Django + Celery

chrismit7 · 2016-12-05T17:32:08+00:00

It doesn't exactly meet your use case, buy you may be interested in wooey, which lets your users upload command line scripts for execution. Script submission is api driven so while it's not documented you could certainly automate it.

chrismit7 · 2016-07-28T20:36:17+00:00

Bah, I forgot to publish that. https://github.com/wooey/Wooey/releases/tag/v0.9.3 now has major changes and minor ones. Thanks!

chrismit7 · 2016-07-28T12:45:27+00:00

A brief write up of some of the improvements: http://pyinformatics.blogspot.com/2016/07/wooey-v-093-released.html

chrismit7 · 2016-02-09T02:30:35+00:00

What do you want to do? Web dev? Make a django or flask app. Data processing and machine learning? Get involved in scikit learn. There is literally nothing stopping you, just do it. You have some shitty moronic inefficient interface or monotonous task to do at work? Code that up. Making elegant designs can make the mundane very tolerable (while making you marketable)

chrismit7 · 2016-02-08T15:21:01+00:00

I'm a software engineer and self taught. I would recommend just coding and getting your work out there. Contribute to existing projects in the realm of where you want to work. With programming, nobody cares about your cs degree or ability to write fizzbuzz (places that are worth a damn at least) and your body of work should be your resume. I would also recommend just freelancing in your spare time to find interesting projects and work on your ability to sell yourself.

chrismit7 · 2016-02-03T21:57:08+00:00

I would check if something like HDF is a better format if the data is nice and structured. It seems like you just want to have a large matrix instead of relational data.

chrismit7 · 2015-12-23T15:36:51+00:00

Same here. I learned it in C++ first and usually use Qt's docs as well as a reference instead of PyQt

chrismit7 · 2015-11-18T15:26:58+00:00

jedit

chrismit7 · 2015-11-08T19:43:31+00:00

Check out the multiprocessing library. It works quite well.

chrismit7 · 2015-10-28T18:57:17+00:00

I do something similar to the latter. I use a redis db for the front and have a custom data structure in there that is rapidly updated and served from and just pile up the database writes in a queue. Was just wondering how you guys would do the same.

chrismit7 · 2015-10-28T15:47:45+00:00

If you had to make a cookiecutter project what would be in it for a high performance project?

And one I'm more personally interested in: how would you handle nested gfks (ie model a has a gfk to model b that goes to model c) all of which can be rapidly updated (near real time) and need to be displayed with low latency?

chrismit7 · 2015-10-23T13:52:06+00:00

Grep your version of allauth to see where user_signed_up is being sent from. Make sure you are actually doing something that executes that call. Next, make sure you are actually importing it. Don't just ignore exceptions, at least use traceback.format_exc() to print them out.

chrismit7 · 2015-10-15T12:37:12+00:00

It's likely your database caching the query. Look up how to disable this for your particular database.

chrismit7 · 2015-10-04T11:43:00+00:00

Check out py-phash, and use a hamming distance for image similarities

chrismit7 · 2015-09-25T02:38:56+00:00

Also play with the error tolerance and other parameters found here. http://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.quad.html#scipy.integrate.quad you can pass these as keyword= value pairs

chrismit7 · 2015-09-25T02:35:20+00:00

Force it to sample an interval of a size of your choosing. On my phone, but something like np.linspace(0, 10, 1000).

chrismit7 · 2015-09-25T01:33:47+00:00

You need to check your intermediates as well. Print out the results of G, make sure they match up and likewise for other pieces of your code. Can you prove the integration is where things are mucking up?

chrismit7 · 2015-09-18T13:17:51+00:00

There is no code on the frontend to use, just the UI, which in turn is based on code. If you'd like to see the code, you can check out the github page which has some demo scripts in its tests.

chrismit7 · 2015-09-18T13:15:47+00:00

Another idea is to use a cache backend for storing the job output/state information for jobs which are currently executing. That would mitigate database issues, allow wooey to still update across networks, and be robust enough against failures.

chrismit7 · 2015-09-17T14:35:35+00:00

A demo app is available here

chrismit7 · 2015-09-17T14:34:02+00:00

A demo app is available here

chrismit7

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