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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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The Training Celery - Mastering Asynchronous Python Tasks training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training Celery - Mastering Asynchronous Python Tasks training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training Celery - Mastering Asynchronous Python Tasks training is carried out through:
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Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Quick installation of Celery in a Python virtual environment, broker configuration with Redis or RabbitMQ for reliable message management, creation of simple asynchronous tasks on concrete cases like email sending or heavy file processing, launching workers locally and testing distributed execution, practical exercises to debug and monitor the first queues, development of a scalable red thread project from the first day.
Deployment of Celery in a cluster with multiple workers and priority queues to handle high volumes, integration of Celery Beat for periodic scheduling of critical enterprise tasks, hands-on with Flower for a real-time monitoring dashboard with metrics and alerts, performance optimization via retry and rate limiting on real scenarios, finalization of the red thread project with endurance tests and Docker deployment documentation, immediate application of acquired skills.
Target audience
Backend Python developers, DevOps engineers, and software architects for professional skill advancement
Prerequisites
Mastery of Python 3, basic knowledge of Redis or RabbitMQ, and web frameworks like Django or Flask
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