Category Archives: Programming

How to add Stripe Payment to Spring Boot Application

In this post, we will show how to add Stripe Payment to Spring boot application. Most enterprise applications offer a way where customer can pay online. Online payments are the backbone of internet world in current times. If you ever built an application for a customer, previously there were physical cheques OR credit card payments. With the applications becoming more web based, it has become utmost necessary to integrate your application with some kind of payment gateway. Payment gateway will handle all tax and financial regulation related complications which the application doesn’t have to deal with.

The functionality is part of the application Social KPI that I am building.

What are we trying to achieve here?

Story for Stripe Payment

An administrator comes on the billing page and pays the bill for that month. Once the bill is paid, the billing page will show that the bill has been paid for that month. So the option to enter credit card details will only be shown if the bill has not been paid.

As part of payment service, we will be using Stripe . Once the user enters credit card details and she can enter Pay Now button which will contact Stripe API to get token, this token will be used to create a charge on Stripe and Stripe will respond with success or failure of the charge.

Flow

To summarize the flow

  1. User clicks Pay Now to pay the charges
  2. Frontend Stripe javascript API contacts Stripe to create token using enter billing details
  3. Frontend Stripe javascript API sends this token to server to handle billing on server side
  4. On server side, controller uses the token and amount to create charge for that customer for application usage.
  5. For paid bills, the status is marked as paid for the customer for that month.

Frontend Implementation

To use Stripe APIs, we must first create account on stripe.com as a developer and get the keys. Good thing is Stripe offers API keys for test and live environments. For this post and demo, we will be using test keys only. Once we have API keys, we will use them in our frontend and backend implementation.

In following screenshot, you will see how the billing page will look:

Billing Page

Once the user clicks on Pay Now, the javascript function from Stripe for mounting card and creating token will be called. Once the token is available, the same function will pass it server by submitting a POST request. Sample of this code will look like below:


            var form = document.getElementById('payment-form');
            form.addEventListener('submit',function(event){
                event.preventDefault();
                payTheBill();
            });

            function payTheBill(){
                stripe.createToken(card).then(function(result){
                    if(result.error){
                        var errorElement = document.getElementById('card-errors');
                        errorElement.textContent = result.error.message;
                    } else {
                        var token = result.token.id;
                        var email = $('#email').val();
                        var companyid = $('#companyid').val();
                        var amount = $('#amount').val();
                        $.get(
                            "/createcharge",
                            {email:email,token:token,companyid : companyid, amount:amount},
                            function(data){
                                alert(data.details);
                            },'json');
                    }
                })
            }

Backend Implementation

As part of the application Social KPI, I have a database table billing to track customer’s paid bills. The PaymentController is a REST controller which will have a POST request mapping for creating a charge and storing in the database table and mark the bill as paid. As shown above in javascript code, once the token is available it will be sent to server side to controller to handle the charge. This will be a REST call, so the controller is also RestController.


 @RequestMapping(value="/createcharge",method = RequestMethod.GET)
    @ResponseBody
    public Response createCharge(String email, String token, String companyid, double amount)
    {
        LOGGER.info("Enter >> createCharge() ");

        if(token == null)
        {
            throw new RuntimeException("Can't create a charge, try again");
        }

        Billing billing = billingRepository.findByCompanyId(Integer.parseInt(companyid));

        double billedAmount = amount * 100;

        String chargeId = paymentService.createCharge(email,token,billedAmount);

        if(chargeId != null && !chargeId.equals(""))
        {
            LOGGER.info("bill has been charged on consumer's account");
            billing.setStatus(true);
            billing.setPaiddate(new Date());
            billingRepository.save(billing);
        }

        LOGGER.info("Exit << createCharge() ");
        return new Response(true,"Congratulations, your card has been charged, chargeId= "+chargeId);
    }

As shown above, Service called paymentService will create a charge on Stripe. To implement paymentService, you will need to include stripe java library in your implementation.

compile('com.stripe:stripe-java:10.5.0')

So the service class PaymentService will look like below to create charge:


    public String createCharge(String email, String token, double amount)
    {
        String id = null;
        try
        {
            Stripe.apiKey = API_SECRET_KEY;
            Map chargeParams = new HashMap<>();
            chargeParams.put("amount", (int)(amount*100));
            chargeParams.put("currency", "USD");
            chargeParams.put("description", "Charge for " + email);
            chargeParams.put("source", token);
            Charge charge = Charge.create(chargeParams);
            id = charge.getId();
        }
        catch(StripeException e)
        {
            throw new RuntimeException("Unable to process the charge", e);
        }
        return id;
    }

Once the bill is paid, administrator will see this as the bill paid for that month.

Conclusion

In this post, we showed how to integrate Spring boot application with Stripe payment gateway.

References

  1. Stripe API reference - https://stripe.com/docs/api/charges
  2. Integrate Stripe with Spring boot - Stripe with Spring boot

Metrics collection with Micrometer and Prometheus

In my previous post here, I showed how to configure Micrometer and Prometheus to collect microservice performance metrics data. In this post, I will show how we can collect Spring Boot Actuator metrics data and transfer to Prometheus UI, and view it using dashboards.

Spring Boot offers a lot of great features with Actuator. With enterprise applications constantly looking for ways to monitor the application, these metrics become even more important.

Configure Prometheus using the docker

Firstly, we will configure the Prometheus. Depending on the environment you are using, start the docker terminal. Use the following command to download Prometheus

docker pull prom/prometheus

We will configure Prometheus to scrape metrics from our application’s actuator endpoint. As shown in the previous post here, spring boot actuator endpoint is running on http://localhost:8080/actuator/prometheus

We will add Prometheus configuration in prometheus.yml file as below:

# my global config
global:
  scrape_interval:     5s # Set the scrape interval to every 5 seconds. Default is every 1 minute.
  evaluation_interval: 5s # Evaluate rules every 5 seconds. The default is every 1 minute.
  # scrape_timeout is set to the global default (10s).
 
# Alertmanager configuration
alerting:
  alertmanagers:
  - static_configs:
    - targets:
      # - alertmanager:9093
 
# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
  # - "first_rules.yml"
  # - "second_rules.yml"
 
# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'prometheus'
 
    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.
 
    static_configs:
    - targets: ['localhost:9090']
 
  - job_name: 'spring-actuator'
    metrics_path: '/actuator/prometheus'
    scrape_interval: 5s
    static_configs:
    - targets: ['IPADDRESS_OF_HOST:8080']

Few things to notice from this configuration file. scrape_interval is 5s. In scrape_configs , job name for our Spring Actuator endpoint is spring-actuator and the endpoint is running at /actuator/prometheus. The targets section shows where our application is running.  Save this file at a location that we can use to mount while running the docker container.

To Run the Prometheus using docker, use the following command:

docker run --name prometheus -d --mount type=bind,source=//c/Users/sandbox/prometheus.yml,destination=/etc/prometheus/prometheus.yml -p 9090:9090 prom/prometheus

This will start the Prometheus server at 9090 and it can be accessed at 9090.  Meanwhile, we can check the Prometheus dashboard. Let’s get the docker IP first by using the following command

docker-machine ip

Now check the Prometheus dashboard at http://docker-ip:9090 , it will look like below:

Spring Boot Actuator Metrics in Prometheus Dashboard

Conclusion

In this post, we showed how to run a Prometheus out of docker container and scrape metrics from Spring boot application.

References

  1. Spring Boot and Prometheus – Spring boot actuator and Prometheus
  2. Monitoring your microservices – Monitoring your microservices

 

 

Introduction to Graphs

In my previous article, I talked about hashtables. I will discuss one more data structure in this post and it is probably one of the most important data structures of all and that is Graphs.

Clearly, our current web technologies are heavily reliant on graphs. Google, Facebook, or LinkedIn or any social media platform which includes users use graphs as a data structure. So, graphs are the most common data structure to solve problems related to finding the distance between two nodes OR the shortest path from place A to place B.

Therefore, when it comes to the social network, we are accustomed to six degrees of freedom, in such cases, we can use graphs to find how many degrees will it take to connect two nodes on the social network. In networking, most use graphs to find the fastest way to deliver the response.

How do you explain Graphs to 5-year-olds?

The easiest example, one can give to a kid to explain Graphs, is to look at City A and City B on a map. Now use the road that connects to those two cities.

City A – has bananas, and oranges, city B – has apples, and city C – has watermelons.

Now on the map, when we travel from City A to City B, what possible route we can take and what information we can exchange. City A and City B can transfer apples, bananas, oranges to each other. Once City B gets bananas and oranges, it can transfer that to other neighboring cities.

In short, we are connecting nodes (vertices) of cities A and B through a road (edge) while exchanging the products these two cities are known for.

Graphs Data Structure

In this post, we will discuss graphs from the Java perspective. Graphs allow representing real-life relationships between different types of data. There are two important aspects to graph:

  • Vertices (Nodes) – Nodes represent the points of a graph where the graph is connected. Node store the data or data points. 
  • Edges – Edges represent the relationship between different nodes. Edges can have weight or cost.

However, there is no starting node or ending node in the graph. A graph can be cyclical or acyclical. In conclusion, edges can be directed or undirected which give birth to graphs as directed or undirected. 

For instance, edges are generally represented in the form of a set of ordered pairs as in (x,y) – there is an edge from node x to node y. So (x,y) can be different from (y,x), especially in the directed graph.

Representations of Graphs

A. Adjacency Matrix –

This is a 2 dimensional array of size n*n where n is number of nodes in the graph. adj[][] is the usual way of representing this matrix.  So if adj[i][j] = 1, it represents an edge between node i and node j. Adjacency matrix for an undirected graph is symmetrical. Now if I have to represent the graph shown above in the figure, I will represent it like below:

                A               B             C        G         E
               A                 0               1             0         1         0
               B                1              0             1         0         1
               C                0              1             0         0         1
               G                1              0             0         0         1
               E                0              1             1         1         0

 B. Adjacency List –

Similarly, an array of lists is used. The size of the array is equal to the number of nodes in the graph. So arr[i] will indicate the list of vertices adjacent to node i.

 

Operations on the Graphs

There are common operations that we will use often. Likewise, graph as a data structure offers the following operations:

Additions

addNode  – Add a node in the existing graph

addEdge – Add an edge in the existing graph between two nodes

Removal

removeNode – Remove a node from the existing graph

removeEdge – Remove an edge between two nodes from the graph

Search

contains– find if the graph contains the given node

hasEdge – find if there is an edge between given two nodes

 

Time and Space Complexity of operations on Graphs

Above all, a post would be incomplete if I didn’t talk about complexity about operations on the graph data structure. Basically, this really depends on what representations you use for the graph. With adjacency matrix, addition and removal operations are O(1) operations. While search operations like contains and hasEdge are also O(1) operations. In addition, the space complexity for the adjacency matrix is O(n*n).

While with adjacency list, additions are O(1) and removal of a node is O(n) operation, removal of an edge is O(1) . Therefore, search operations are equally O(1)

Conclusion

In conclusion, I showed the basics of the graph as a data structure. The graph is a data structure that contains nodes and edges. Also, It has operations like additions, removal, and search. In future posts, I will talk about implementing Depth First Search and Breadth First Search in the graph. After that, we will solve some real problems using this data structure. Above all, Graph is an important data structure.

References

  1. Introduction to Graphs – Graphs
  2. Graph as data structure – Graph as data structure

Hash Tables

What are Hash Tables?

Hash Tables are data structures used to store the data in key/value pair format. It uses a hash function to compute an index which will be used in an array to store the element at that index.

What is key/value pair though?

Alright, I will be digging in fundamentals here. Let’s take an example of database table. To retrieve a particular value from database table, you sometimes need to know a primary key or a unique value from the row of database table. Then you query on database table based on that unique value or primary key to get that entire row or that particular value you are looking for me.

Still complicated?

Let’s take an example of classroom. You are in 2nd grade class and when a teacher does roll call, she doesn’t necessarily call your name, she calls the number assigned to you. So example

1 – John Doe

2 – Jill Doe

3 – Mark Ranson

So the roll number assigned to the student becomes a key to identify that student.

Similarly in programming languages (Java in this case), we use a data structure called Hash Tables.

Hash function takes an input, hashes that input to generate an index which we use as a key to store the value in an array. Why so complexity? Why not we go in sequential order?

There are many reasons, first hashing gives security. If somebody exploits sequential order, it is easy to find next element. But hashing allows us to randomly store the data. But the most important, the average time required to search for an element in a hash table is O(1).

Now from the basics, we can say that hash tables have two components – one an array to store the value and a function to calculate the index of the array.

So what is a hash function and how do we write this hash function?

A hash function is a function that takes a data of any size and transforms that data into a fixed size data. In short a hash function will take an input x and transform that into output y. Now, this looks simple, but the question arises what if there are multiple inputs that can be transformed into y. Then we will have a problem. This is known as Collision.

Important characteristics of this hash function

  1. It should avoid collision.
  2. It should easily calculate the keys.
  3. It should uniformly distribute the keys.

How to avoid collision?

There are a couple of techniques.

One technique is open addressing. In Open Addressing, store all elements in hash table itself. At any point, the size of the hash table must be greater than or equal to that of the number of keys. This is useful in the scenario of fixed size tables. During insertion, if you found the occupied slot in the hash table, you go for the next slot. It will continue until it finds an unoccupied slot. Since this is a linear process, open addressing is also linear probing. The disadvantage of open addressing is insertion and search operation becomes linear.

The second technique is Separate Chaining. In this, make each cell of a hash table point to a linked list of records. So if a hash function returns a duplicate key, the value will be placed in a linked list which will be pointed by earlier value stored at that key. The next value will be pointed by earlier linked list element. To make this simpler – let’s assume we have a has function key % 3 and so for 9, it will return 0. For 10, it will return 1. For 16, it will return 1 again. Now when we will store a value (for 10), we will store at index 1 and the next value (for 16), will be in a linked list pointed by the value stored at 1.

When do we use hash tables?

  1. Hash tables offer fast insertion
  2. Hash tables allow fast deletion
  3. Hash tables can help in searching an element

References

  1. Hash tables as data structures
  2. Hash Tables

 

Object Oriented Design Principles

A good software developer builds a software using right design principles. If you learn design patterns, object oriented concepts, but don’t learn principles, then you will do a disservice to yourself as a developer. Without design principles, you will build a software with no heart, no functionality to serve. I hope you don’t want to do that.

In this post, I will try to explain some design principles that I have come across or learned through my experience. If you do not understand any of these principles, please comment on the post and I will answer your questions.

Programming for interface and not for implementation

While building design, you can think how you can reuse or design your code in a way where you can extend it in future if needed. OR you have to minimal changes if you have to change. One design principle that can help in such cases is to Program interfaces instead of implementation directly.

For variables, method return types or argument type of methods – use interfaces. This will help to implement interfaces as you want.

Single Responsibility Principle

A class, a method should always implement single responsibility or single functionality. Putting more than one functionality in an object can disturb the functionality in future if there are any changes. To reduce future changes, always create implement your code with single responsibility principle.

Liskov Substitution Principle

This principle states that objects should be replaceable with instances of their subclasses without altering the correctness of the program.

To understand this, let’s look at a simple object and subclasses of that object Bird

public class Bird
{
    void fly()
    {
       // Fly function for bird
    }
}

public class Parrot extends Bird
{
    @Override
    void fly()
    {

    }
}

public class Ostrich extends Bird
{
   // can't implement fly since Ostrich doesn't fly
}

Parrot as a bird can fly, but Ostrich as a bird can’t fly. So if we end up using such an implementation, it will violate the principle of Liskov Substitution.

Open Closed Principle

Open Closed Principle makes that objects,methods should be open for extensions, but closed for modification. Many times, requirements are not clear at the beginning of design and implementation, we must use open closed principle to implement initial design and slowly if requirements change, it becomes easy to add them in design.

Interface Segregation Principle

This principle requires that client should not be forced to implement interface if it doesn’t use that. In another words, make sure your interfaces are concise and implement single functionality only. If interface has more than one functionality, it can be unnecessary for client to implement all the functionalities when it only needs one.

Delegation Principle

Don’t do all the stuff by yourself, but delegate the functionalities to respective classes. Delegation is kind of relationship between objects where an object can forward certain functions to do work to other objects (provided those objects implement those functions).

Dependency Inversion Principle

This principle is type of decoupling behavior for software modules. High level modules should not depend on low level modules. Generally while designing high level classes will depend on low level classes. But if you have to change low level classes after every design revision, it will warrant to be a bad design. To avoid such a problem, we create an abstraction layer. Low level classes will be created based on abstraction layer.

When this principle is used, high level classes use interfaces as an abstraction layer to work with low level classes, instead of working directly with low level classes.

References

  1. Ten object oriented design principles – SOLID Principles
  2. Design Principles – design principles