psycopg2:无法适应类型'numpy.int64' [英] psycopg2: can't adapt type 'numpy.int64'

问题描述

我有一个具有如下所示dtypes的数据框，我想将该数据框插入到postgres DB中，但是由于错误 不能适应类型为'numpy.int64'

I have a dataframe with the dtypes shown below and I want to insert the dataframe into a postgres DB but it fails due to error can't adapt type 'numpy.int64'

id_code               int64
sector              object
created_date         float64
updated_date    float64

如何将这些类型转换为本地python类型，例如从int64(本质上是"numpy.int64")转换为经典int，然后可以通过psycopg2客户端对postgres进行接受.

How can I convert these types to native python types such as from int64 (which is essentially 'numpy.int64') to a classic int that would then be acceptable to postgres via the psycopg2 client.

data['id_code'].astype(np.int)  defaults to int64

仍然可以从一种numpy类型转换为另一种(例如，从int转换为float)

It is nonetheless possible to convert from one numpy type to another (e.g from int to float)

data['id_code'].astype(float)

更改为

dtype: float64

最重要的是，如果有人知道如何将psycopg2转换为经典类型，psycopg2似乎不理解numpy数据类型.

The bottomline is that psycopg2 doesn't seem to understand numpy datatypes if any one has ideas how to convert them to classic types that would be helpful.

已更新:插入数据库

def insert_many():
    """Add data to the table."""
    sql_query = """INSERT INTO classification(
                id_code, sector, created_date, updated_date)
                VALUES (%s, %s, %s, %s);"""
    data = pd.read_excel(fh, sheet_name=sheetname)
    data_list = list(data.to_records())

    conn = None
    try:
        conn = psycopg2.connect(db)
        cur = conn.cursor()
        cur.executemany(sql_query, data_list)
        conn.commit()
        cur.close()
    except(Exception, psycopg2.DatabaseError) as error:
        print(error)
    finally:
        if conn is not None:
            conn.close()

推荐答案

我不确定为什么您的data_list包含NumPy数据类型，但是当我运行您的代码时，我也会遇到同样的事情.这是构造data_list的另一种方法，该方法使整数和浮点数最终成为其本机python类型:

I'm not sure why your data_list contains NumPy data types, but the same thing happens to me when I run your code. Here is an alternative way to construct data_list that so that integers and floats end up as their native python types:

data_list = [list(row) for row in data.itertuples(index=False)] 

---

替代方法

我认为，使用pandas

I think you could accomplish the same thing in fewer lines of code by using pandas to_sql:

import sqlalchemy
import pandas as pd
data = pd.read_excel(fh, sheet_name=sheetname)
engine = sqlalchemy.create_engine("postgresql://username@hostname/dbname")
data.to_sql(engine, 'classification', if_exists='append', index=False)

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