Derick Greyling dgreyling

How to recover lost Python source code if it's still resident in-memory

I screwed up using git ("git checkout --" on the wrong file) and managed to delete the code I had just written... but it was still running in a process in a docker container. Here's how I got it back, using https://pypi.python.org/pypi/pyrasite/ and https://pypi.python.org/pypi/uncompyle6

Attach a shell to the docker container

Install GDB (needed by pyrasite)

apt-get update && apt-get install gdb

Simple automated GIT Deployment using GIT Hooks

Here are the simple steps needed to create a deployment from your local GIT repository to a server based on this in-depth tutorial.

How it works

You are developing in a working-copy on your local machine, lets say on the master branch. Most of the time, people would push code to a remote server like github.com or gitlab.com and pull or export it to a production server. Or you use a service like deepl.io to act upon a Web-Hook that's triggered that service.

Login page using Python, Flask and sqlite3 DB

How-to guide

(Task for GCI 2015-16) Year: 2015-16 This guide will show how to create a simple login page with Flask (a python microframework) and a sqlite3 database.

1. Database Schema and Models

As we are creating a simple user login app we need to store 2 basic values in the database: the username and the password. In order to build the database we need to define a schema:

	#!/bin/bash

	set -Eeuo pipefail

	BLOCKSIZE=256
	OVERVIEW_BLOCKSIZE=256
	MIN_OVERVIEW_SIZE=256
	KEEP_TEMP=0
	MOSAIC_VRT="mosaic.vrt"
	MOSAIC_RGB_VRT="mosaicrgb.vrt"

	import numpy as np
	from keras import backend as K
	from keras.models import Sequential
	from keras.layers.core import Dense, Dropout, Activation, Flatten
	from keras.layers.convolutional import Convolution2D, MaxPooling2D
	from keras.preprocessing.image import ImageDataGenerator
	from sklearn.metrics import classification_report, confusion_matrix

	#Start
	train_data_path = 'F://data//Train'

	#from __future__ import absolute_import
	from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img

	from keras.callbacks import ModelCheckpoint
	from keras.models import Sequential
	from keras.layers import Convolution2D, MaxPooling2D
	from keras.layers import Layer, Dense, Dropout, Activation, Flatten, Reshape, Merge, Permute
	from keras.layers import ZeroPadding2D, UpSampling2D
	from keras.layers.normalization import BatchNormalization
	import sys

	"""
	Problem:
	How to Convert PDF to Image with Python Script ?

	Installation:
	I use ubuntu OS 14.04
	We use wrapper for ImageMagick [http://www.imagemagick.org/script/index.php] to Convert The PDF file
	in Python do:

	$ sudo apt-get install libmagickwand-dev

	#!/bin/bash
	set -e
	type docker >/dev/null 2>&1 \|\| { echo >&2 "error: docker is required. See: https://docs.docker.com/engine/installation/linux/"; exit 1; }
	type docker-compose >/dev/null 2>&1 \|\| { echo >&2 "error: docker-compose is required. See: https://docs.docker.com/compose/install/"; exit 1; }
	[ ! -d cgimap ] && git clone --branch add-docker --depth 1 https://github.com/Firefishy/cgimap.git;
	[ ! -d openstreetmap-website ] && git clone --branch add-docker --depth 1 https://github.com/Firefishy/openstreetmap-website.git
	(cd cgimap && docker build -t openstreetmap/cgimap .)
	(cd openstreetmap-website && docker-compose run --rm app bundle exec rake db:migrate)
	(cd openstreetmap-website && docker-compose up)
	# remove environment; cd openstreetmap-website ; docker-compose down

	web: env/bin/mapproxy-util serve-develop mapproxy.yaml --bind 0.0.0.0:${PORT:=8080}

	jupyter:
	image: jupyter/datascience-notebook
	environment:
	- PASSWORD=${PASSWORD}


	nginx:
	image: nginx
	links:
	- jupyter