| # extracted from http//www.naturalearthdata.com/download/110m/cultural/ne_110m_admin_0_countries.zip | |
| # under public domain terms | |
| country_bounding_boxes = { | |
| 'AF': ('Afghanistan', (60.5284298033, 29.318572496, 75.1580277851, 38.4862816432)), | |
| 'AO': ('Angola', (11.6400960629, -17.9306364885, 24.0799052263, -4.43802336998)), | |
| 'AL': ('Albania', (19.3044861183, 39.624997667, 21.0200403175, 42.6882473822)), | |
| 'AE': ('United Arab Emirates', (51.5795186705, 22.4969475367, 56.3968473651, 26.055464179)), | |
| 'AR': ('Argentina', (-73.4154357571, -55.25, -53.628348965, -21.8323104794)), | |
| 'AM': ('Armenia', (43.5827458026, 38.7412014837, 46.5057198423, 41.2481285671)), |
YouTube link: https://www.youtube.com/watch?v=uCpw9eBYbOw
don't just listen to the audio, you'll miss out on Heather talking with her hands: http://cl.ly/image/3Z2y2c0v1O2i/heather.png
Picking the right architecture = Picking the right battles + Managing trade-offs
| { | |
| "name": "project-name", | |
| "description": "Template for static sites", | |
| "version": "1.0.0", | |
| "homepage": "http://www.project-name.com", | |
| "author": { | |
| "name": "Adam Reis", | |
| "url": "http://adam.reis.nz" | |
| }, | |
| "license": "UNLICENSED", |
| # coding=utf-8 | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from scipy.spatial import Voronoi | |
| from shapely.geometry import Polygon | |
| def voronoi_finite_polygons_2d(vor, radius=None): | |
| """ | |
| Reconstruct infinite voronoi regions in a 2D diagram to finite | |
| regions. |
The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.
In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.
This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.
Making a bot? Making a bot in Python? Making a bot in Python that uses the Mastodon API? If so, chances are you need to get some credentials. Here's how I did it!
(The following tutorial uses Python 2.7, but if you're using Python 3+ everything should work substantially the same.)
I just started using it, but it looks like Mastodon.py is a pretty great library for working with the Mastodon API! However, all of the authentication examples use static files to store credentials, which I don't like—I'm afraid I'll accidentally push them to Github. I like to keep my authentication as close to the actual command that runs the program as possible, so usually I pass them on the command line to the script running my bot. To do this, I need to get the appropriate credentials on their own, as separate strings that I can cut and paste.
At CARTO, among other things, we render maps, just check this example of Map with countries and USA states.
In order to limit the scope of the challenge, we are gonna use Mapnik and Node.js. Within this repository, we are providing all the pieces you need to reproduce that map. Well, all pieces except the map tile server.
An example of how to create an image with Mapnik:
| # Bash best practices and style-guide | |
| Just simple methods to keep the code clean. | |
| Inspired by [progrium/bashstyle](https://github.com/progrium/bashstyle) and [Kfir Lavi post](http://www.kfirlavi.com/blog/2012/11/14/defensive-bash-programming/). | |
| ## Quick big rules | |
| * All code goes in a function | |
| * Always double quote variables |
You may want to employ the Parcel backed boilerplate that implements the solution described below.
