Skip to main content

Superstream optimisation library for Kafka producers

Project description

Superclient Python

A Python library for automatically optimizing Kafka producer configurations based on topic-specific recommendations.

Overview

Superstream Clients works as a Python import hook that intercepts Kafka producer creation and applies optimized configurations without requiring any code changes in your application. It dynamically retrieves optimization recommendations from Superstream and applies them based on impact analysis.

Supported Libraries

  • kafka-python
  • aiokafka
  • confluent-kafka
  • Faust
  • FastAPI event publishers
  • Celery Kafka backends
  • Any custom wrapper around these Kafka clients

Features

  • Zero-code integration: No code changes required in your application
  • Dynamic configuration: Applies optimized settings based on topic-specific recommendations
  • Intelligent optimization: Identifies the most impactful topics to optimize
  • Graceful fallback: Falls back to default settings if optimization fails

Installation

pip install superstream-clients && python -m superclient install_pth

That's it! Superclient will now automatically load and optimize all Kafka producers in your Python environment.

Usage

After installation, superclient works automatically. Just use your Kafka clients as usual.

Docker Integration

When using Superstream Clients with containerized applications, include the package in your Dockerfile:

FROM python:3.8-slim

# Install superclient
RUN pip install superstream-clients
RUN python -m superclient install_pth

# Your application code
COPY . /app
WORKDIR /app

# Run your application
CMD ["python", "your_app.py"]

Required Environment Variables

  • SUPERSTREAM_TOPICS_LIST: Comma-separated list of topics your application produces to

Optional Environment Variables

  • SUPERSTREAM_LATENCY_SENSITIVE: Set to "true" to prevent any modification to linger.ms values
  • SUPERSTREAM_DISABLED: Set to "true" to disable optimization
  • SUPERSTREAM_DEBUG: Set to "true" to enable debug logs

Example:

export SUPERSTREAM_TOPICS_LIST=orders,payments,user-events
export SUPERSTREAM_LATENCY_SENSITIVE=true

Prerequisites

  • Python 3.8 or higher
  • Kafka cluster that is connected to the Superstream's console
  • Read and write permissions to the superstream.* topics

License

Apache License 2.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

superstream_clients_beta-1.0.3.tar.gz (31.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

superstream_clients_beta-1.0.3-py3-none-any.whl (35.6 kB view details)

Uploaded Python 3

File details

Details for the file superstream_clients_beta-1.0.3.tar.gz.

File metadata

  • Download URL: superstream_clients_beta-1.0.3.tar.gz
  • Upload date:
  • Size: 31.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for superstream_clients_beta-1.0.3.tar.gz
Algorithm Hash digest
SHA256 abf84cac04778905c3363d461e742dcfdc88f6a276553b106e573d0602f48d30
MD5 f2a6db7eb87418bf4963a91f9370405f
BLAKE2b-256 34b749e86297261ff79d7b51f4d147010aec53e12fe2a865c89e95a1687a69da

See more details on using hashes here.

File details

Details for the file superstream_clients_beta-1.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for superstream_clients_beta-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 207d1a6a9b336034c8a2e2885ee7a29c30b8e72823201fefc7db57fdc9c28f4d
MD5 782b9f7109388430519290e9e1ccf719
BLAKE2b-256 e0e6cc44bed3d3d08c10c495ee248daf404b51208944600d794f2664877bbee7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page