在不连接到 SQL 数据库的情况下转换 Pandas DataFrame

Question

All solutions I have seen require connecting to a SQL database, which IS NOT the goal of this question.

The Goal Is To Convert A DataFrame To A String Capturing How To Re-Create The DataFrame That I Can Save As A Valid.sql File

Let's say I have a simple pandas DataFrame:

df = pd.DataFrame({{'hello'}:[1], {'world}:[2]})

...and I wanted to automatically convert it into a.sql file that could be executed to generate the table, so something like:

#psuedocode

py_script.output_file_sql('my_table')

  return  """CREATE TABLE my_table (

      hello   integer,

      world   integer

);""

Problem:

1. I can't find the documentation for pandas conversion into an.sql without actually connecting to a database.

2. If I use sqlalchemy, then run a query with information_schema.columns or \d table_name that doesn't seem to work.

Any suggestions?

Answer 1

you need to map all the datatypes correctly, i only used a sample to show you how top start.

But to be correct you need to rebuild all https://www.postgresql.org/docs/current/sql-createtable.html if you want to have all options

So i repeat my comment, best is to backup your database on database server with a backup tool, and use hat instead.

import pandas as pd
df = pd.DataFrame({'hello':[1], 'world':[2]})
df.name = 'Ones'
indextext = "hello"
def typeconversion(x):
    return {
        'int64': 'bigint ',
        'float64': 'FLOAT'
    }[x]

def get_sql(df,Indexx_table):

    STR_sql = "CREATE TABLE " +  df.name + "( "

    for (col1, col2) in zip(df.columns, df.dtypes):    
        STR_sql += col1 + " " + typeconversion(col2.name) + ','
    #remove last comma
    STR_sql = STR_sql[:-1]
    if Indexx_table:
        STR_sql += ", PRIMARY KEY (" + Indexx_table + ")"
    STR_sql += ")"
    return STR_sql

print(get_sql(df,indextext))

result is

CREATE TABLE Ones( hello bigint ,world bigint , PRIMARY KEY (hello))