Python Pandas to_sql，如何用主键创建表? [英] Python Pandas to_sql, how to create a table with a primary key?

问题描述

我想用Pandas的to_sql函数创建一个具有主键的MySQL表(在mysql表中具有主键通常是一种好习惯)，如下所示:

I would like to create a MySQL table with Pandas' to_sql function which has a primary key (it is usually kind of good to have a primary key in a mysql table) as so:

group_export.to_sql(con = db, name = config.table_group_export, if_exists = 'replace', flavor = 'mysql', index = False)

但这会创建一个没有任何主键(甚至没有任何索引)的表.

but this creates a table without any primary key, (or even without any index).

文档中提到了参数"index_label"，该参数与"index"参数结合可用于创建索引，但未提及主键的任何选项.

The documentation mentions the parameter 'index_label' which combined with the 'index' parameter could be used to create an index but doesn't mention any option for primary keys.

文档

推荐答案

免责声明:此答案更具实验性，实用性强，但也许值得一提.

Disclaimer: this answer is more experimental then practical, but maybe worth mention.

我发现类pandas.io.sql.SQLTable的命名参数为key，如果您为其分配了字段名称，则该字段将成为主键:

I found that class pandas.io.sql.SQLTable has named argument key and if you assign it the name of the field then this field becomes the primary key:

不幸的是，您不能只从DataFrame.to_sql()函数传递此参数.要使用它，您应该:

Unfortunately you can't just transfer this argument from DataFrame.to_sql() function. To use it you should:

1. 创建pandas.io.SQLDatabase实例

engine = sa.create_engine('postgresql:///somedb')
pandas_sql = pd.io.sql.pandasSQL_builder(engine, schema=None, flavor=None)

定义类似于pandas.io.SQLDatabase.to_sql()的函数，但带有附加的*kwargs参数，该参数传递给在其中创建的pandas.io.SQLTable对象(我刚刚复制了原始的to_sql()方法并添加了*kwargs): /p>

define function analoguous to pandas.io.SQLDatabase.to_sql() but with additional *kwargs argument which is passed to pandas.io.SQLTable object created inside it (i've just copied original to_sql() method and added *kwargs):

def to_sql_k(self, frame, name, if_exists='fail', index=True,
           index_label=None, schema=None, chunksize=None, dtype=None, **kwargs):
    if dtype is not None:
        from sqlalchemy.types import to_instance, TypeEngine
        for col, my_type in dtype.items():
            if not isinstance(to_instance(my_type), TypeEngine):
                raise ValueError('The type of %s is not a SQLAlchemy '
                                 'type ' % col)

    table = pd.io.sql.SQLTable(name, self, frame=frame, index=index,
                     if_exists=if_exists, index_label=index_label,
                     schema=schema, dtype=dtype, **kwargs)
    table.create()
    table.insert(chunksize)

使用您的SQLDatabase实例和要保存的数据框调用此函数

call this function with your SQLDatabase instance and the dataframe you want to save

to_sql_k(pandas_sql, df2save, 'tmp',
        index=True, index_label='id', keys='id', if_exists='replace')

我们得到类似的东西

CREATE TABLE public.tmp
(
  id bigint NOT NULL DEFAULT nextval('tmp_id_seq'::regclass),
...
)

在数据库中.

PS当然，您可以使用Monkey-patch DataFrame，io.SQLDatabase和io.to_sql()函数来方便地使用此替代方法.

PS You can of course monkey-patch DataFrame, io.SQLDatabase and io.to_sql() functions to use this workaround with convenience.

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