A minimal configuration for a dockerized kafka project

A minimal configuration for a dockerized kafka project. Usage: Run this command to build kafka and zookeeper containers, and create the network kafka-network, where your containers can access the endpoint kafka:29092. # creates the network `kafka-network` and build and # runs the containers for zookeeper and kafka docker-compose -f “docker-compose.kafka.yml” up -d –build # remove -d if you want to see logs in the same shell You can then run as many broker/consumer    

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A simple docker-compose app for orchestrating a fastapi application, a celery queue with rabbitmq(broker) and redis(backend)

A simple docker-compose app for orchestrating a fastapi application, a celery queue with rabbitmq(broker) and redis(backend) build and run containers docker-compose up -d –build This will expose fastapi application on 5000 and celery flower on 5555 swagger docs – http://localhost:5000/ redoc – http://localhost:5000/redoc celery flower – http://localhost:5555 GitHub https://github.com/karthikasasanka/fastapi-celery-redis-rabbitmq    

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You should have Docker+Docker-compose installed

Preparations You should have Docker+Docker-compose installed. All commands made from insta_api folder First launch docker-compose up –build docker-compose run django python manage.py migrate docker-compose run django python manage.py makemigrations api docker-compose run django python manage.py migrate docker-compose run django python manage.py createsuperuser To launch/exit Postgres docker exec -it pgdb psql -U postgres Django

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Simple Docker image will generate an M3U playlist optimized for use in Channels and expose them over HTTP

This simple Docker image will generate an M3U playlist optimized for use in Channels and expose them over HTTP. Channels supports custom channels by utilizing streaming sources via M3U playlists. Channels allows for additional extended metadata tags in M3U playlists that allow you to give it extra information and art to make the experience better. This project adds those extra tags to make things look great in Channels. Set Up Running the container is easy. Fire up the container as […]

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A Python library for extract property from data

Summary A Python library for extract property from data. Installation Installation: pip pip install DataProperty Installation: conda conda install -c conda-forge dataproperty Installation: apt sudo add-apt-repository ppa:thombashi/ppa sudo apt update sudo apt install python3-dataproperty Usage >>> from dataproperty import DataProperty >>> DataProperty(-1.1) data=-1.1, type=REAL_NUMBER, align=right, ascii_width=4, int_digits=1, decimal_places=1, extra_len=1 >>> from dataproperty import DataProperty >>> DataProperty(123456789) data=123456789, type=INTEGER, align=right, ascii_width=9, int_digits=9, decimal_places=0, extra_len=0 >>> from dataproperty import DataProperty >>> DataProperty(“sample string”) data=sample string, type=STRING, align=left, length=13, ascii_width=13, extra_len=0 >>> from […]

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Deploying Machine learning Application on AWS Fargate

Amazon Web Services(AWS) offers reliable, scalable, and cost-effective cloud computing services. It provides Infrastructure as a service(IaaS), Platform as a Service(PaaS), Software as a Service(SaaS) also a new model known as Function as a Service(FaaS) eg. AWS Lambda which is a serverless entity. Before going further, if you don’t have an AWS account please create one to follow along with the hands-on. Amazon Elastic Container Service(ECS) Amazon ECS is a container orchestration platform developed by Amazon, it is similar to […]

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