huhao0 2019-07-01
在《Graphql实战系列(上)》中我们已经完成技术选型,并将graphql桥接到凝胶gels项目中,并动手写了schema,并可以通过 http://localhost:5000/graphql 查看效果。这一节,我们根据数据库表来自动生成基本的查询与更新schema,并能方便的扩展schema,实现我们想要的业务逻辑。
用navicat在数据库中设计的表
自动生成的graphql测试
对象定义在apollo-server中是用字符串来做的,而Query与Mutation只能有一个,而我们的定义又会分散在多个文件中,因此只能先以一定的形式把它们存入数组中,在生成schema前一刻再组合。
const customDefs = { textDefs: ` type ReviseResult { id: Int affectedRows: Int status: Int message: String }, queryDefs: [], mutationDefs: [] } const customResolvers = { Query: { }, Mutation: { } } export { customDefs, customResolvers }
let typeDefs = [] let dirGraphql = requireDir('../../graphql') //从手写schema业务模块目录读入文件 G.L.each(dirGraphql, (item, name) => { if (item && item.customDefs && item.customResolvers) { typeDefs.push(item.customDefs.textDefs || '') //合并文本对象定义 typeDefObj.query = typeDefObj.query.concat(item.customDefs.queryDefs || []) //合并Query typeDefObj.mutation = typeDefObj.mutation.concat(item.customDefs.mutationDefs || []) //合并Matation let { Query, Mutation, ...Other } = item.customResolvers Object.assign(resolvers.Query, Query) //合并resolvers.Query Object.assign(resolvers.Mutation, Mutation) //合并resolvers.Mutation Object.assign(resolvers, Other) //合并其它resolvers } }) //将query与matation查询更新对象由自定义的数组转化成为文本形式 typeDefs.push(Object.entries(typeDefObj).reduce((total, cur) => { return total += ` type ${G.tools.bigCamelCase(cur[0])} { ${cur[1].join('')} } ` }, ''))
自动生成内容:
定义一类型转换,不在定义中的默认为String。
const TYPEFROMMYSQLTOGRAPHQL = { int: 'Int', smallint: 'Int', tinyint: 'Int', bigint: 'Int', double: 'Float', float: 'Float', decimal: 'Float', }
let dao = new BaseDao() let tables = await dao.querySql('select TABLE_NAME,TABLE_COMMENT from information_schema.`TABLES` ' + ' where TABLE_SCHEMA = ? and TABLE_TYPE = ? and substr(TABLE_NAME,1,2) <> ? order by ?', [G.CONFIGS.dbconfig.db_name, 'BASE TABLE', 't_', 'TABLE_NAME'])
tables.data.forEach((table) => { columnRs.push(dao.querySql('SELECT `COLUMNS`.COLUMN_NAME,`COLUMNS`.COLUMN_TYPE,`COLUMNS`.IS_NULLABLE,' + '`COLUMNS`.CHARACTER_SET_NAME,`COLUMNS`.COLUMN_DEFAULT,`COLUMNS`.EXTRA,' + '`COLUMNS`.COLUMN_KEY,`COLUMNS`.COLUMN_COMMENT,`STATISTICS`.TABLE_NAME,' + '`STATISTICS`.INDEX_NAME,`STATISTICS`.SEQ_IN_INDEX,`STATISTICS`.NON_UNIQUE,' + '`COLUMNS`.COLLATION_NAME ' + 'FROM information_schema.`COLUMNS` ' + 'LEFT JOIN information_schema.`STATISTICS` ON ' + 'information_schema.`COLUMNS`.TABLE_NAME = `STATISTICS`.TABLE_NAME ' + 'AND information_schema.`COLUMNS`.COLUMN_NAME = information_schema.`STATISTICS`.COLUMN_NAME ' + 'AND information_schema.`STATISTICS`.table_schema = ? ' + 'where information_schema.`COLUMNS`.TABLE_NAME = ? and `COLUMNS`.table_schema = ?', [G.CONFIGS.dbconfig.db_name, table.TABLE_NAME, G.CONFIGS.dbconfig.db_name])) })
取数据库表字段类型,去除圆括号与长度信息
getStartTillBracket(str: string) { return str.indexOf('(') > -1 ? str.substr(0, str.indexOf('(')) : str }
下划线分隔的表字段转化为big camel-case
bigCamelCase(str: string) { return str.split('_').map((al) => { if (al.length > 0) { return al.substr(0, 1).toUpperCase() + al.substr(1).toLowerCase() } return al }).join('') }
下划线分隔的表字段转化为small camel-case
smallCamelCase(str: string) { let strs = str.split('_') if (strs.length < 2) { return str } else { let tail = strs.slice(1).map((al) => { if (al.length > 0) { return al.substr(0, 1).toUpperCase() + al.substr(1).toLowerCase() } return al }).join('') return strs[0] + tail } }
不以_id结尾,是正常字段,判断是否为null,处理必填
typeDefObj[table].unshift(`${col['COLUMN_NAME']}: ${typeStr}${col['IS_NULLABLE'] === 'NO' ? '!' : ''}\n`)
以_id结尾,则需要处理关联关系
//Book表以author_id关联单个Author实体 typeDefObj[table].unshift(`"""关联的实体""" ${G.L.trimEnd(col['COLUMN_NAME'], '_id')}: ${G.tools.bigCamelCase(G.L.trimEnd(col['COLUMN_NAME'], '_id'))}`) resolvers[G.tools.bigCamelCase(table)] = { [G.L.trimEnd(col['COLUMN_NAME'], '_id')]: async (element) => { let rs = await new BaseDao(G.L.trimEnd(col['COLUMN_NAME'], '_id')).retrieve({ id: element[col['COLUMN_NAME']] }) return rs.data[0] } } //Author表关联Book列表 let fTable = G.L.trimEnd(col['COLUMN_NAME'], '_id') if (!typeDefObj[fTable]) { typeDefObj[fTable] = [] } if (typeDefObj[fTable].length >= 2) typeDefObj[fTable].splice(typeDefObj[fTable].length - 2, 0, `"""关联实体集合"""${table}s: [${G.tools.bigCamelCase(table)}]\n`) else typeDefObj[fTable].push(`${table}s: [${G.tools.bigCamelCase(table)}]\n`) resolvers[G.tools.bigCamelCase(fTable)] = { [`${table}s`]: async (element) => { let rs = await new BaseDao(table).retrieve({ [col['COLUMN_NAME']]: element.id}) return rs.data } }
单条查询
if (paramId.length > 0) { typeDefObj['query'].push(`${G.tools.smallCamelCase(table)}(${paramId}!): ${G.tools.bigCamelCase(table)}\n`) resolvers.Query[`${G.tools.smallCamelCase(table)}`] = async (_, { id }) => { let rs = await new BaseDao(table).retrieve({ id }) return rs.data[0] } } else { G.logger.error(`Table [${table}] must have id field.`) }
列表查询
let complex = table.endsWith('s') ? (table.substr(0, table.length - 1) + 'z') : (table + 's') typeDefObj['query'].push(`${G.tools.smallCamelCase(complex)}(${paramStr.join(', ')}): [${G.tools.bigCamelCase(table)}]\n`) resolvers.Query[`${G.tools.smallCamelCase(complex)}`] = async (_, args) => { let rs = await new BaseDao(table).retrieve(args) return rs.data }
typeDefObj['mutation'].push(` create${G.tools.bigCamelCase(table)}(${paramForMutation.slice(1).join(', ')}):ReviseResult update${G.tools.bigCamelCase(table)}(${paramForMutation.join(', ')}):ReviseResult delete${G.tools.bigCamelCase(table)}(${paramId}!):ReviseResult `) resolvers.Mutation[`create${G.tools.bigCamelCase(table)}`] = async (_, args) => { let rs = await new BaseDao(table).create(args) return rs } resolvers.Mutation[`update${G.tools.bigCamelCase(table)}`] = async (_, args) => { let rs = await new BaseDao(table).update(args) return rs } resolvers.Mutation[`delete${G.tools.bigCamelCase(table)}`] = async (_, { id }) => { let rs = await new BaseDao(table).delete({ id }) return rs }
https://github.com/zhoutk/gels
git clone https://github.com/zhoutk/gels cd gels yarn tsc -w nodemon dist/index.js
然后就可以用浏览器打开链接:http://localhost:5000/graphql 查看效果了。
我只能把大概思路写出来,让大家有个整体的概念,若想很好的理解,得自己把项目跑起来,根据我提供的思想,慢慢的去理解。因为我在编写的过程中还是遇到了不少的难点,这块既要自动化,还要能方便的接受手动编写的schema模块,的确有点难度。