- Create
UNLOGGED
table. This reduces the amount of data written to persistent storage by up to 2x. - Set
WITH (autovacuum_enabled=false)
on the table. This saves CPU time and IO bandwidth on useless vacuuming of the table (since we neverDELETE
orUPDATE
the table). - Insert rows with
COPY FROM STDIN
. This is the fastest possible approach to insert rows into table. - Minimize the number of indexes in the table, since they slow down inserts. Usually an index
on
time timestamp with time zone
is enough. - Add
synchronous_commit = off
topostgresql.conf
. - Use table inheritance for fast removal of old data:
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-- Create a group | |
CREATE ROLE readaccess; | |
-- Grant access to existing tables | |
GRANT USAGE ON SCHEMA public TO readaccess; | |
GRANT SELECT ON ALL TABLES IN SCHEMA public TO readaccess; | |
-- Grant access to future tables | |
ALTER DEFAULT PRIVILEGES IN SCHEMA public GRANT SELECT ON TABLES TO readaccess; |
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CMD exec /bin/bash -c "trap : TERM INT; sleep infinity & wait" |
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#!/usr/bin/env python | |
'''Using Webhook and self-signed certificate''' | |
# This file is an annotated example of a webhook based bot for | |
# telegram. It does not do anything useful, other than provide a quick | |
# template for whipping up a testbot. Basically, fill in the CONFIG | |
# section and run it. | |
# Dependencies (use pip to install them): | |
# - python-telegram-bot: https://github.com/leandrotoledo/python-telegram-bot |
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class PreparaLeilaoAdmin(admin.ModelAdmin): | |
model = Leilao | |
extra = 0 | |
can_delete = False | |
form = LeilaoForm | |
def save_model(self, request, obj, form, change): | |
super(PreparaLeilaoAdmin, self).save_model(request, obj, form, change) | |
arquivo = form.cleaned_data.get('arquivo') |
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.
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from django.contrib.sites.models import Site | |
class Object(object): | |
def __init__(self, model, key): | |
self.model = model | |
self.key = key | |
def __call__(self, *args, **kwargs): | |
params = {} |
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#element:before { | |
content: ""; | |
position: absolute; | |
width: 0; | |
height: 0; | |
border-left: 16px solid transparent; | |
border-right: 16px solid transparent; | |
border-bottom: 16px solid #fff; | |
top: -15px; | |
left: 27px; |
The following is for the AOC 931sn.
- Find the Recommended Resolution for your Display (on Manufacturer Website or similar)
- Run the following in you shell
- Press the "Auto Adjust" Button on your Display