PYNDAS

Pembelajaran membuat Sebuah Library Python. Library ini digunakan untuk melakukan proses transformasi data nested array supaya bisa mengumpulkan semua datamenjadi satu. berharap bisa melakukan preprocessing tidak memakan waktu

Penggunaan

Instalasi

Untuk mendownload dan menginstall library ini, gunakan perintah

pip install pyndas

Pemanggilan

Pemanggilan fungsi bisa dilakukan dengan import sederhana terhadap function yang tersedia

import pyndas

Berikut secara gambaran dari nested array dari sudut pandang .json

{
    "_id": {
      "$oid": ""
    },
    "customer_info": {
      "Cust City Name": "",
      "Cust Province Name": "",
      "Cust Subdistrict Name": ""
    },
    "payment_info": {
      "Payment Method": "",
      "Payment Status": "",
      "Mode": ""
    },
    "order_info": {
      "Order ID": "",
      "User ID": "",
      "Created At": "",
      "Completed At": null,
      "Updated At": "",
      "Total Price": ,
      "Total Product Price": ,
      "Type": ""
    },
    "product_data": {
      "Product ID": null,
      "Product Price": 
    },
    "shipping_data": {
      "Ship ID": "",
      "Ship Cost": null,
      "Weight": null,
      "Courier": null,
      "Delivery Status": "",
      "Shipping Payment": "",
      "Manifested": "",
      "Manifested At": null,
      "Receipt Number": null,
      "Origin ID": "261",
      "Dest ID": "261",
      "Pickup At": null,
      "Shipping Service": null,
      "On Proses Deliver": null,
      "On Proses Return": null
    }
  }

  OR

{
  "_id": {
    "$oid": ""
  },
  "user_id": {
    "$oid": ""
  },
  "product_id": {
    "$oid": ""
  },
  "form_id": {
    "$oid": ""
  },
  "is_deleted": false,
  "order_id": ,
  "product_data": {
    "name": "",
    "slug": "",
    "code": "",
    "type": "",
    "price": ,
    "sale_price": {
      "enabled": false,
      "price": 0,
      "schedule": {
        "enabled": true,
        "since": "",
        "until": ""
      }
    },
    "cogs": ,
    "variations": {
      "attributes": [],
      "prices": [],
      "multiple_variations": {
        "enabled": false
      }
    },
    "wholesale": [],
    "picture": ""
  },
  "form_data": {
    "name": ""
  },
  "customer_data": {
    "name": "",
    "phone": "",
    "email": "",
    "notes": "",
    "address": ""
  },
  "product_price": ,
  "product_weight": ,
  "shipping": {
    "courier": "",
    "service": "",
    "cost": 0,
    "cod": false,
    "cod_cost": 0,
    "cod_include_shipping": true,
    "cod_fee_type": "",
    "cod_min": ,
    "cod_max": ,
    "cod_percentage": ,
    "markup": 0,
    "original_cost": 0,
    "origin_id": ,
    "weight": ,
    "mode": ""
  },
  "bump": {
    "checked": false,
    "name": "",
    "price": 0,
    "weight": 1
  },
  "coupon": {
    "id": "",
    "code": "",
    "discount": 0,
    "discount_for": ""
  },
  "total_product_price": ,
  "total_price": ,
  "unique_code_price": {
    "type": "",
    "unique_code": 0
  },
  "cogs": ,
  "progress": {
    "welcome": false,
    "follow_up_1": false,
    "follow_up_2": false,
    "follow_up_3": false,
    "follow_up_4": false,
    "processing": false,
    "closing": false,
    "cancelled": false,
    "up_selling": false
  },
  "progress_sms": {
    "welcome": false,
    "follow_up_1": false,
    "follow_up_2": false,
    "follow_up_3": false,
    "follow_up_4": false,
    "processing": false,
    "closing": false,
    "cancelled": false,
    "up_selling": false
  },
  "payment": {
    "method": "",
    "data": [],
    "channels": [],
    "status": ""
  },
  "status": "",
  "is_printed": false,
  "meta": {
    "url": "",
    "fbc": "",
    "fbp": "",
    "ip": "",
    "os": "",
    "browser": "",
    "location": "",
    "network": "",
    "device_type": "",
    "device_model": "",
    "user_agent": "",
    "embed": false,
    "referrer": "",
    "uuid": ""
  },
  "belongs_to": [
    {
      "$oid": ""
    }
  ],
  "type": "",
  "hash": "",
  "other_cost": 0,
  "dropship": {
    "enabled": false,
    "name": "",
    "phone": ""
  },
  "is_stock_reduced": false,
  "customer_id": {
    "$oid": ""
  },
  "updated_at": {
    "$date": ""
  },
  "created_at": {
    "$date": ""
  }
}

Harapan dari library ini untuk melakukan transformasi data dengan waktu yang singkat

Fungsi Tersedia

1. RemoveRedudancy-data
2. TransformData-nested_array

Changelog:

v0.0.3

library masih permulaan,

1. percobaan kalkulasi dari proses melakukan transformasi data

Stats

License

Menggunakan MIT License