php与mysql的常规使用

<?php
    header("Content-type:text/html;charset=GBK");
    /*
        通常，php网页中完成有关数据库的操作，首先，需要如下代码：
        $link = mysql_connect(“数据库服务器地址”,”用户名”,”密码”);    //连接数据库系统
        mysql_query(“set  names  网页文件编码名”);        //设定“连接编码”；
                        也可以这样做：mysql_set_charset(“网页文件编码名”);
        mysql_query(“use  数据库名”);        //选定要使用的数据库
                        也可以这样做：mysql_select_db(“数据库名”);
    */
    $link = mysql_connect("localhost","root","");
    mysql_set_charset("gbk");
    mysql_select_db("student");
    //添加数据
    // mysql_query("insert into stu1 value(null,'小刚',default,19)");
    echo "<h2>-------mysql_error()-------</h2>";
    /*
    获取mysql执行失败时的错误信息。它通常应用与如下场合：
    mysql_query语句，当执行成功时，会返回一个结果集，失败就会返回false
        $result  =  mysql_query(“select / delete / update / insert / create / dropt ....所有sql语句”);
    if( $result === false){
    echo “语句执行失败，请参考提示信息：” . mysql_error();
    }
    else{
    //这里是成功的情况，那就后续处理。。。
    }
    */
    //我们执行一个错误的query语句
    $error = mysql_query("insert into stu2 value(null,'小刚',default,19)");
    if($error===false){
        echo "执行失败，失败参考：".mysql_error();
    }else{
        echo "执行成功";
    }
    echo "<h2>-------查询语句-------</h2>";
    /*
        执行有数据返回的语句：select， show  tables， show  databases， desc  表名（显示表结构）；
        此时，使用mysql_query()函数，返回的结果分为：
        如果失败：返回的是false；
        如果成功：返回的是“结果集”——“数据集”——就是一行一行数据，就是有字段的一个“表结构”。它需要我们进一步去“取出”数据，才能使用其中的数据，其基本模式为：
        $result = mysql_query(“select ... “);    //执行有返回数据的语句
        while (  $rec  =  mysql_fetch_array( $result )  ){
            //mysql_fetch_array()会取出该结果集中的“一行数据”，并取得该行数据后赋值给$rec；
            //此$rec就是一个数组，其下标就是字段名；
            //在此while循环中，mysql_fetch_array()会一次次（一行行）取出结果集中的所有数据；
            然后，在这里就可以处理该数组$rec了：
        }

    fetch的三种类型
    1.    mysql_fetch_assoc($result):得到的数组类似这样：
        array(“id” => 1,  “name” => “user1”,  “age”=>18);

    2.    mysql_fetch_row($result):得到的数组类似这样：
        array(0=> 1,  1=> “user1”,  2=>18);

    3.    mysql_fetch_array($result):得到的数组类似这样：
        array(“id” => 1,  “name” => “user1”,  “age”=>18,  0=> 1,  1=> “user1”,  2=>18);

    */
    $str = mysql_query("select * from stu1");
    echo "<table border=1px>";
    echo "<tr><td>id</td><td>名字</td><td>性别</td><td>年龄</td></tr>";
    while ($arr = mysql_fetch_array($str)) {
        echo "<tr>";
        echo "<td>".$arr['id']."</td>";
        echo "<td>".$arr['name']."</td>";
        echo "<td>".$arr['sex']."</td>";
        echo "<td>".$arr['age']."</td>";
        echo "</tr>";
    }
    echo "</table>";
    echo "<h2>-------通用的查询语句-------</h2>";
    /*
    扩展php中操作mysql数据的几个函数：
    $n1 = mysql_num_rows(结果集);    //获得该结果集的数据行数；
    $n2 = mysql_num_fields(结果集);    //获得该结果集的数据列数；
    $name = mysql_field_name(结果集, $i );    //获得结果集的第i个字段的名字！i从0开始算起
    */
    echo "<table border=1px>";
    //可以根据输入的查询语句的不同来显示查询结果
    $sql = "describe stu1";
    $str2 = mysql_query($sql);
    echo "<tr>";
    for($i = 0;$i<mysql_num_fields($str2);$i++){
        $name = mysql_field_name($str2, $i);
        echo "<td>".$name."</td>";
    }
    echo "</tr>";
    while ($arr = mysql_fetch_array($str2)) {
        echo "<tr>";
        for($i = 0;$i<mysql_num_fields($str2);$i++){
        $name = mysql_field_name($str2, $i);
            echo "<td>".$arr[$name]."</td>";
        }
        echo "</tr>";
    }
    echo "</table>";
?>

效果演示

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" 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