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*[Merging Django ORM with SQLAlchemy for Easier Data Analysis](https://djangostars.com/blog/merging-django-orm-with-sqlalchemy-for-easier-data-analysis/)
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has details on why, how and when you may want to use SQLAlchemy to
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augment the [Django ORM](/django-orm.html).
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### SQLAlchemy resources
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The best way to get comfortable with SQLAlchemy is to dig in and write
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avoid with `ForeignKey` field relationships, handling IDs and many other
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edge cases that come up when frequently working with Django's ORM.
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*[Merging Django ORM with SQLAlchemy for Easier Data Analysis](https://djangostars.com/blog/merging-django-orm-with-sqlalchemy-for-easier-data-analysis/)
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provides rationale for using the [SQLAlchemy](/sqlalchemy.html) ORM
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instead of Django's default ORM in some situations.
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*[Working with huge data sets in Django](https://blog.labdigital.nl/working-with-huge-data-sets-in-django-169453bca049)
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explains how to slice the data you retrieve by query into pages and then
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use `prefetch_related` on a subset of the data rather than your whole
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great overview of WebRTC and the new security concerns it can bring as it
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is integrated into more web applications.
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*[How Discord Handles Two and Half Million Concurrent Voice Users using WebRTC](https://blog.discordapp.com/how-discord-handles-two-and-half-million-concurrent-voice-users-using-webrtc-ce01c3187429)
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provides detailed insight into the what and why of the highly scalable
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[Discord](https://discordapp.com/) technical architecture that relies
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upon WebRTC for communication. There are a bunch of great examples here
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for why some of the service must be centralized (to prevent client IP
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addresses from leaking to other clients) while others are decentralized
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to assist with scaling the number of possible connections.
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*[Architectures for a kickass WebRTC application](https://www.youtube.com/watch?v=m9QxBc0OeoI)
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is a video of a technical talk that covers some of the tools and protocols
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that can be used to create your WebRTC projects and why you would choose
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