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我创建了一个 Python 脚本，它从政府网站提取数据，格式化数据，然后将数据转储到 Access 表中。

我正在使用 Sqlalchemy 和 pyodbc 导入数据；但是，如果我的数据完全有一个整数列，我会得到可怕的“pyodbc.Error: ('HYC00', '[HYC00] [Microsoft][ODBC Access Database Driver]Optional feature not implemented (0) (SQLBindParameter)' ）“ 错误信息。

有谁知道解决此错误的任何方法，即使一列已格式化为整数，我也可以导入已格式化的数据？我了解解决此问题的方法是将列格式化为浮动，但我不想浮动。还有其他选择吗？

这是我的测试代码：

import pandas as pd
from pandas import DataFrame

import numpy as np
import re as re
import pyodbc
from sqlalchemy import create_engine

# Download zipfile from BOEM website, extract and save file to temp folder
from io import BytesIO
from urllib.request import urlopen
from zipfile import ZipFile
zipurl = 'https://www.data.boem.gov/Well/Files/5010.zip'
with urlopen(zipurl) as zipresp:
    with ZipFile(BytesIO(zipresp.read())) as zfile:
        zfile.extractall('/temp/leasedata')


# Import fixed field file to Pandas for formatting

# Define column spacing of fixed field file
colspecs = [(0, 12), (13, 17), (18, 26), (27, 31), (31, 37), (39, 47), (47, 53), (57, 62), (62, 67),
            (67, 73), (84, 86), (86, 92), (104, 106), (106, 112), (112, 120), (120, 128), (131, 134), (134, 139),
            (140, 155), (156, 171), (172, 187), (188, 203), (203, 213)]

df = pd.read_fwf('/temp/leasedata/5010.DAT', colspecs=colspecs, header=None)
# Add column headers
df.columns = ['API', 'WellName', 'Suffix', 'OprNo', 'BHFldName', 'SpudDate', 'BtmOCSLse', 'RKBElev', 'TotalMD',
              'TVD', 'SurfArea', 'SurfBlock', 'BHArea', 'BHBlock', 'TDDate', 'StatusDate', 'StatusCode', 'WaterDepth',
              'SurfLon', 'SurfLat', 'BHLon', 'BHLat', 'SurfOCSLse']

# Load dataframe into new temp table in database

# Connect to OOSA Access database. Make sure to create a User DSN directly to OOSA database before running script

conn = create_engine("access+pyodbc://@OOSA")

print(df)

df.to_sql('borehole_temp_table', conn, if_exists='replace')

感谢您的帮助！

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1 回答 1

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我了解解决此问题的方法是将列格式化为浮动，但我不想浮动。还有其他选择吗？

从sqlalchemy-access 维基：

解决方法包括将列保存为 ShortText ...</p> 

import sqlalchemy_access as sa_a

# …

df = pd.DataFrame(
    [
        (12345678901,),
        (-12345678901,),
    ],
    columns=["column1"],
)
df["column1"] = df["column1"].astype(str)
dtype_dict = {'column1': sa_a.ShortText(20)}
df.to_sql("my_table", engine, index=False, if_exists="replace", dtype=dtype_dict)

… 或十进制

df = pd.DataFrame(
    [
        (12345678901,),
        (-12345678901,),
    ],
    columns=["column1"],
)
df["column1"] = df["column1"].astype(str)  # still need to convert the column to string!
dtype_dict = {'column1': sa_a.Decimal(19, 0)}
df.to_sql("my_table", engine, index=False, if_exists="replace", dtype=dtype_dict)
于 2021-10-08T13:55:32.360 回答