Question

处理数据批量生成sql插入语句

处理数据批量生成sql插入语句最近在做一个天气预报模块，首先需要将客户端公网ip转换成所在城市，然后将所在城市名转换成对应的城市代码，

Answer 1

处理数据批量生成sql插入语句
最近在做一个天气预报模块，首先需要将客户端公网ip转换成所在城市，然后将所在城市名转换成对应的城市代码，在网上找到了城市代码，但是需要处理一下，看了看，有三百多城市及对应的城市代码，想存到数据库。就想着做一个数据处理自动生成sql语句的工具，提高效率。
1 直辖市
2 "北京","上海","天津","重庆"
3 "101010100","101020100","101030100","101040100"
4
5 特别行政区
6 "香港","澳门"
7 "101320101","101330101"
8
9 黑龙江
10 "哈尔滨","齐齐哈尔","牡丹江","大庆","伊春","双鸭山","鹤岗","鸡西","佳木斯","七台河","黑河","绥化","大兴安岭"
11 "101050101","101050201","101050301","101050901","101050801","101051301","101051201","101051101","101050401","101051002","101050601","101050501","101050701"
12
13 吉林
14 "长春","延吉","吉林","白山","白城","四平","松原","辽源","大安","通化"
15 "101060101","101060301","101060201","101060901","101060601","101060401","101060801","101060701","101060603","101060501"
16
17 辽宁
18 "沈阳","大连","葫芦岛","盘锦","本溪","抚顺","铁岭","辽阳","营口","阜新","朝阳","锦州","丹东","鞍山"
19 "101070101","101070201","101071401","101071301","101070501","101070401","101071101","101071001","101070801","101070901","101071201","101070701","101070601","101070301"
20
21 内蒙古
22 "呼和浩特","呼伦贝尔","锡林浩特","包头","赤峰","海拉尔","乌海","鄂尔多斯","通辽"
23 "101080101","101081000","101080901","101080201","101080601","101081001","101080301","101080701","101080501"
24
25 河北
26 "石家庄","唐山","张家口","廊坊","邢台","邯郸","沧州","衡水","承德","保定","秦皇岛"
27 "101090101","101090501","101090301","101090601","101090901","101091001","101090701","101090801","101090402","101090201","101091101"
28
29 河南
30 "郑州","开封","洛阳","平顶山","焦作","鹤壁","新乡","安阳","濮阳","许昌","漯河","三门峡","南阳","商丘","信阳","周口","驻马店"
31 "101180101","101180801","101180901","101180501","101181101","101181201","101180301","101180201","101181301","101180401","101181501","101181701","101180701","101181001","101180601","101181401","101181601"
32
33 山东
34 "济南","青岛","淄博","威海","曲阜","临沂","烟台","枣庄","聊城","济宁","菏泽","泰安","日照","东营","德州","滨州","莱芜","潍坊"
35 "101120101","101120201","101120301","101121301","101120710","101120901","101120501","101121401","101121701","101120701","101121001","101120801","101121501","101121201","101120401","101121101","101121601","101120601"
36
37 山西
38 "太原","阳泉","晋城","晋中","临汾","运城","长治","朔州","忻州","大同","吕梁"
39 "101100101","101100301","101100601","101100401","101100701","101100801","101100501","101100901","101101001","101100201","101101101"
40
41 江苏
42 "南京","苏州","昆山","南通","太仓","吴县","徐州","宜兴","镇江","淮安","常熟","盐城","泰州","无锡","连云港","扬州","常州","宿迁"
43 "101190101","101190401","101190404","101190501","101190408","101190406","101190801","101190203","101190301","101190901","101190402","101190701","101191201","101190201","101191001","101190601","101191101","101191301"
44
45 安徽
46 "合肥","巢湖","蚌埠","安庆","六安","滁州","马鞍山","阜阳","宣城","铜陵","淮北","芜湖","毫州","宿州","淮南","池州"
47 "101220101","101221601","101220201","101220601","101221501","101221101","101220501","101220801","101221401","101221301","101221201","101220301","101220901","101220701","101220401","101221701"
48
49 陕西
50 "西安","韩城","安康","汉中","宝鸡","咸阳","榆林","渭南","商洛","铜川","延安"
51 "101110101","101110510","101110701","101110801","101110901","101110200","101110401","101110501","101110601","101111001","101110300"
52
53 宁夏
54 "银川","固原","中卫","石嘴山","吴忠"
55 "101170101","101170401","101170501","101170201","101170301"
56
57 甘肃
58 "兰州","白银","庆阳","酒泉","天水","武威","张掖","甘南","临夏","平凉","定西","金昌"
59 "101160101","101161301","101160401","101160801","101160901","101160501","101160701","101050204","101161101","101160301","101160201","101160601"
60
61 青海
62 "西宁","海北","海西","黄南","果洛","玉树","海东","海南"
63 "101150101","101150801","101150701","101150301","101150501","101150601","101150201","101150401"
64
65 湖北
66 "武汉","宜昌","黄冈","恩施","荆州","神农架","十堰","咸宁","襄阳","孝感","随州","黄石","荆门","鄂州"
67 "101200101","101200901","101200501","101201001","101200801","101201201","101201101","101200701","101200201","101200401","101201301","101200601","101201401","101200301"
68
69 湖南
70 "长沙","邵阳","常德","郴州","吉首","株洲","娄底","湘潭","益阳","永州","岳阳","衡阳","怀化","韶山","张家界"
71 "101250101","101250901","101250601","101250501","101251501","101250301","101250801","101250201","101250701","101251401","101251001","101250401","101251201","101250202","101251101"
72
73 浙江
74 "杭州","湖州","金华","宁波","丽水","绍兴","衢州","嘉兴","台州","舟山","温州"
75 "101210101","101210201","101210901","101210401","101210801","101210501","101211001","101210301","101210601","101211101","101210701"
76
77 江西
78 "南昌","萍乡","九江","上饶","抚州","吉安","鹰潭","宜春","新余","景德镇","赣州"
79 "101240101","101240901","101240201","101240301","101240401","101240601","101241101","101240501","101241001","101240801","101240701"
80
81 福建
82 "福州","厦门","龙岩","南平","宁德","莆田","泉州","三明","漳州"
83 "101230101","101230201","101230701","101230901","101230301","101230401","101230501","101230801","101230601"
84
85 贵州
86 "贵阳","安顺","赤水","遵义","铜仁","六盘水","毕节","凯里","都匀"
87 "101260101","101260301","101260208","101260201","101260601","101260801","101260701","101260501","101260401"
88
89 四川
90 "成都","泸州","内江","凉山","阿坝","巴中","广元","乐山","绵阳","德阳","攀枝花","雅安","宜宾","自贡","甘孜州","达州","资阳","广安","遂宁","眉山","南充"
91 "101270101","101271001","101271201","101271601","101271901","101270901","101272101","101271401","101270401","101272001","101270201","101271701","101271101","101270301","101271801","101270601","101271301","101270801","101270701","101271501","101270501"
92
93 广东
94 "广州","深圳","潮州","韶关","湛江","惠州","清远","东莞","江门","茂名","肇庆","汕尾","河源","揭阳","梅州","中山","德庆","阳江","云浮","珠海","汕头","佛山"
95 "101280101","101280601","101281501","101280201","101281001","101280301","101281301","101281601","101281101","101282001","101280901","101282101","101281201","101281901","101280401","101281701","101280905","101281801","101281401","101280701","101280501","101280800"
96
97 广西
98 "南宁","桂林","阳朔","柳州","梧州","玉林","桂平","贺州","钦州","贵港","防城港","百色","北海","河池","来宾","崇左"
99 "101300101","101300501","101300510","101300301","101300601","101300901","101300802","101300701","101301101","101300801","101301401","101301001","101301301","101301201","101300401","101300201"
100
101 云南
102 "昆明","保山","楚雄","德宏","红河","临沧","怒江","曲靖","思茅","文山","玉溪","昭通","丽江","大理"
103 "101290101","101290501","101290801","101291501","101290301","101291101","101291201","101290401","101290901","101290601","101290701","101291001","101291401","101290201"
104
105 海南
106 "海口","三亚","儋州","琼山","通什","文昌"
107 "101310101","101310201","101310205","101310102","101310222","101310212"
108
109 新疆
110 "乌鲁木齐","阿勒泰","阿克苏","昌吉","哈密","和田","喀什","克拉玛依","石河子","塔城","库尔勒","吐鲁番","伊宁"
111 "101130101","101131401","101130801","101130401","101131201","101131301","101130901","101130201","101130301","101131101","101130601","101130501","101131001"
112
113 西藏
114 "拉萨","阿里","昌都","那曲","日喀则","山南","林芝"
115 "101140101","101140701","101140501","101140601","101140201","101140301","101140401"
116
117 台湾
118 "台北","高雄"
119 "101340102","101340201"

城市代码

一看上去很乱的，而且对应关系是每个省城市一行，代码一行，分别用引号引起，用逗号分隔，每行间都没有符号分隔，省名没有用引号。首先是想着把省名去掉，因为每个城市名都是不相同的。想着每两行两行的去处理，但是也要费不少功夫，还容易出错。就想个索性一次性的全处理的算法。

ps：界面很简单，上面是输入数据，中间是转换，下面是输出数据。

后台主要代码：
[csharp] view plain copy

private void button1_Click(object sender, EventArgs e)
{
string data = textBox1.Text.Replace("r", "").Replace("n", "").Replace("t", "").Replace(" ", "").Replace(" ", "").Replace(" ", "");
MatchCollection matchsdata = matches(data, ""[sS]*?"");
string[,] temps = new string[matchsdata.Count / 2, 2];
int count0 = 0;
int count1 = 0;
string input = string.Empty;
foreach (Match m in matchsdata)
{
string tempdata = m.Value.Replace(""", "");
try
{
int tryp = int.Parse(tempdata);
temps[count1, 1] = tempdata;
count1++;
}
catch (Exception ex)
{
temps[count0, 0] = tempdata;
count0++;
}
}
for (int i = 0; i < (matchsdata.Count / 2); i++)
{
input += "insert into tbl_CityCode(c_city,c_code) values( + temps[i, 0] + , + temps[i, 1] + )rn";
}
textBox2.Text = input;
}

public static MatchCollection matches(string str, string exp)
{
return Regex.Matches(str, exp, RegexOptions.IgnoreCase);
}

首先是将输入的数据处理，去除换行符，空格什么的。然后你应该是会得到一行数据，然后通过正则表达式匹配出所有带引号的数据，你会发现需要的数据全部都是用引号引起来的，但是怎样区分城市名和城市代码呢，它们是混在一起的。不用担心，你发现了吗？城市名是字符串，城市代码是一串数字，我们只要将匹配出的数据数组遍历，每一行数据都去转换成int类型，这样城市名的行就会报错，在catch中捕捉，这一行就是城市名，没错的就是城市代码，把数据一次存到一个二维数组，对应的列中就行了。这样就会获得了相对应的城市名和城市代码。生成的sql语句要对应相应的数据库表。
表结构：
转换完了将生成的sql语句放到查询器中执行就ok了。共处理了349个城市。
最后不放心自己的算法，随机抽查了几条数据，没有错误。

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