb.siblings({ name: '张三' }) \n\n[\n ...\n]\n\n```\n\n## flatten 处理递归数据\n\n```\nconst list = [\n {\n id: 1,\n value: '北京',\n children: [\n {\n id: 2,\n value: '朝阳区',\n children: [\n {\n id: 4,\n value: '三里屯'\n }\n ]\n },\n {\n id: 3,\n value: '东城区'\n }\n ]\n },\n ...\n]\n```\n\n解构上面的递归结构数据\n\n```\nconst data = DBList.flatten(list, 'children') // children 为数据结构中的递归字段\n\n[\n { id: 1, value: '北京', pid: 0 },\n { id: 2, value: '朝阳区', pid: 1 },\n { id: 4, value: '三里屯', pid: 2 },\n { id: 3, value: '东城区', pid: 1 }\n]\nid 为该条数据种的唯一值\npid 为自动生成的外键关系数据\n\n```\n\n## 构造参数\n\n\n| 字段 | 是否可以为空 | 说明 | 默认值 |\n| ------------ | ------------ | ------------ | ------------ |\n| list | 否 | 实列化时默认执行一次 insert 方法 | [] |\n| primary | 否 | 主键 , 用于标识别当前数据 | \"id\" |\n| foreign | 否 | 外键, 用于与哪条数据进行关联 | \"pid\" \"\n| foreignValue | 否 | 第一层外键的值 | \"-1\" |\n\n\n```\nnew DBList(list, primary, foreign, foreignValue)\n\nconst db = new DBList(list, \"id\", \"pid\", \"0\");\n\ndb.primary => \"id\"\ndb.foreign => \"pid\"\ndb.foreignValue => \"0\"\n```\n\n\n### 测试数据\n\n```\n[\n { \"id\": \"100\", \"name\": \"A\", \"pid\": 0 },\n { \"id\": \"101\", \"name\": \"B\", \"pid\": \"100\" },\n { \"id\": \"102\", \"name\": \"C\", \"pid\": \"101\" },\n { \"id\": \"103\", \"name\": \"D\", \"pid\": \"102\" },\n { \"id\": \"104\", \"name\": \"E\", \"pid\": \"103\" }\n]\n```\n\n## children 查询子级数据\n\n查询 id = 100 的子级数据\n\n```\ndb.children({ id: '100' });\n[\n { \"id\": \"101\", \"name\": \"B\", \"pid\": \"100\" }\n]\n```\n\n## parent 查询父级数据\n\n查询 id = 104 的父级数据 (父级返回的是对象，非数组)\n\n```\ndb.parent({ id: '104' });\n{ \"id\": \"103\", \"name\": \"D\", \"pid\": \"102\" }\n```\n\n## childrenDeep 递归查询子级数据\n\n该方法与 children 类似, children 只会查询一层子级数据，childrenDeep 则会进行递归查询\n\n```\ndb.childrenDeep({ id: '100' })\n// db.childrenDeep(where, 'children') \n// 第二个参数用于指定 children 列表的键值，默认 children\n\n[\n {\n \"id\": \"100\",\n \"name\": \"A\",\n \"pid\": 0,\n \"children\": [\n {\n \"id\": \"101\",\n \"name\": \"B\",\n \"pid\": \"100\",\n \"children\": [\n {\n \"id\": \"102\",\n \"name\": \"C\",\n \"pid\": \"101\",\n \"children\": [\n {\n \"id\": \"103\",\n \"name\": \"D\",\n \"pid\": \"102\",\n \"children\": [\n {\n \"id\": \"104\",\n \"name\": \"E\",\n \"pid\": \"103\"\n }\n ]\n }\n ]\n }\n ]\n }\n ]\n }\n]\n```\n\n## parentDeep 递归查询父级数据\n\n该方法与 parent 类似, parent 只会查询一层父级数据，parentDeep 则会进行递归查询\n\n```\ndb.parentDeep({ id: '104' })\n\n// db.parentDeep(where, 'parent') \n// 第二个参数用于指定 parent 列表的键值，默认 parent\n\n[\n {\n \"id\": \"104\",\n \"name\": \"E\",\n \"pid\": \"103\",\n \"parent\": [\n {\n \"id\": \"103\",\n \"name\": \"D\",\n \"pid\": \"102\",\n \"parent\": [\n {\n \"id\": \"102\",\n \"name\": \"C\",\n \"pid\": \"101\",\n \"parent\": [\n {\n \"id\": \"101\",\n \"name\": \"B\",\n \"pid\": \"100\",\n \"parent\": [\n {\n \"id\": \"100\",\n \"name\": \"A\",\n \"pid\": 0\n }\n ]\n }\n ]\n }\n ]\n }\n ]\n }\n]\n```\n\n## clone 复制\n\n执行 clone 时会将所有数据以 Array 格式返回\n\n```\nconst list = db.clone()\n```\n\n执行 clone 时处理每一条数据\n\n```\nconst list = db.clone(item => {\n\t// todo\n\treturn item;\n});\n```\n\n## childrenDeepFlatten\n childrenDeep + flatten\n 把 childrenDeep 的数据做降维处理 \n\n## parentDeepFlatten\n parentDeep + flatten\n 把 parentDeep 的结果做降维处理\n\n## clear\n 清空所有数据\n\n## empty\n 清空元素几节点上的数据，只保留 primary & foreign 属性\n","readmeFilename":"README.md"}