I''m teaching a course in scientific Python these days. Usually I give
"homework" from project Euler (which
I personally use every time I learn a new programming language). I thought it''ll
be fun to solve the problem not just with Python but with what numpy has to offer as well.
Here''s an example solution for project Euler problem 8.
If it won't be simple, it simply won't be. [Hire me, source code] by Miki Tebeka, CEO, 353Solutions
Tuesday, April 21, 2015
Tuesday, April 07, 2015
Docker + MiniConda = A Perfect Match
Working with one of
my clients (who is hiring BTW), we decided to use Docker as deployment platform. Since many Linux systems
now use Python for many utilities, it''s advisable to install your own Python
next to the system one and use it.
Installing CPython from source requires some system packages, libraries, headers and some knowledge. The much easier path it to use MiniConda (from the wonderful people at Continuum). Not only the Python installation is super simple, but also the conda package manger will get you a lot of packages pre-compiled so you don''t have to install gcc and header files for C extensions. And if you can''t find the package you need with conda, pip is also available.
Here''s a little project to demonstrate how to do this. The application is an image server with has two entry points /edge for edge detection and /resize for image resizing. We''ll be using scikit-image and Pillow for image manipulation and Flask as web server. All of them can be conda installed.
Here''s the Dockerfile for the project. Build with docker build -tag imgsrv, Run with docker run -p 8080:8080 imgsrv (see Makefile).
Installing CPython from source requires some system packages, libraries, headers and some knowledge. The much easier path it to use MiniConda (from the wonderful people at Continuum). Not only the Python installation is super simple, but also the conda package manger will get you a lot of packages pre-compiled so you don''t have to install gcc and header files for C extensions. And if you can''t find the package you need with conda, pip is also available.
Here''s a little project to demonstrate how to do this. The application is an image server with has two entry points /edge for edge detection and /resize for image resizing. We''ll be using scikit-image and Pillow for image manipulation and Flask as web server. All of them can be conda installed.
Here''s the Dockerfile for the project. Build with docker build -tag imgsrv, Run with docker run -p 8080:8080 imgsrv (see Makefile).
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