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Same could be said about Django and APIs!

by parham 12y ago

andybak 12y ago
Been writing a Django-based API-heavy app and it still feels very Django. DRF fits the ORM like a glove and there's a Django way of doing things that runs throughout. Models ≈ ModelForms ≈ ModelSerializers ≈ ViewSets ≈ ModelAdmin. Certainly never feels like I'm fighting the framework(s).
kyllo 12y ago
Good point, but my impression of this tool is that it's more intended for quickly tacking an external API onto an existing Django app, and not so much for building an internal API for a client-side MVC app (Angular/Ember/Backbone etc). It can certainly be used for that too, but Django is kind of overkill for that use case, and a lighter-weight framework like Flask with a REST plugin like Restless and (optionally) an ORM plugin like SQLAlchemy is probably sufficient.
- parham 12y ago
  My thought too but if your data is complex you should consider building an API first using an ORM more powerful than Django's (e.g. SQLAlchemy) then use Django to handle users and then allow your users to access the API directly via signed requests or something... that way you get good performance without network/Django ORM overhead.
  - lumpypua 12y ago
    I prefer SQLAlchemy, but it definitely has just as much overhead as django's ORM. This is just a microbenchmark, but notice how when frameworks are making raw DB queries they stomp the ones using ORM: http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&l=1kw http://www.techempower.com/benchmarks/#section=data-r9&hw=i7... Looking at only python frameworks using ORM, Flask with SQLA hits 85% of the requests/sec of Django using pypy, and only 73% on stock python. Django has decently lower latency as well (450ms django, 550ms flask pypy, 600ms flask stock python): http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&l=1kw&o=1 http://www.techempower.com/benchmarks/#section=data-r9&hw=i7... Really, if performance matters at all and you want an ORM use Java. The fastest python solution using an ORM is a tenth as fast as the Java solutions, with literally 10x the latency. :P Flask making raw db queries gets within 2x of this, as does bottle. http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&o=3 http://www.techempower.com/benchmarks/#section=data-r9&hw=i7...
    - parham 12y ago
      I wasn't refering to performance, but the queries you could do. If performance was an issue and the ORM was the bottle neck then I would use raw SQL and scrap the ORM altogether. Thanks for this benchmarks though good to know that info! :) Edit: The overhead thing was a secondary point my main point was handling data.
    - wfn 12y ago
      These numbers are somewhat misleading, and the phrasing may confuse people. > The fastest python solution using an ORM is a tenth as fast as the Java solutions This may be true if your bottleneck is the ORM in the first place (this is relatively easily verifiable by running a profiler on your python program, comparing the results against (e.g.) EXPLAIN ANALYZE output, etc.) I run a service with a decently-sized database (over 100G); so far all the bottlenecks were at the "query execution in the DB" level. I use lower-level SQLAlchemy primitives to form the queries, and check the resulting raw SQL against the raw SQL queries that I had designed for the DB before. If you know what you're doing, SQLAlchemy will know, too. Use cases and situations vary. But the way you phrase those particular benchmarking results is somewhat misleading.
jaegerpicker 12y ago
No not really. Django makes a great API framework.
- parham 12y ago
  Depends on your data, if you don't need joins/complex queries Django indeed is a great framework, though if an API is all you need a lighter framework might be worth looking into.
  - crdoconnor 12y ago
    Django handles joins just fine using the double underscore in the filter method. It also provides an easy to use means of doing complex queries via raw SQL: MyModel.objects.extra(select = {'blah blah raw sql'}) will return a regular queryset.
    - rectangletangle 12y ago
      Django's ORM seems to be one of the areas they're consistently improving upon. Sure it's not SQLAlchemy. But SQLAlchemy is just an ORM, while Django is quite a bit more. Though I really love how SQLAlchemy separates it's core from the higher-level ORM.

Same could be said about Django and APIs!

by parham 12y ago

Same could be said about Django and APIs!

Been writing a Django-based API-heavy app and it still feels very Django. DRF fits the ORM like a glove and there's a Django way of doing things that runs throughout. Models ≈ ModelForms ≈ ModelSerializers ≈ ViewSets ≈ ModelAdmin. Certainly never feels like I'm fighting the framework(s).

kyllo 12y ago

Good point, but my impression of this tool is that it's more intended for quickly tacking an external API onto an existing Django app, and not so much for building an internal API for a client-side MVC app (Angular/Ember/Backbone etc). It can certainly be used for that too, but Django is kind of overkill for that use case, and a lighter-weight framework like Flask with a REST plugin like Restless and (optionally) an ORM plugin like SQLAlchemy is probably sufficient.

parham 12y ago
My thought too but if your data is complex you should consider building an API first using an ORM more powerful than Django's (e.g. SQLAlchemy) then use Django to handle users and then allow your users to access the API directly via signed requests or something... that way you get good performance without network/Django ORM overhead.
- lumpypua 12y ago
  I prefer SQLAlchemy, but it definitely has just as much overhead as django's ORM. This is just a microbenchmark, but notice how when frameworks are making raw DB queries they stomp the ones using ORM: http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&l=1kw http://www.techempower.com/benchmarks/#section=data-r9&hw=i7... Looking at only python frameworks using ORM, Flask with SQLA hits 85% of the requests/sec of Django using pypy, and only 73% on stock python. Django has decently lower latency as well (450ms django, 550ms flask pypy, 600ms flask stock python): http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&l=1kw&o=1 http://www.techempower.com/benchmarks/#section=data-r9&hw=i7... Really, if performance matters at all and you want an ORM use Java. The fastest python solution using an ORM is a tenth as fast as the Java solutions, with literally 10x the latency. :P Flask making raw db queries gets within 2x of this, as does bottle. http://www.techempower.com/benchmarks/#section=data-r9&hw=i7&test=query&o=3 http://www.techempower.com/benchmarks/#section=data-r9&hw=i7...
  - parham 12y ago
    I wasn't refering to performance, but the queries you could do. If performance was an issue and the ORM was the bottle neck then I would use raw SQL and scrap the ORM altogether. Thanks for this benchmarks though good to know that info! :) Edit: The overhead thing was a secondary point my main point was handling data.
  - wfn 12y ago
    These numbers are somewhat misleading, and the phrasing may confuse people. > The fastest python solution using an ORM is a tenth as fast as the Java solutions This may be true if your bottleneck is the ORM in the first place (this is relatively easily verifiable by running a profiler on your python program, comparing the results against (e.g.) EXPLAIN ANALYZE output, etc.) I run a service with a decently-sized database (over 100G); so far all the bottlenecks were at the "query execution in the DB" level. I use lower-level SQLAlchemy primitives to form the queries, and check the resulting raw SQL against the raw SQL queries that I had designed for the DB before. If you know what you're doing, SQLAlchemy will know, too. Use cases and situations vary. But the way you phrase those particular benchmarking results is somewhat misleading.

jaegerpicker 12y ago

No not really. Django makes a great API framework.

parham 12y ago
Depends on your data, if you don't need joins/complex queries Django indeed is a great framework, though if an API is all you need a lighter framework might be worth looking into.
- crdoconnor 12y ago
  Django handles joins just fine using the double underscore in the filter method. It also provides an easy to use means of doing complex queries via raw SQL: MyModel.objects.extra(select = {'blah blah raw sql'}) will return a regular queryset.
  - rectangletangle 12y ago
    Django's ORM seems to be one of the areas they're consistently improving upon. Sure it's not SQLAlchemy. But SQLAlchemy is just an ORM, while Django is quite a bit more. Though I really love how SQLAlchemy separates it's core from the higher-level ORM.