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@jeromer
jeromer / storageaggregations.conf
Created Nov 11, 2016
Graphite's storage aggregations for collectd metrics
View storageaggregations.conf
# This is a work in progress. Any improvement welcome :)
[collectd_plugin_entropy]
pattern = \.entropy\.entropy$
xFilesFactory = 0.3
aggregationMethod = last
[collectd_plugin_tcpconns]
pattern = \.tcp_connections.*$
xFilesFactory = 0.3
View postgres_update_strategies.py
#! /usr/bin/env python
# Tested on Postgres 9.5
import psycopg2
import datetime
conn = psycopg2.connect("dbname=sandbox user=postgres")
cursor = conn.cursor()
View numbers.everyone.should.know.txt
Numbers Everyone Should Know
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns
Mutex lock/unlock 25 ns
Main memory reference 100 ns
Compress 1K bytes with Zippy 3,000 ns
Send 2K bytes over 1 Gbps network 20,000 ns
Read 1 MB sequentially from memory 250,000 ns
@jeromer
jeromer / compassbearing.py
Last active Sep 19, 2020
compass bearing between two points in Python
View compassbearing.py
# LICENSE: public domain
def calculate_initial_compass_bearing(pointA, pointB):
"""
Calculates the bearing between two points.
The formulae used is the following:
θ = atan2(sin(Δlong).cos(lat2),
cos(lat1).sin(lat2) − sin(lat1).cos(lat2).cos(Δlong))
@jeromer
jeromer / orthodromicdistance.py
Created Feb 22, 2012
Orthodromic distance using the Harversine formula in Python
View orthodromicdistance.py
# -*- coding: utf-8 -*-
import math
def calculate_orthodromic_distance(pointA, pointB):
"""
Calculates the great circle distance between two points.
The great circle distance is the shortest distance.
This function uses the Haversine formula :
- https://en.wikipedia.org/wiki/Haversine_formula
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