Lecture 1: Introduction to Research — [📝Lecture Notebooks] [
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[
#!/usr/bin/env python3 | |
""" | |
Downloaded from https://gist.github.com/rams3sh/15ac9487f2b6860988dc5fb967e754aa | |
Craft a web request to the AWS rest API and hit an endpoint that actually works but isn't supported in the boto3 or AWS CLI | |
Based on https://gist.github.com/andrewmackett/5f73bdd29aeed4728ecaace53abbe49b | |
Usage :- python3 rds_log_downloader.py --region <region> --db <db_name> --logfile <log_file_to_download> --output <output_file_path> |
# -*- coding: utf-8 -*-\ | |
""" | |
The MIT License (MIT) | |
Copyright (c) 2015 Zalando SE | |
Permission is hereby granted, free of charge, to any person obtaining a copy | |
of this software and associated documentation files (the "Software"), to deal | |
in the Software without restriction, including without limitation the rights |
#!groovy | |
import groovy.json.JsonOutput | |
import groovy.json.JsonSlurper | |
def label = "mypod-${UUID.randomUUID().toString()}" | |
podTemplate(label: label, yaml: """ | |
spec: | |
containers: | |
- name: mvn | |
image: maven:3.3.9-jdk-8 |
Disclaimer: Please follow this guide being aware of the fact that I'm not an expert regarding the things outlined below, however I made my best attempt. A few people in IRC confirmed it worked for them and the results looked acceptable.
Attention: After following all the steps run gdk-pixbuf-query-loaders --update-cache
as root, this prevents various gdk-related bugs that have been reported in the last few hours. Symptoms are varied, and for Cinnamon the DE fails to start entirely while for XFCE the icon theme seemingly can't be changed anymore etc.
Check the gist's comments for any further tips and instructions, especially if you are running into problems!
Results after following the guide as of 11.01.2017 13:08:
#!/usr/bin/env python | |
from flask import Flask, request, abort | |
import cups | |
import requests | |
import os | |
import tempfile | |
app = Flask(__name__) |
--- | |
- name: Group by Distribution | |
hosts: all | |
tasks: | |
- group_by: key={{ansible_distribution}} | |
- name: Set Time Zone | |
hosts: Ubuntu | |
gather_facts: False | |
vars: |
Moved to git repository: https://github.com/denji/nginx-tuning
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon
with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
Notes from Advanced Python Workshop conducted on 24th - 26th May 2013 in Bangalore.
ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats