Mehmet Ali "Mali" Akmanalp makmanalp

Serving Flask under a subpath

Your Flask app object implements the __call__ method, which means it can be called like a regular function. When your WSGI container receives a HTTP request it calls your app with the environ dict and the start_response callable. WSGI is specified in PEP 0333. The two relevant environ variables are:

SCRIPT_NAME
The initial portion of the request URL's "path" that corresponds to the application object, so that the application knows its virtual "location". This may be an empty string, if the application corresponds to the "root" of the server.

Papers

This list is adapted from the lecture plan for the "Advanced Topics in Computer Systems" course at Berkeley, which is available here: https://people.eecs.berkeley.edu/~kubitron/cs262/index_lectures.html

Thanks to Anthony Joseph and John Kubiatowicz for putting the original list together.

Introduction to the course, some basic philosophy, UNIX system.

	import os
	import sys
	import io
	import tarfile
	import urllib.request


	ARCHIVE_URL = 'http://d.pr/f/YqS5+'

	#!/usr/bin/env bash -e

	cat <<TEXT

	Git has no undo feature, but maybe these will help:
	===================================================

	## Unstage work

	Unstage a file

	def remove_foreign_keys(db):
	log("Dropping all foreign key constraints from archive database")

	inspector = reflection.Inspector.from_engine(db.engine)
	fake_metadata = MetaData()

	fake_tables = []
	all_fks = []

	for table_name in db.metadata.tables:

	import pandas as pd
	import numpy as np
	from sklearn.feature_extraction import DictVectorizer

	def encode_onehot(df, cols):
	"""
	One-hot encoding is applied to columns specified in a pandas DataFrame.

	Modified from: https://gist.github.com/kljensen/5452382

	# see also https://github.com/wrobstory/pgshift

	import gzip
	from io import StringIO, BytesIO
	from functools import wraps

	import boto
	from sqlalchemy import MetaData
	from pandas import DataFrame
	from pandas.io.sql import SQLTable, pandasSQL_builder

	SELECT OBJECT_TYPE
	,OBJECT_SCHEMA
	,OBJECT_NAME
	FROM (
	SELECT 'TABLE' AS OBJECT_TYPE
	,TABLE_NAME AS OBJECT_NAME
	,TABLE_SCHEMA AS OBJECT_SCHEMA
	FROM information_schema.TABLES

	UNION

	"""
	A sympy-based Lagrange polynomial constructor.

	Given a set of function inputs and outputs, the lagrangePolynomial function will construct an
	expression that for every input gives the corresponding output. For intermediate values,
	the polynomial interpolates (giving varying results based on the shape of your input).
	This is useful when the result needs to be used outside of Python, because the
	expression can easily be copied. To convert the expression to a python function object,
	use sympy.lambdify.
	"""

	# Note – this is not a bash script (some of the steps require reboot)
	# I named it .sh just so Github does correct syntax highlighting.
	#
	# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
	#
	# The CUDA part is mostly based on this excellent blog post:
	# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

	# Install various packages
	sudo apt-get update