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Understanding Type Checking

A few examples of types in the context of programming language can be integer, float, character, string, array, etc.  When a program executes then data flow between instructions and values of specific types are assigned to a variable after some operation. It's important for the system to verify if the correct types are used as operands in operations. For e.g. In a sum operation, the expectation for operands to be of numeric type. The program's execution should fail in the case there is inconsistency. We can classify programming languages into two categories based as per their ability to cater to type safety: Dynamically Typed Language Statically Typed Language
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Working with Twilio

Email channel support in Twilio As per Twilio documentation , we can bring email as a channel and leverage Task Routing capabilities easily as long as we can create a task and programmatically interact with the email service. They recommended an email service provider with REST API (like SendGrid ) capabilities because of ease of use. However, we can use any Email provider for this purpose. Gmail-based email channel support Let's assume our support email is hosted on Gmail and we have a Flex-based contact support system in place where Agents handle chat and voice-based support. Now we want to extend our chat interface to handle email-based support conversations.  We will build a worker service using Gmail API that will listen to new emails. Once a new email arrives, we will use Twilio SDK to create a new channel and task. Once an agent accepts the task and they can respond to the customer's queries. Agent response will be further emailed to the customer using Gmail API.

Useful SFTP terminal commands

First Step - Connect to a remote computer sftp -i ~/.ssh/LightsailDefaultKey-ap-south-1.pem ubuntu@ Similar to ssh command. Output: Connected to sftp> Remote and Local computer commands When we relay basic terminal commands at sftp> like 'pwd , ls , cd , and it is executed at the remote computer. Basic terminal commands above when prefixed with l like lpwd , lls , lcd and etc. it is executed at a local computer. For e.g. List all files in the present working directory at the remote computer: sftp> ls List all files in the present working directory at the local computer: sftp> lls Sending a local computer file to present the working directory of a remote computer sftp> put /Users/mj/Downloads/test.png Output Uploading /Users/mj/Downloads/test.png to /home/ubuntu/test.png /Users/mj/Downloads/tech-mrit-prod.ovpn 100% 13KB 382.9KB/s 00:00 References How To Use SFTP to Securely Transfer Files with a Re

FastAPI first shot

Setup on my Mac (Macbook Pro 15 inch Retina, Mid 2014) Prerequisite Python 3.6+ (I used 3.7.x. I recently reinstalled OS after cleaning up disk, where stock Python 2.7 was available. I installed Pyenv and then used it to install 3.7.x). I already had a git repo initialized at Github for this project. I checked that out. I use this approach to keep all the source code safe or at a specific place 😀. I set the Python version in .python-version file. I also initialize the virtual environment using pyenv in venv folder. I started the virtual environment. FastAPI specific dependencies setup Now I started with basic pip commands to install dependency for the project. I saved dependencies in requirements.txt  the file. Minimal viable code to spin an API Server FastAPI is as cool as NodeJS or Go Lang (?) to demonstrate the ability to spin an API endpoint up and running in no time. I had the same feeling for the Flask too, which was also super cool. app/ from typing i

Setting Clickhouse column data warehouse at Google Cloud Compute Engine VM

I didn't have a Google Cloud account associated with my email, so I signed up for one. It needs a valid Credit Card and mobile number to check if you are human. On successful sign up I get 300$ to spend within 3 months. Creating a free forever Google Cloud Compute Engine VM As per Google Cloud documentation you can have 1 non-preemptible e2-micro VM instance (1GB 2vCPU, 30GB Disk, etc.) per month free forever in some regions with some restrictions. I wanted the following stuff in my VM before I can install Clickhouse on to that: Ubuntu 20.x LTS SSH access from my machine Enabling SSH-based access to Google Compute Engine VM Step 1 Created an ssh private and public key on my mac using the following command ssh-keygen -t rsa -f ~/.ssh/gcloud-ssh-key -C mrityunjay -b 2048 Step 2 Copied the public key from the console using the following command: cat ~/.ssh/ output ssh-rsa <Gibrish :)> mrityunjay Step 3 I went to Google Cloud Console > Co

Initial research on FastAPI

I already used Flask in the past. I know about the extensive usage of DJango Framework in the Python community. Both are decent frameworks for web and API development in the Python world. As usual, at the beginning of a new project, I was unconsciously checking out the health and relevance of my technology selection. I came across FastAPI framework and noticed it because of the following facts: Selected in InfoWorld Best Open Source Software Award 2021 . Simplicity of Flask. Faster than Flask as it uses ASGI (Asynchronous Server Gateway Interface) . Adaptation among large product companies like Uber , Netflix and others. More than 38K stars on Github as on 17 Nov 2021. Remember Flask has more than 55K stars on Github. FastAPI is catching up fast. More to come.

Extend and reuse an existing AirByte destination connector

AirByte is an open-source ELT (Extract, Load, and Transformation) application. It heavily uses containerization for the deployment of its various components. On the local machine, we need docker to run it. AirByte has an impressive list of source and destination connectors available. One of my use case data destinations is the  ClickHouse data warehouse and its destination connector is not yet (2021-12-08) available. As per the documentation, It seems that creating a destination connector is a non-trivial job. It's a great idea to build an open-source ClickHouse destination connector. However, I tried avoiding the temptation to create one because of the required effort. AirByte has a  MySql destination connector available. ClickHouse provides a MySQL connector for access from any MySQL client. We need to configure Clickhouse to give support for the MySQL connector. Accessing ClickHouse from AirByte using its MySQL destination connector looks promising. However, when I tri