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python sqlalchemy不同的列值

[英]python sqlalchemy distinct column values

I have 6 tables in my SQLite database, each table with 6 columns( Date, user, NormalA, specialA, contact, remarks ) and 1000+ rows. 我的SQLite数据库中有6个表,每个表有6列( Date, user, NormalA, specialA, contact, remarks )和1000多行。

How can I use sqlalchemy to sort through the Date column to look for duplicate dates, and delete that row? 如何使用sqlalchemy对Date列进行排序以查找重复日期,并删除该行?

Assuming this is your model: 假设这是你的模型:

class MyTable(Base):
    __tablename__ = 'my_table'
    id = Column(Integer, primary_key=True)
    date = Column(DateTime)
    user = Column(String)
    # do not really care of columns other than `id` and `date`
    # important here is the fact that `id` is a PK

following are two ways to delete you data: 以下是两种删除数据的方法:

  1. Find duplicates, mark them for deletion and commit the transaction 查找重复项,将其标记为删除并提交事务
  2. Create a single SQL query which will perform deletion on the database directly. 创建一个SQL查询,直接在数据库上执行删除。

For both of them a helper sub-query will be used: 对于它们两者,将使用辅助子查询:

# helper subquery: find first row (by primary key) for each unique date
subq = (
    session.query(MyTable.date, func.min(MyTable.id).label("min_id"))
    .group_by(MyTable.date)
) .subquery('date_min_id')

Option-1: Find duplicates, mark them for deletion and commit the transaction 选项-1:查找重复项,将其标记为删除并提交事务

# query to find all duplicates
q_duplicates = (
    session
    .query(MyTable)
    .join(subq, and_(
        MyTable.date == subq.c.date,
        MyTable.id != subq.c.min_id)
    )
)

for x in q_duplicates:
    print("Will delete %s" % x)
    session.delete(x)
session.commit()

Option-2: Create a single SQL query which will perform deletion on the database directly 选项2:创建单个SQL查询,直接在数据库上执行删除

sq = (
    session
    .query(MyTable.id)
    .join(subq, and_(
        MyTable.date == subq.c.date,
        MyTable.id != subq.c.min_id)
    )
).subquery("subq")

dq = (
    session
    .query(MyTable)
    .filter(MyTable.id.in_(sq))
).delete(synchronize_session=False)

Inspired by the Find duplicate values in SQL table this might help you to select duplicate dates: SQL表中查找重复值的启发,这可能有助于您选择重复日期:

query = session.query(
    MyTable
).\
    having(func.count(MyTable.date) > 1).\
    group_by(MyTable.date).all()

If you only want to show unique dates; 如果您只想显示独特的日期; distinct on is what you might need distinct on是你可能需要的东西

While I like the whole object oriented approache with SQLAlchemy, sometimes I find it easier to directly use some SQL. 虽然我喜欢使用SQLAlchemy的整个面向对象的方法,但有时我发现直接使用某些SQL更容易。 And since the records don't have a key, we need the row number ( _ROWID_ ) to delete the targeted records and I don't think the API provides it. 由于记录没有密钥,我们需要行号( _ROWID_ )来删除目标记录,我认为API并不提供。

So first we connect to the database: 首先我们连接到数据库:

from sqlalchemy import create_engine
db = create_engine(r'sqlite:///C:\temp\example.db')
eng = db.engine

Then to list all the records: 然后列出所有记录:

for row in eng.execute("SELECT * FROM TableA;") :
  print row

And to display all the duplicated records where the dates are identical: 并显示日期相同的所有重复记录:

for row in eng.execute("""
  SELECT * FROM {table}
  WHERE {field} IN (SELECT {field} FROM {table} GROUP BY {field} HAVING COUNT(*) > 1)
  ORDER BY {field};
  """.format(table="TableA", field="Date")) :
  print row

Now that we identified all the duplicates, they probably need to be fixed if the other fields are different: 现在我们确定了所有重复项,如果其他字段不同,则可能需要修复它们:

eng.execute("UPDATE TableA SET NormalA=18, specialA=20 WHERE Date = '2016-18-12' ;");
eng.execute("UPDATE TableA SET NormalA=4,  specialA=8  WHERE Date = '2015-18-12' ;");

And finnally to keep the first inserted record and delete the most recent duplicated records : 并最终保留第一个插入的记录并删除最新的重复记录:

print eng.execute("""
  DELETE FROM {table} 
  WHERE _ROWID_ NOT IN (SELECT MIN(_ROWID_) FROM {table} GROUP BY {field});
  """.format(table="TableA", field="Date")).rowcount

Or to keep the last inserted record and delete the other duplicated records : 或者保留最后插入的记录并删除其他重复记录:

print eng.execute("""
  DELETE FROM {table} 
  WHERE _ROWID_ NOT IN (SELECT MAX(_ROWID_) FROM {table} GROUP BY {field});
  """.format(table="TableA", field="Date")).rowcount

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