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@bep
bep / hugo-on-android.md
Last active Jul 13, 2019
Run Hugo on an Android phone
View hugo-on-android.md

First install Termux

Then there are two options:

Build from source

Open the Termux terminal on your Android device and copy-and-paste the commands listed below and hit ENTER:

@alysonla
alysonla / active-issues.sql
Last active Aug 7, 2019
Queries that power the open source section of the 2016 Octoverse report https://octoverse.github.com/
View active-issues.sql
-- Active issues
-- Count of total active issues in the specified time frame
-- Source: githubarchive public data set via Google BigQuery http://githubarchive.org/
SELECT
COUNT(DISTINCT JSON_EXTRACT_SCALAR(events.payload, '$.issue.id')) AS events_issue_count
FROM (SELECT * FROM TABLE_DATE_RANGE([githubarchive:day.],TIMESTAMP('2015-09-01'),TIMESTAMP('2016-08-31')))
AS events
-- 10,723,492 active issues
@fperez
fperez / ProgrammaticNotebook.ipynb
Last active Jul 25, 2019
Creating an IPython Notebook programatically
View ProgrammaticNotebook.ipynb
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@edrex
edrex / camlistore-server-vps-s3.md
Last active Jun 8, 2016
Camlistore on a VPS with S3 blob storage
View camlistore-server-vps-s3.md

Let's set up Camlistore on a Linux server, with blobs stored in s3. This seems to be the currently best-supported option for "cloud" deployment.

This is meant as a supplement to the official server config doc. Read through both docs before you start.

http://camlistore.org/docs/server-config

This blog post is also recommended reading.

I've posted my config files for reference, but they will be created the first time you run camlistored (for the server) and camput init (for the client) so don't copy them.

@lelandbatey
lelandbatey / whiteboardCleaner.md
Last active Aug 24, 2019
Whiteboard Picture Cleaner - Shell one-liner/script to clean up and beautify photos of whiteboards!
View whiteboardCleaner.md

Description

This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.

The script is here:

#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"

Results

@baali
baali / MajorClust.py
Last active May 28, 2016
MajorClust algorithm implementation using sklearn based on SO conversation about text clustering using python(http://stackoverflow.com/questions/1789254/clustering-text-in-python).
View MajorClust.py
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import linear_kernel
import numpy as np
from itertools import combinations
from random import shuffle
def majorclust_sklearn():
texts = [
"foo blub baz",
"foo bar baz",
@zflat
zflat / pg_migrate_steps.sh
Last active Sep 4, 2018
Migrate pg dump from Heroku to local sqlite3 development (and beyond)
View pg_migrate_steps.sh
# Export the Heroku PG database to a local dump file
# https://devcenter.heroku.com/articles/heroku-postgres-import-export#export
heroku pgbackups:capture
curl -o latest.dump `heroku pgbackups:url`
# Install postregs & Setup password
# https://help.ubuntu.com/community/PostgreSQL
# List databases
sudo -u postgres psql -l
@hellerbarde
hellerbarde / latency.markdown
Created May 31, 2012 — forked from jboner/latency.txt
Latency numbers every programmer should know
View latency.markdown

Latency numbers every programmer 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  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns  = 250 µs
@jboner
jboner / latency.txt
Last active Aug 23, 2019
Latency Numbers Every Programmer Should Know
View latency.txt
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD
@baali
baali / dlAttachments.py
Created May 8, 2012
Python script to download all gmail attachments.
View dlAttachments.py
# Something in lines of http://stackoverflow.com/questions/348630/how-can-i-download-all-emails-with-attachments-from-gmail
# Make sure you have IMAP enabled in your gmail settings.
# Right now it won't download same file name twice even if their contents are different.
import email
import getpass, imaplib
import os
import sys
detach_dir = '.'
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