Leetcode Rotate Array

Given an array, rotate the array to the right by k steps, where k is non-negative.

Example 1:

Input: nums = [1,2,3,4,5,6,7], k = 3
Output: [5,6,7,1,2,3,4]
Explanation:
rotate 1 steps to the right: [7,1,2,3,4,5,6]
rotate 2 steps to the right: [6,7,1,2,3,4,5]
rotate 3 steps to the right: [5,6,7,1,2,3,4]

Example 2:

Input: nums = [-1,-100,3,99], k = 2
Output: [3,99,-1,-100]
Explanation:
rotate 1 steps to the right: [99,-1,-100,3]
rotate 2 steps to the right: [3,99,-1,-100]

Constraints:

- 1 <= nums.length <= 105
- -231 <= nums[i] <= 231 - 1
- 0 <= k <= 105

Object-oriented programming (OOP) and functional programming (FP) are two popular programming paradigms. In recent years, there has been a trend towards FP due to its benefits such as increased reliability and easier testing. In this article, I’ll show some helpful patterns for people coming from the OOP world.

Private properties

In object-oriented programming, a private property is a member variable that is only accessible within the class in which it is defined. Private properties are often used to store internal data for an object that should not be directly modified by external code. Private properties do not exist in the same way in functional programming as they do in object-oriented programming. To archive this, simply use a closure to wrap the private properties.

Here is a simple example about private properties in C#

public class Controller
{
    private int _totalCount = 0;

    public void Increase(string user, int amount)
    {
        if (user != "truongtx")
            return;

        _totalCount += amount;
    }

    public int GetTotal()
    {
        return _totalCount;
    }
}

public class Runner
{
    public void Run()
    {
        var controller = new Controller();
        controller.Increase("truongtx", 100);
        controller.Increase("otherUser", 200);
        Console.Out.WriteLine(controller.GetTotal());
    }
}

And here is how you would do it the functional way…

Leetcode: Search Insert Position

Given a sorted array of distinct integers and a target value, return the index if the target is found. If not, return the index where it would be if it were inserted in order.

You must write an algorithm with O(log n) runtime complexity.

Example 1:

Input: nums = [1,3,5,6], target = 5
Output: 2

Example 2:

Input: nums = [1,3,5,6], target = 2
Output: 1

Example 3:

Input: nums = [1,3,5,6], target = 7
Output: 4

Example 4:

Input: nums = [1,3,5,6], target = 0
Output: 0

Example 5:

Input: nums = [1], target = 0
Output: 0

Constraints:

1 <= nums.length <= 104
-104 <= nums[i] <= 104
nums contains distinct values sorted in ascending order.
-104 <= target <= 104

Leetcode: Move Zeros

Given an integer array nums, move all 0’s to the end of it while maintaining the relative order of the non-zero elements.

Note: that you must do this in-place without making a copy of the array.

Example 1:

Input: nums = [0,1,0,3,12]
Output: [1,3,12,0,0]

Example 2:

Input: nums = [0]
Output: [0]

Constraints:

1 <= nums.length <= 104
-231 <= nums[i] <= 231 - 1

Leetcode: First Bad Version

You are a product manager and currently leading a team to develop a new product. Unfortunately, the latest version of your product fails the quality check. Since each version is developed based on the previous version, all the versions after a bad version are also bad.

Suppose you have n versions [1, 2, ..., n] and you want to find out the first bad one, which causes all the following ones to be bad.

You are given an API bool isBadVersion(version) which returns whether version is bad. Implement a function to find the first bad version. You should minimize the number of calls to the API.

Example 1:

Input: n = 5, bad = 4
Output: 4
Explanation:
call isBadVersion(3) -> false
call isBadVersion(5) -> true
call isBadVersion(4) -> true
Then 4 is the first bad version.

Example 2:

Input: n = 1, bad = 1
Output: 1

Constraints:

1 <= bad <= n <= 231 - 1

Just a collection of tips to make working with Postgres (and other SQL-like databases) easier

Integration data

Usually when you build a system that integrates with other 3rd party service, you will need to store integration information related to the entity, for example the id of the entity on the 3rd party system or some of its configuration on that system. Imagine that you are building an e-commerce related product, you may want to sync the Sales order information from Shopify to do the analytics on customer behavior. The first solution you can think of is to add a column like shopify_entity_id on that table.

• What will happens if you introduce another integration later? Does the name shopify_entity_id still make sense? You may consider renaming it to external_entity_id. How do you know where it comes from? Adding another source column? How do you store extra 3rd party information about the sales order? Keep adding columns like external_something? Do those columns actually belong to the sales_order table itself?
• What will happen if an single entity exists on multiple 3rd party system? For instance, the sales order may be presented on both Shopify and on another Shipping service. How would you deal with it? Keep adding more columns? What if we introduct another integration?
  • A Json (Jsonb) column could solve the above issue but also creates a whole new problem. How about schema enforcement and constraint? How do we make sure that nobody will accidentally update it the an incorrect schema? How about null and undefined values (in case you are working with Javascript)? How about indexing the values for quick access? You can index inside the json but it just makes things more complicated due to those schema problems mentioned above.

The solution, of course, is a SQL approach: make an entity integration table (sales_order_integration in this case). It’s a 1-N relationship, 1 sales order could have 0 or multiple integrations

sales_order table

sales_order_integration table

Just a collection of tips to make working with Postgres (and other SQL-like databases) easier

Measurement Unit

Take this case for an example, you have a product table and you want to store product information like its size and weight by adding these columns to describe such properties: width, length, height and weight.

So what’s the problem with the above table? We are assuming that the size props (width, height and length) are measured in cm and the weight is measured in kg. Usually, we could put this logic in application layer to make sure we convert everything to cm and kg before inserting into the database. However, it could lead to even more problems

• What will happen if a new dev join the team? How can you make sure that person will know when to convert and when not?
• What will happen if a dev using pound join the team?
• What will happen if a dev accidentally assume the value in weight is in mg?
• Sometimes, you could do a double conversion, making thing worse.
• You need to remember adding comment to every place in your code, just to remind people which measurement unit that function is using.
• Which data type to choose? Integer, of course, is not a good choice. However, working with real, double, decimal or numeric is always harder compare to int. They could cause some problems with parsing and datatype for languages/libraries like Nodejs.

Leetcode: Squares of Sorted Array

Given an integer array nums sorted in non-decreasing order, return an array of the squares of each number sorted in non-decreasing order.

Example 1:

Input: nums = [-4,-1,0,3,10]
Output: [0,1,9,16,100]
Explanation: After squaring, the array becomes [16,1,0,9,100].
After sorting, it becomes [0,1,9,16,100].

Example 2:

Input: nums = [-7,-3,2,3,11]
Output: [4,9,9,49,121]

Constraints:

1 <= nums.length <= 104
-104 <= nums[i] <= 104
nums is sorted in non-decreasing order.

Leetcode: Power of Two

Given an integer n, return true if it is a power of two. Otherwise, return false.

An integer n is a power of two, if there exists an integer x such that n == 2^x.

Example 1:

Input: n = 1
Output: true
Explanation: 20 = 1

Example 2:

Input: n = 16
Output: true
Explanation: 24 = 16

Example 3:

Input: n = 3
Output: false

Constraints:

-231 <= n <= 231 - 1

Follow up: Could you solve it without loops/recursion?

An example about configuring PubSub BigQuery Subscription with Pulumi

• BigQuery Subscription
• Configure BigQuery Dataset and Table
• Configure BigQuery Subscription
• Application Logging
• Query data from BigQuery

BigQuery Subscription

It’s hard to view the content of the messages that were published to a topic because the application has already processed and acknowledged them before you can do anything. Usually, you have to create another test subscription for the messages to be replicated to and then pull messages from that test subscription. However, the Google PubSub UI doesn’t provide any way to pull specific message by id. The GCloud Console UI is a frustrating UI itself, slow to load and had to pull several times to find the necessary messages.

Google offers BigQuery Subscription, a solution to that issue and also to provide a long term storage for your messages so you can troubleshoot and do complex query later. In this post, I’m going to show a sample BigQuery Subscription workflow with Pulumi.

Configure BigQuery Dataset and Table

First, you need to create a BigQuery Dataset and a BigQuery Table following the schema defined here. You can do it manually on the UI or via Pulumi

BigQuery Dataset

const pubsubDatasetId = `pubsub`;

export const pubsubDataset = new gcp.bigquery.Dataset(
  `my-dataset`,
  { datasetId: pubsubDatasetId }
);

BigQuery Table (a bit messy since the schema has to be defined in JSON string)

export const messageTable = new gcp.bigquery.Table(
  `my-table`,
  {
    datasetId: pubsubDatasetId,
    tableId: `message-values`,
    // if you don't want other people to accidentally delete is, set to true
    deletionProtection: true,
    schema: `
  [
    {
      "name": "data",
      "type": "STRING",
      "mode": "NULLABLE",
      "description": "The message body"
    },
    {
      "name": "subscription_name",
      "type": "STRING",
      "mode": "NULLABLE",
      "description": ""
    },
    {
      "name": "message_id",
      "type": "STRING",
      "mode": "NULLABLE",
      "description": ""
    },
    {
      "name": "publish_time",
      "type": "TIMESTAMP",
      "mode": "NULLABLE",
      "description": ""
    },
    {
      "name": "attributes",
      "type": "STRING",
      "mode": "NULLABLE",
      "description": "Message attributes as JSON string"
    }
  ]
  `,
  },
  {
    dependsOn: [pubsubDataset],
  }
);