Ilan Toren ilantoren

## SequenceSum
package sequence

import scala.annotation.tailrec
import scala.util.Random

/**
 * Created by Owner on 10/21/14.
 *
 *    Problem:  In an array of uniformly distributed digits from 0-9 find two sequences such that
 *    the first sequence and second sequence add to the same sum and that sequence 1 and sequence 2 are

## dclab_report.xsl
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<xsl:stylesheet xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0">
	<xsl:output method="xml" indent="yes" encoding="UTF-8" />

	<xsl:template match="/data">

		<xsl:element name="html">
			<head>
				<title>OCLC matching to CARS files</title>
				<style type="text/css">

## map-region.R
library( reticulate)
library(ggplot2)
library( dplyr )

# As in the call-python.R script  the structure remains unchanged
# A) load the python file
# B) use the function to return a data.frame
#    i)  name is the neighborhood name
#    ii) restaurants
#    iii) region_lng and region_at

## map-region.py
from pymongo import MongoClient
import pandas as pd

def get_data( neighborhood ):
   data = {}
   client = MongoClient('mongodb+srv://restaurantAppUser:restaurantAppPwd@mflix.beal2.mongodb.net/test?authSource=admin&replicaSet=atlas-a7tqy4-shard-0&readPreference=primary&appname=MongoDB%20Compass&ssl=true')
   restaurants = client['sample_restaurants']['restaurants']
#  Sometimes all the work is in getting your data into the format your program requires
#  In this example there are two queries: a) get the region coordinates for the neighborhood selected, and b) use that set of coordinates to
#  find the restaurants within that region.

## restaurantsByName.js
/*
 *  restaurantsByNeighborhood
 *  @param  string neighborhood
 *  @returns object
 */

exports = function(neighborhood){

  // A simple function to create an average coordinate
  //  for centering the map.

## realm-function.js
/*
 *  restaurantsByNeighborhood
 *  @param  string neighborhood
 *  @returns object
 */

exports = function(neighborhood){

  // A simple function to create an average coordinate
  //  for centering the map.

## realm_neighborhood.dart
import 'dart:convert';

import 'package:flutter/services.dart' show rootBundle;
import 'package:google_maps_flutter/google_maps_flutter.dart';
import 'package:http/http.dart' as http;
import 'package:json_annotation/json_annotation.dart';
import 'package:logging/logging.dart';
import 'package:flutter_dotenv/flutter_dotenv.dart';

// RUN THIS COMMAND TO CREATE the g.dart files

## mongodb_aggregate.rs
#[derive(Serialize,Deserialize, Debug)]
 pub struct Restaurant {
    cuisine: String,
    borough: String,
    name: String,
    address: Address
}
#[derive(Serialize, Deserialize, Debug)]
pub struct Address {
    building: String,

## mongo_requests_a.rs
/**
   For a web server  objects are sent serialized into json, but a client
   could create an object from the http call response
**/
#[derive(Serialize, Deserialize, Debug, Clone)]
#[serde(crate = "rocket::serde")]
pub struct Restaurant {
    cuisine: String,
    borough: String,
    name: String,

## mongo_requests_c.rs
/** This is not compiler ready
   from cargo.toml:
   dependencies.mongodb]
    version = "2.0.0"
    default-features = false
    features = ["sync"]
    **/

use mongodb::{bson::Bson, bson::doc, bson::Document, options::ClientOptions, options::FindOptions, sync::Client, sync::Collection};
use mongodb::options::AggregateOptions;
	package sequence

	import scala.annotation.tailrec
	import scala.util.Random

	/**
	* Created by Owner on 10/21/14.
	*
	* Problem: In an array of uniformly distributed digits from 0-9 find two sequences such that
	* the first sequence and second sequence add to the same sum and that sequence 1 and sequence 2 are
	<?xml version="1.0" encoding="UTF-8" standalone="no"?>
	<xsl:stylesheet xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0">
	<xsl:output method="xml" indent="yes" encoding="UTF-8" />

	<xsl:template match="/data">

	<xsl:element name="html">
	<head>
	<title>OCLC matching to CARS files</title>
	<style type="text/css">
	library( reticulate)
	library(ggplot2)
	library( dplyr )

	# As in the call-python.R script the structure remains unchanged
	# A) load the python file
	# B) use the function to return a data.frame
	# i) name is the neighborhood name
	# ii) restaurants
	# iii) region_lng and region_at
	from pymongo import MongoClient
	import pandas as pd

	def get_data( neighborhood ):
	data = {}
	client = MongoClient('mongodb+srv://restaurantAppUser:restaurantAppPwd@mflix.beal2.mongodb.net/test?authSource=admin&replicaSet=atlas-a7tqy4-shard-0&readPreference=primary&appname=MongoDB%20Compass&ssl=true')
	restaurants = client['sample_restaurants']['restaurants']
	# Sometimes all the work is in getting your data into the format your program requires
	# In this example there are two queries: a) get the region coordinates for the neighborhood selected, and b) use that set of coordinates to
	# find the restaurants within that region.
	/*
	* restaurantsByNeighborhood
	* @param string neighborhood
	* @returns object
	*/

	exports = function(neighborhood){

	// A simple function to create an average coordinate
	// for centering the map.
	import 'dart:convert';

	import 'package:flutter/services.dart' show rootBundle;
	import 'package:google_maps_flutter/google_maps_flutter.dart';
	import 'package:http/http.dart' as http;
	import 'package:json_annotation/json_annotation.dart';
	import 'package:logging/logging.dart';
	import 'package:flutter_dotenv/flutter_dotenv.dart';

	// RUN THIS COMMAND TO CREATE the g.dart files
	#[derive(Serialize,Deserialize, Debug)]
	pub struct Restaurant {
	cuisine: String,
	borough: String,
	name: String,
	address: Address
	}
	#[derive(Serialize, Deserialize, Debug)]
	pub struct Address {
	building: String,
	/**
	For a web server objects are sent serialized into json, but a client
	could create an object from the http call response
	**/
	#[derive(Serialize, Deserialize, Debug, Clone)]
	#[serde(crate = "rocket::serde")]
	pub struct Restaurant {
	cuisine: String,
	borough: String,
	name: String,
	/** This is not compiler ready
	from cargo.toml:
	dependencies.mongodb]
	version = "2.0.0"
	default-features = false
	features = ["sync"]
	**/

	use mongodb::{bson::Bson, bson::doc, bson::Document, options::ClientOptions, options::FindOptions, sync::Client, sync::Collection};
	use mongodb::options::AggregateOptions;