vikas-git

import os
from datetime import datetime
from django.conf import settings
from django.db import connection
from django.core.files.storage import FileSystemStorage


def get_dict_wise_data(columns,cursor):
	results = []
	for row in cursor.fetchall():

vikas-git

'''
    For more information visit official documents 
    https://boto3.amazonaws.com/v1/documentation/api/latest/guide/s3-examples.html
'''

import boto3
from botocore.errorfactory import ClientError
from boto3.s3.transfer import S3Transfer

vikas-git

LIST VIEW:
    from django.views.generic import ListView

    ** Simple example
        class UsersListView(ListView):
            model = User
   
   ** You can add attributes to change the default behaviour.
        class UsersListView(ListView):
            model = User

vikas-git

$(document).on('keypress', '.only-numbers', function(e){
    var keycode = (e.which) ? e.which : e.keyCode;
    if (!(keycode==8 || keycode == 46)&&(keycode < 48 || keycode > 57)){
        return false;
    }
});

vikas-git

# source: https://towardsdatascience.com/10-python-pandas-tricks-that-make-your-work-more-efficient-2e8e483808ba

pd.read_csv('file_name.csv', nrows = 5, usecols=['c1', 'c2'], dtype = {‘c1’: str, ‘c2’: int, …})
  argument
    * nrows = 5 (it will select only 5 rows from dataframe)
    * usecols (select certain columns on df creation)
    * dtype (specify col data type)
    *

vikas-git

Source Blog: https://medium.com/jbennetcodes/how-to-rewrite-your-sql-queries-in-pandas-and-more-149d341fc53e?source=search_post---------0

-> Sql queries vs pandas queries

* select Query
    -> select * from airports;
    -> airports.head()

* select query with limit
    -> select * from airports limit 3

vikas-git

# -*- coding: utf-8 -*-
"""
Created on Tuesday 23-July-2019

@author: Vikas shrivastava

For more info go to official documentation of folium https://python-visualization.github.io/folium/modules.html

"""

vikas-git

"""
Python script for batch geocoding of addresses using the Google Geocoding API.
This script allows for massive lists of addresses to be geocoded for free by pausing when the 
geocoder hits the free rate limit set by Google (2500 per day).  If you have an API key for paid
geocoding from Google, set it in the API key section.
Addresses for geocoding can be specified in a list of strings "addresses". In this script, addresses
come from a csv file with a column "Address". Adjust the code to your own requirements as needed.
After every 500 successul geocode operations, a temporary file with results is recorded in case of 
script failure / loss of connection later.
Addresses and data are held in memory, so this script may need to be adjusted to process files line

vikas-git

For Dump and Restore :
    mongodump --db=<old_db_name> --collection=<collection_name> --out=data/
    mongorestore --db=<new_db_name> --collection=<collection_name> data/<db_name>/<collection_name>.bson

Loop on mongodb query:
    db.users.find().forEach( function(myDoc) { print( "user: " + myDoc.name ); } );

vikas-git

import os
import json
import pandas as pd
import pymongo


def import_content(filepath):
    mng_client = pymongo.MongoClient('localhost', 27017)
    mng_db = mng_client['route_planning'] 
    collection_name = 'lat_long'