Python Convert Dictionary To CSV

I am trying to convert dictionary to CSV so that it is readable (in their respective key). import csv import json from urllib.request import urlopen x =0 id_num = [848649491, 88356

Solution 1:

Using DictWriter from the csv module

Demo:

import csv

data_list ={'x':{'title':'productName()','price':'price()','description':'description()','preorder':'checkPreorder()',
             'estimate delivery':'estimateDelivery()','variation': 'variation()', 'category':'categories()',
             'brand':'brand()','image':'image_link()'}}

with open(filename, "w") as infile:
    writer = csv.DictWriter(infile, fieldnames=data_list["x"].keys())
    writer.writeheader()
    writer.writerow(data_list["x"])

Solution 2:

I think, maybe you just want to merge some cells like excel do? If yes, I think this is not possible in csv, because csv format does not contain cell style information like excel. Some possible solutions:

1. use openpyxl to generate a excel file instead of csv, then you can merge cells with "worksheet.merge_cells()" function.

2. do not try to merge cells, just keep title, price and other fields for each line, the data format should be like:

   first line: {'title':'test_title', 'price': 22, 'image': 'image_link_1'}

   second line: {'title':'test_title', 'price': 22, 'image': 'image_link_2'}

3. do not try to merge cells, but set the title, price and other fields to a blank string, so it will not show in your csv file.

4. use line break to control the format, that will merge multi lines with same title into single line.

hope that helps.

Solution 3:

If I were you, I would have done this a bit differently. I do not like that you are calling so many functions while this website offers a beautiful JSON response back :) More over, I will use pandas library so that I have total control over my data. I am not a CSV lover. This is a silly prototype:

import requests
import pandas as pd

# Create our dictionary with our items lists

data_list = {'title':[],'price':[],'description':[],'preorder':[],
             'estimate delivery':[],'variation': [], 'categories':[],
             'brand':[],'image':[]}

# API url
url ='https://shopee.com.my/api/v2/item/get' 

id_nums = [848649491, 883560475, 431495539, 883481767, 851341658,
          42842466, 173114302, 900616370, 1042383097, 859872672]
shop_id = 1883827

# Loop throw id_nums and return the goodies
for id_num in id_nums:
    params = {
         'itemid': id_num, # take values from id_nums 
        'shopid':shop_id}
    r = requests.get(url, params=params)

    # Check if we got something :)
    if r.ok:
        data_json = r.json()

        # This web site returns a beautiful JSON we can slice :)

        product = data_json['item']

        # Lets populate our data_list with the items we got. We could simply
        # creating one function to do this, but for now this will do
        data_list['title'].append(product['name'])
        data_list['price'].append(product['price'])
        data_list['description'].append(product['description'])
        data_list['preorder'].append(product['is_pre_order'])
        data_list['estimate delivery'].append(product['estimated_days'])
        data_list['variation'].append(product['tier_variations'])
        data_list['categories'].append([product['categories'][i]['display_name'] for i, _ in enumerate(product['categories'])])
        data_list['brand'].append(product['brand'])
        data_list['image'].append(product['image'])

    else:
            # Do something if we hit connection error or something.
            # may be retry or ignore
            pass



# Putting dictionary to a list and ordering :)
df = pd.DataFrame(data_list)
df = df[['title','price','description','preorder','estimate delivery',
         'variation', 'categories','brand','image']]

# df.to ...? There are dozen of different ways to store your data 
# that are far better than CSV, e.g. MongoDB, HD5 or compressed pickle

df.to_csv('my_data.csv', sep = ';', encoding='utf-8', index=False)