jd_check_dependent.py

jd_check_dependent.py是一个用于检查JD（职位描述）与依赖项之间关联性的Python脚本。在招聘流程中，有时会有一些特定的职位要求对应着特定的技能或经验，这些技能或经验往往为该职位的依赖项。因此，为了更好地筛选候选人并节省时间和人力成本，我们可以利用这个脚本来自动化这个过程。

该脚本的主要功能是根据预先定义的依赖项列表，对比JD中所列出的技能和经验要求，然后输出是否满足依赖项的要求。脚本通过读取JD文件并解析其中的内容，然后与依赖项列表进行比对来实现这个功能。

首先，脚本需要读取依赖项列表的文件，并从中提取技能和经验要求。然后，脚本会读取JD文件，并根据预先定义的关键词来提取其中的技能和经验要求。接下来，脚本会将JD中的要求与依赖项列表进行匹配，并标记满足或不满足依赖项要求的内容。

最后，脚本将根据匹配的结果生成一个报告，并输出满足依赖项要求的职位和未满足要求的职位。这样，招聘团队可以更方便地筛选候选人，只需要关注满足依赖项要求的职位。

总之，jd_check_dependent.py是一个用于自动化检查JD与依赖项之间关联性的Python脚本。它可以帮助招聘团队更高效地筛选候选人，并节省时间和人力成本。

相关问题

select c.`stock_id`,a.`stock_name`,a.`coupon_amount`, a.`transaction_minimum`, b.`company_name`, a.`start_time`, a.`end_time`, (select count(1) from user_coupon where `activity_id` = a.`id`) as `grant`,(select count(1) from user_coupon where `activity_id` = a.`id` and (status = "20" or status = "30")) as `receive`,(select count(1) from user_coupon where `activity_id` = a.`id` and status = "30") as `writeOff` from wx_coupon a left join baishiof_company b on a.company_id = b.company_id left join user_coupon c on a.`id` = c.`activity_id` group by c.`stock_id`这段SQL报Expression #2 of SELECT list is not in GROUP BY clause and contains nonaggregated column 'baishiof.a.stock_name' which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by错误 修改这条SQL使其可以执行

要修复这个错误，你可以调整 GROUP BY 子句配置，以便在查询中包含所有非聚合列。修改后的 SQL 查询语句如下：

SELECT
    c.stock_id,
    a.stock_name,
    a.coupon_amount,
    a.transaction_minimum,
    b.company_name,
    a.start_time,
    a.end_time,
    (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id) AS grant,
    (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND (status = "20" OR status = "30")) AS receive,
    (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND status = "30") AS writeOff
FROM
    wx_coupon a
LEFT JOIN
    baishiof_company b ON a.company_id = b.company_id
LEFT JOIN
    user_coupon c ON a.id = c.activity_id
GROUP BY
    c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time;

通过在 GROUP BY 子句中包含所有非聚合列，这个错误就被修复了。请注意，根据你的实际需求和数据库结构，你可能需要调整 GROUP BY 子句中的列。

SELECT DISTINCT p.*, u1.id AS directorId, CASE WHEN up1.member_type = 348 THEN u1.nickname ELSE up1.member_name END AS directorName FROM project p LEFT JOIN userproject up1 ON p.p_id=up1.p_id AND up1.director=1 LEFT JOIN sys_user u1 ON up1.member_id = u1.id LEFT JOIN userproject up ON p.p_id=up.p_id LEFT JOIN sys_user u ON up.member_id = u.id LEFT JOIN sys_user_department d ON d.user_id = u.id WHERE (p.enable = ? AND p.audit_status = ? AND p.organization_id = ? AND p.project_name IS NOT NULL) GROUP BY p.project_name,p.project_code,p.project_nature ORDER BY p.p_id DESC报错Expression #1 of SELECT list is not in GROUP BY clause and contains nonaggregated column 'spms.p.p_id' which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by怎么处理

这是因为 MySQL 的 sql_mode 设置了 only_full_group_by，导致在 GROUP BY 子句中未包含的列不能在 SELECT 子句中使用。可以尝试以下两种处理方式：

1. 修改 sql_mode
将 MySQL 的 sql_mode 修改为不包含 only_full_group_by 这个选项，可以在 MySQL 配置文件 my.cnf 或者 my.ini 中找到 sql_mode 选项，将其修改为：

sql_mode=NO_ENGINE_SUBSTITUTION

然后重启 MySQL 服务即可生效。

2. 修改查询语句
在 SELECT 子句中将非聚合列 p.p_id 改为聚合列，例如使用 MAX(p.p_id)。修改后的查询语句如下：

SELECT DISTINCT MAX(p.p_id) AS p_id, p.project_name, p.project_code, p.project_nature, u1.id AS directorId, CASE WHEN up1.member_type = 348 THEN u1.nickname ELSE up1.member_name END AS directorName 
FROM project p 
LEFT JOIN userproject up1 ON p.p_id=up1.p_id AND up1.director=1 
LEFT JOIN sys_user u1 ON up1.member_id = u1.id 
LEFT JOIN userproject up ON p.p_id=up.p_id 
LEFT JOIN sys_user u ON up.member_id = u.id 
LEFT JOIN sys_user_department d ON d.user_id = u.id 
WHERE (p.enable = ? AND p.audit_status = ? AND p.organization_id = ? AND p.project_name IS NOT NULL) 
GROUP BY p.project_name,p.project_code,p.project_nature 
ORDER BY p.p_id DESC