quix-streams
quix-samples
quix-streams | quix-samples | |
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25 | 3 | |
796 | 38 | |
43.4% | - | |
9.0 | 8.1 | |
about 11 hours ago | 7 days ago | |
Python | C# | |
Apache License 2.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
quix-streams
- Show HN: Streaming DataFrames–a Pandas-like syntax for real-time data
- FLaNK AI-April 22, 2024
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Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
Airflow for Streaming
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Apache Pulsar VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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redpanda VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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ApacheKafka VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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flink-statefun VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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Apache Spark VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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beam VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
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debezium VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
Debezium is a change data capture framework for streaming. Connect it to your databases to detect changes and produce those change events to Kafka. Quix Streams is a Python stream processing library for ML and AI applications. It builds on the Confluent Python library to add a state store with RocksDB and adds a Streaming DataFrames API with declarative operations like Windows. It is designed for analytics and data engineering workloads. Use it together with Debezium to process your CDC data in real-time.
quix-samples
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DAG orchestration for streaming data?
Full disclosure: I work at Quix. I don't always make this recommendation but we could be a really good fit in this case. We enable any number of transformation steps and destinations (outputs/sinks) so you could chain as many as you'd like and be 100% transparent because it's all in code (includes DAG visualiser). We have an open source client library and code samples, we work really well with telemetry/time-series/IoT/sensor data (the founders worked in the McLaren Racing F1 team), we have a Kinesis connector and recently collaborated with AWS to provide a solution for Brompton Bicycle (using Kinesis Firehose). We have a free tier and I'm happy to help you out if you reach limits or have any questions.
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Questioning my approach with Kafka!
The point is that they host Kafka for you (quix.io), and have all these connectors and templates and whatnot including one that will connect Kafka to Slack, so you'll still get your Slack notifications. It's all Python so you don't have to write any Java if that's not your skillset. Here are links to code that might help: * Stream from file: https://github.com/quixio/quix-library/tree/main/python/sources/Real-Time-From-File (e.g. log file) * Notify in Slack: https://github.com/quixio/quix-library/tree/main/python/destinations/slack-notifications * Write to Postgres DB: https://github.com/quixio/quix-library/tree/main/python/destinations/Postgres
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Show HN: An open-source library for telemetry streaming started at Formula 1
All the samples and connectors are also open source in this repo https://github.com/quixio/quix-library
This project has a stream from CSV example
What are some alternatives?
confluent-kafka-python - Confluent's Kafka Python Client
aiokafka - asyncio client for kafka
qr-code - A no-framework, no-dependencies, customizable, animate-able, SVG-based <qr-code> HTML element.
bytewax - Python Stream Processing
csv-import - The open-source CSV importer, maintained by @tableflowhq
ml-runtimes
kafka-python - Python client for Apache Kafka
flasho - Open source customer notifications in less than 5 minutes
DeepStream-dGPU-Installation - This repository is helpful for installing DeepStream SDK and it's python bindings in dGPU machine.
maelstrom - A workbench for writing toy implementations of distributed systems.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.