在数据库设计完成之后, 常常需要在 wiki 或其他文档中保存一份数据库中所有表的 desc 描述, 尤其是每个字段的含义和用途。 手动去生成自然是不可取的。 因此, 我编写了一个简单的 python 程序,可以自动生成数据库中所有表的 desc 描述, 并以可读格式输出。

# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------------
# Name: db_tables_descs.py
# Purpose: generate the tables that describe the meanings of fields in db
#
# Author: qin.shuq
#
# Created: 2014/11/17
# Output: desc.txt
# recording the tables that describe the meanings of fields in db
#-------------------------------------------------------------------------------
#!/usr/bin/env python import db globalFieldDescs = ('Field', 'Type', 'Null', 'Key', 'Default', 'Extra') globalDescFile = 'desc.txt' conflictedWithMysqlKeywords = set(['group']) fieldDescMapping = {
'id': '唯一标识',
'is_deleted': '是否逻辑删除',
'status': '实体状态',
'type': '实体类型',
'priority': '优先级',
'password': '密码',
'ip': 'ip 地址',
'mac': 'mac 地址',
'protocol': '访问协议',
'user_id': '用户唯一标识'
} def formatCols(fieldDesc):
return "%-16s %-24s %-5s %-8s %-8s %-30s" % fieldDesc def withNewLine(astr):
return astr + '\n' def commonFieldsProcess(fieldDescList):
fieldName = fieldDescList[0]
fieldDesc = fieldDescMapping.get(fieldName)
desclen = len(fieldDescList)
if fieldDesc is None:
if fieldName.startswith('gmt_c'):
fieldDesc = '创建时间'
elif fieldName.startswith('gmt_m'):
fieldDesc = '修改时间'
else:
fieldDesc = fieldDescList[desclen-1]
fieldDescList[desclen-1] = fieldDesc def formatF(fieldDescTuple):
fieldDescList = list(fieldDescTuple)
fieldLen = len(fieldDescList)
for i in range(fieldLen):
if fieldDescList[i] is None:
fieldDescList[i] = 'NULL'
else:
fieldDescList[i] = str(fieldDescList[i])
commonFieldsProcess(fieldDescList)
return formatCols(tuple(fieldDescList)) def format(tableDesc):
desc = ''
for fieldDescTuple in tableDesc:
desc += withNewLine(formatF(fieldDescTuple))
return desc def descDb(givenDb):
tablesRet = givenDb.query("show tables;")
tableNames = [table[0] for table in tablesRet]
desc = u''
for tablename in tableNames:
if tablename in conflictedWithMysqlKeywords:
tablename = '`' + tablename + '`'
descSql = "desc " + tablename
tableDesc = givenDb.query(descSql)
desc += withNewLine(tablename)
desc += withNewLine(formatCols(globalFieldDescs)).decode('utf-8')
desc += withNewLine(format(tableDesc)).decode('utf-8')
desc += withNewLine('').decode('utf-8')
return desc def main(): descFile = open(globalDescFile, 'w') desc = descDb(db.Mydb())
descFile.write(desc.encode('utf-8')) descFile.close() if __name__ == '__main__':
main()

db.py

#!/usr/ali/bin/python
# coding=utf-8 '''Implements a database api to your db. Example 1: Query SQL a. Use execute() method to execute query sql: db.execute('select * from ip') # Get only the first two rows
db.get_rows(2)
# result like [('10.10.0.1', 'my'), ..] # Get the next two rows, but each row record is a dict
db.get_rows(2, is_dict = True)
# result like [{'address':'10.10.0.1', 'name': 'my'}, ..] b. Use query() method to execute query sql directly: # The query() method will get the result rows immediately
db.query('select * from ip', size = 2, is_dict = True) c. Use split_query() method to split long query into small ones: # Assume that the name_list's length is 10000
# See the docstring of split_query() for more details
db.split_query('select address from ip', 'name', name_list) Example 2: Insert SQL a. Insert a new record into ip table: db.execute("insert into ip('address','name') values('192.168.0.1','vm-xxx')") # If auto commit set to false, call commit() method manually
db.commit() b. Insert multi-records into ip table: db.executemany("insert into ip('address','name') values(%s,%s)", [
('192.168.0.1', 'vm-xxx'),
('192.168.0.2', 'vm-yyy'),
('192.168.0.3', 'vm-zzz')])
db.commit() Note: db.multi_insert is an alias for executemany method.
See test_main() method for more examples.
''' from database import DB class Mydb(DB):
'''A simple query interface of a specific database.'''
def __init__(self, read_only = True,
auto_commit = False, timeout = 5, auto_connect = False,
max_idle_time = 28800):
'''Initialize the database access object.'''
# Get the database parameters
args = {'host':'127.0.0.1', 'user':'root','passwd':'','db':'mysql','port':3306,'charset':'utf8'} # Set extra connection parameters
args['connect_timeout'] = timeout
args['auto_commit'] = auto_commit
args['max_idle_time'] = max_idle_time
args['auto_connect'] = auto_connect DB.__init__(self, **args)

database.py

#!/usr/ali/bin/python
# coding=utf-8 '''Implements a simple database interface Example 0: Create connection: # Set auto commit to false, default case
db = DB(auto_commit = False, host = 'x', user = 'x', passwd = 'x', db = 'x')
# Set auto commit to true
db = DB(auto_commit = True, host = 'x', user = 'x', passwd = 'x', db = 'x')
# Set auto connect to true, this will set auto commit to true too
# This will enable auto connect when the connection is timeout
db = DB(auto_connect = True, host = 'x', user = 'x', passwd = 'x', db = 'x') Example 1: Query SQL a. Use query() method to execute query sql directly: # The query() method will get the result rows immediately
db.query('select * from ip', size = 2, is_dict = True) c. Use split_query() method to split long query into small ones: # Assume that the name_list's length is 10000
# See the docstring of split_query() for more details
db.split_query('select address from ip', 'name', name_list) Example 2: Insert SQL a. Insert a new record into ip table: db.execute("insert into ip('address','name') values('192.168.0.1','vm-xxx')") # If auto commit set to false, call commit() method manually
db.commit() b. Insert multi-records into ip table: db.executemany("insert into ip('address','name') values(%s,%s)", [
('192.168.0.1', 'vm-xxx'),
('192.168.0.2', 'vm-yyy'),
('192.168.0.3', 'vm-zzz')])
db.commit() Note: db.multi_insert is an alias for executemany method.
''' # Can be 'Prototype', 'Development', 'Product'
__status__ = 'Development'
__author__ = 'tuantuan.lv <tuantuan.lv@alibaba-inc.com>' import re
import time
import MySQLdb from storage import Storage OperationalError = MySQLdb.OperationalError def _format(sql):
'''Format the sql.'''
return ' '.join(sql.split()) class DB():
'''A simple database query interface.'''
def __init__(self, auto_commit = False, auto_connect = False,
max_idle_time = 28800, **kwargs):
'''Initialize the DB object.'''
#
# Remember the max idle time (default: 28800)
# You should set this value to mysql option 'wait_timeout'
#
# mysql> show variables like 'wait_timeout';
# +---------------+-------+
# | Variable_name | Value |
# +---------------+-------+
# | wait_timeout | 28800 |
# +---------------+-------+
#
self.max_idle_time = max_idle_time kwargs.setdefault('charset', 'utf8') # set default charset to utf8
kwargs['port'] = int(kwargs.get('port', '')) # set default port to 3306 self._db = None # MySQLdb connection object
self._db_cursor = None # MySQLdb cursor object
self.cursor = None # MySQLdb cursor object, deprecated
self._db_args = kwargs # MySQL db connection args
self._last_use_time = time.time() # Last active time self._auto_connect = auto_connect # Auto connect when timeout
self._auto_commit = auto_commit # Auto commit # Open a new mysql connection
self._reconnect() def __del__(self):
self.close() def close(self):
'''Close the database connection.'''
if self._db is not None:
self._db_cursor.close()
self._db.close()
self._db = None def _reconnect(self):
'''Close existing connection and re-open a new one.'''
self.close()
self._db = MySQLdb.connect(**self._db_args) # Override auto commit setting if auto connect is true
if self._auto_connect:
self._db.autocommit(True)
else:
self._db.autocommit(self._auto_commit) self._db_cursor = self._db.cursor()
self.cursor = self._db_cursor def _ensure_connected(self):
'''Ensure we connect to mysql.'''
# Mysql by default closes client connections that are idle for
# 8 hours, but the client library does not report this fact until
# you try to perform a query and it fails. Protect against this
# case by preemptively closing and reopening the connection
# if it has been idle for too long (8 hours by default).
if (self._db is None or
(time.time() - self._last_use_time > self.max_idle_time)):
self._reconnect() self._last_use_time = time.time() def _cursor(self):
'''Get the cursor.'''
if self._auto_connect:
self._ensure_connected() return self._db_cursor def execute(self, sql, args = None):
'''Execute a sql and return the affected row number. You should call the get_rows method to fetch the rows manually.
'''
cursor = self._cursor()
return cursor.execute(_format(sql), args) def execute_lastrowid(self, sql, args = None):
'''Execute a sql and return the last row id. You should call the get_rows method to fetch the rows manually.
'''
cursor = self._cursor()
cursor.execute(_format(sql), args) return cursor.lastrowid def executemany(self, sql, args):
'''Execute a multi-row insert. You can use this method to do a multi-row insert: c.executemany(
"""INSERT INTO breakfast (name, spam, eggs, sausage, price)
VALUES (%s, %s, %s, %s, %s)""",
[
("Spam and Sausage Lover's Plate", 5, 1, 8, 7.95 ),
("Not So Much Spam Plate", 3, 2, 0, 3.95 ),
("Don't Wany ANY SPAM! Plate", 0, 4, 3, 5.95 )
] ) See http://mysql-python.sourceforge.net/MySQLdb.html for more help.
'''
cursor = self._cursor()
return cursor.executemany(_format(sql), args) # Execute a multi-row insert, the same as executemany()
multi_insert = executemany def get_rows(self, size = None, is_dict = False):
'''Get the result rows after executing.'''
cursor = self._cursor()
description = cursor.description if size is None:
rows = cursor.fetchall()
else:
rows = cursor.fetchmany(size) if rows is None:
rows = [] if is_dict:
dict_rows = []
dict_keys = [ r[0] for r in description ] for row in rows:
dict_rows.append(Storage(zip(dict_keys, row))) rows = dict_rows return list(rows) def query(self, sql, args = None, size = None, is_dict = False):
'''Execute a query sql and return the rows immediately.'''
self.execute(sql, args)
return self.get_rows(size, is_dict) # Alias of query() method
select = query def split_query(self, sql, in_attr, in_list, max_cnt = 3000):
'''Split one long query into many small ones. For example, if you want to select the records whose attrname is in
one long list (larger than 8000) of possible values. If you decide to
use 'attr in (...)' syntax, the length will exceed the maximum length
of one sql allowed. In this case you must split the long query into many
small ones. in_attr is the attribute name of in operator, and in_list is the possible
value list. max_cnt is the maximum count of values in one small query.
'''
total = len(in_list) start = 0
end = max_cnt result = [] if re.search(r'\bwhere\b', sql.lower()):
#if sql.lower().find('where ') != -1 or sql.lower().find('where\n') != -1:
sql = '%s and %s in %%s' % (sql, in_attr)
else:
sql = '%s where %s in %%s' % (sql, in_attr) while start < total:
if end < total:
in_expr = "('%s')" % "','".join(in_list[start:end])
else:
in_expr = "('%s')" % "','".join(in_list[start:]) result.extend(self.query(sql % in_expr)) start = end
end += max_cnt return result #def get_autoincrement_id(self, tbl):
# '''Get the next auto increment id of table.
#
# Return None if the table doesn't have an auto-increment id.
# '''
# self.execute('SHOW TABLE STATUS LIKE %s', (tbl,))
# result = self.get_rows(is_dict = True) # if result[0]:
# return result[0]['Auto_increment']
# else:
# return None def commit(self):
'''Commits the current transaction.'''
if self._db is not None:
self._db.commit() def rollback(self):
'''Rollback the last transaction.'''
if self._db is not None:
self._db.rollback() # vim: set expandtab smarttab shiftwidth=4 tabstop=4:

storage.py

#!/usr/ali/bin/python
# coding=utf-8 '''Wrap an existing dict, or create a new one, and access with dot notation See test_main() for more example.
''' # Can be 'Prototype', 'Development', 'Product'
__status__ = 'Development'
__author__ = 'tuantuan.lv <tuantuan.lv@alibaba-inc.com>' # Taken from http://stackoverflow.com/a/12187277
class Storage(object):
'''Wrap an existing dict, or create a new one, and access with dot notation. The attribute _data is reserved and stores the underlying dictionary. args:
d: Existing dict to wrap, an empty dict created by default.
create: Create an empty, nested dict instead of raising a KeyError.
'''
def __init__(self, d = None, create = True):
'''Initialize storage object.'''
if d is None: # Create empty storage object
d = {}
else: # create as a dictionary?
d = dict(d) # Set storage attributes
self.__dict__['__storage_data'] = d
self.__dict__['__storage_create'] = create def __getattr__(self, name):
'''Get the key value.'''
try:
value = self.__dict__['__storage_data'][name] except KeyError:
# Create empty storage value if auto-create set to true
if not self.__dict__['__storage_create']:
raise value = {}
self.__dict__['__storage_data'][name] = value # Create nested dict if the value has items attribute
if isinstance(value, dict):
value = Storage(value, self.__dict__['__storage_create'])
self.__dict__['__storage_data'][name] = value return value def __setattr__(self, name, value):
'''Set the storage key to value'''
self.__dict__['__storage_data'][name] = value def __delattr__(self, name):
'''Delete the storage key.'''
del self.__dict__['__storage_data'][name] def __contains__(self, name):
'''Check whether the key exists.'''
return name in self.__dict__['__storage_data'] def __nonzero__(self):
'''Check whether the storage is empty.'''
return bool(self.__dict__['__storage_data']) # Defines common dict api
__getitem__ = __getattr__
__setitem__ = __setattr__
__delitem__ = __delattr__ def get(self, name, default = None):
'''Defines an get method.'''
return self.__dict__['__storage_data'].get(name, default) # Define dictionary like methods
def keys(self):
return self.__dict__['__storage_data'].keys() def items(self):
return self.__dict__['__storage_data'].items() def values(self):
return self.__dict__['__storage_data'].values() def setdefault(self, name, default = None):
return self.__dict__['__storage_data'].setdefault(name, default) def pop(self, name, *args):
return self.__dict__['__storage_data'].pop(name, *args) def update(self, d, **kwargs):
return self.__dict__['__storage_data'].update(d, **kwargs) def clear(self):
self.__dict__['__storage_data'].clear() def __len__(self):
return len(self.__dict__['__storage_data']) def __iter__(self):
return self.__dict__['__storage_data'].__iter__() def __unicode__(self):
return u'<Storage %s>' % str(self.__dict__['__storage_data']) def __str__(self):
return '<Storage %s>' % str(self.__dict__['__storage_data']) def __repr__(self):
return '<Storage %s>' % repr(self.__dict__['__storage_data']) def test_main():
# Create an empty storage
d1 = Storage()
d1.a.b = 1
d1.b.c = 2 # Iterate the items in storage object
for k, v in d1.items():
print k, v # Create a storage in a (key,value) tuple
d3 = Storage(zip(['a','b','c'], [1,2,3]))
print d3.a, d3.b, d3.c
print d3 # Create a storage from a existing dict
d4 = Storage({'a':{'b':1}})
print d4.a.b
print d4 # Check the attribute
d5 = Storage()
print 'a' in d5 # False
print d5.a # create attribute 'a'
print 'a' in d5 # True
print d5.get('c')
print d5.get('d', 3) d5 = Storage(create = False)
print 'a' in d5 # False
print d5.get('a', 5)
print d5.a # raise KeyError
print 'a' in d5 # False, also if __name__ == '__main__':
test_main()

python生成数据库中所有表的DESC描述的更多相关文章

  1. Hibernate 由实体类与配置文件的配置关系生成数据库中的表

    import org.hibernate.cfg.Configuration; import org.hibernate.tool.hbm2ddl.SchemaExport; public class ...

  2. 获取SQL Server数据库中的表和字段描述

    获取所有dbo表的扩展属性: SELECT * FROM fn_listextendedproperty (NULL, 'schema', 'dbo', 'table', default, NULL, ...

  3. 通过jdbc获取数据库中的表结构 主键 各个表字段类型及应用生成实体类

    http://www.cnblogs.com/lbangel/p/3487796.html 1.JDBC中通过MetaData来获取具体的表的相关信息.可以查询数据库中的有哪些表,表有哪些字段,字段的 ...

  4. 通过数据库中的表,使用 MyEclipse2017的反向生成工具-->hibernate反转引擎引擎(MyEclipse2017自带的插件) 来反转生成实体类和对应的映射文件

    通过数据库中的表,使用 MyEclipse2017的反向生成工具-->hibernate反转引擎引擎(MyEclipse2017自带的插件) 来反转生成实体类和对应的映射文件   文章目录 Ja ...

  5. 分享一个SQLSERVER脚本(计算数据库中各个表的数据量和每行记录所占用空间)

    分享一个SQLSERVER脚本(计算数据库中各个表的数据量和每行记录所占用空间) 很多时候我们都需要计算数据库中各个表的数据量和每行记录所占用空间 这里共享一个脚本 CREATE TABLE #tab ...

  6. 清空SQL Server数据库中所有表数据的方法(转)

    清空SQL Server数据库中所有表数据的方法 其实删除数据库中数据的方法并不复杂,为什么我还要多此一举呢,一是我这里介绍的是删除数据库的所有数据,因为数据之间可能形成相互约束关系,删除操作可能陷入 ...

  7. 通过jdbc获取数据库中的表结构

    通过jdbc获取数据库中的表结构 主键 各个表字段类型及应用生成实体类   1.JDBC中通过MetaData来获取具体的表的相关信息.可以查询数据库中的有哪些表,表有哪些字段,字段的属性等等.Met ...

  8. (转)分享一个SQLSERVER脚本(计算数据库中各个表的数据量和每行记录所占用空间)

    分享一个SQLSERVER脚本(计算数据库中各个表的数据量和每行记录所占用空间) 很多时候我们都需要计算数据库中各个表的数据量和每行记录所占用空间 这里共享一个脚本 CREATE TABLE #tab ...

  9. 【Sqlserver清空数据库中所有表数据】

    脚本: CREATE PROCEDURE sp_DeleteAllData AS EXEC sp_MSForEachTable 'ALTER TABLE ? NOCHECK CONSTRAINT AL ...

随机推荐

  1. Quartzs -- Quartz.properties 配置

    Quartzs -- Quartz.properties 配置 文件加载位置 默认:优先顺序 Classpath:quartz.properties --> org/quartz/quartz. ...

  2. javascript知识点记录(2)

    1.js 异步加载和同步加载 异步加载模式也叫非阻塞模式,浏览器在下载js的同时,同时还会执行后续的页面处理, 在script标签内,用创建一个script元素,并插入到document中,这样就是异 ...

  3. DMV to track the temp file usage for SQLServer

    There are three DMVs you can use to track tempdb usage: sys.dm_db_task_space_usagesys.dm_db_session_ ...

  4. 在Ubutu14.04的Eclipse启动Tomcat的问题

    PS:因为tomcat文件夹的权限问题,导致我研究了一中午,首先是New Server时,不能输入server name,之后我删除了 org.eclipse.wst.server.core.pref ...

  5. 团队冲刺the first day

    2014年5月5号晚上我们团队小组一起做了团队项目.在此期间我们确定了项目的详细计划,,界面的安排,主界面,还有实现的具体功能,在这我就不做赘述了. 本次晚上我们做主界面,把界面和界面之间的调转实现了 ...

  6. sql拼接字符串和转换类型

    select top 10 a.ID as a_ID,a.Name as a_Name,c.* from (select * from DC_Trees where Pid=187 or ID=187 ...

  7. javascript设计模式学习之九——命令模式

    一.命令模式使用场景及定义 命令模式常见的使用场景是:有时候需要向某些对象发送请求,但是并不知道请求的接受者是谁,也不知道请求的具体操作是什么.此时希望用一种松耦合的方式来设计程序,使得请求的发送者和 ...

  8. RPC、SQL、NFS属于OSI的哪一层

    第一层:物理层 第二层:数据链路层 802.2.802.3ATM.HDLC.FRAME RELAY 第三层:网络层 IP.IPX.ARP.APPLETALK.ICMP 第四层:传输层 TCP.UDP. ...

  9. rpmdb出问题,重建rpmdb库

    1.备份原库 tar cvzf rpmdb-backup.tar.gz /var/lib/rpm 2.删除rpmdb库 rm -f /var/lib/rpm/__db.00* 3.重建库 rpm -- ...

  10. npm 介绍

    安装NPM NPM的全称是Node Package Manager,如果你熟悉ruby的gem,Python的PyPL.setuptools,PHP的pear,那么你就知道NPM的作用是什么了.没 错 ...