將 python 響應轉換為 Json 響應

Question

我已經研究了 python 代碼，該代碼自動讀取多個擴展名的數據幀並打印 DF 的前 100 行及其列的類型，並有可能在同一個簡單的 function 中添加更多內容，我目前正在研究以 JSON 格式做出響應但仍然無法這樣做，因為這是我第一次使用 Json API 因為我更喜歡數據分析/科學而不是編程感謝您的幫助和建議

import os
import modin.pandas as pd


def sqlread(con_w_sql, sep='#'):
    con, sql = special_path.split(sep)
    df = pd.read_sql(sql, con)
    return df.head()

readict = {
    ".csv": {
         "read": pd.read_csv
     },
     ".tsv": {
         "read": pd.read_csv 
     },
     ".json": {
         "read": pd.read_json
     },
     ".xlsx": {
         "read": pd.read_excel 
     },
     ".xml": {
         "read": pd.read_xml 
     },
     ".xls": {
         "read": pd.read_excel 
     },
     ".hdf": {
         "read": pd.read_hdf 
     },
     ".sql": {
         "read": sqlread
     }
    
 }


 def read_any(file):
      _, ext = os.path.splitext(file)
      df = readict[ext]["read"](file)
      return df.head(100), df.dtypes

 file = input("enter the path to the file you want to open : ")
 read_any(file)    

Answer 1

我嘗試了以下方法，將頭部和類型放入字典中，然后在字典上使用 json.dumps() 將其轉換為 JSON object 但它給了我一個錯誤：

import os
import modin.pandas as pd
import json
from distributed import Client


def sqlread(con_w_sql, sep='#'):
    con, sql = special_path.split(sep)
    df = pd.read_sql(sql, con)
    return df.head()

readict = {
    ".csv": {
        "read": pd.read_csv
    },
    ".tsv": {
        "read": pd.read_csv 
    },
    ".json": {
        "read": pd.read_json
    },
    ".xlsx": {
        "read": pd.read_excel 
    },
    ".xml": {
        "read": pd.read_xml 
    },
    ".xls": {
        "read": pd.read_excel 
    },
    ".hdf": {
        "read": pd.read_hdf 
    },
    ".sql": {
        "read": sqlread
    }
        
}


def read_any(file):
    _, ext = os.path.splitext(file)
    df = readict[ext]["read"](file)
    head = df.head(100)
    dtype = df.dtypes
    jsonresp = {
    "head": head,
    "dtype": dtype
    }
    return json.dumps(jsonresp)

file = input("enter the path to the file you want to open : ")
read_any(file)