codecakes codecakes

## input.py
x = [1,2,3]
if len(x) < 3:
  return x
else:
  return [4,5,6]

## docker-mongo-repair
#!/bin/bash

# See https://github.com/docker-library/mongo/pull/63

docker run --rm --volumes-from my-mongo-server mongo unlink "/data/db/mongod.lock"
docker run --rm --volumes-from my-mongo-server mongo --repair

## Dockerfile
# set the base image to Debian
# https://hub.docker.com/_/debian/
FROM debian:latest

# replace shell with bash so we can source files
RUN rm /bin/sh && ln -s /bin/bash /bin/sh

# update the repository sources list
# and install dependencies
RUN apt-get update \

## README.md

      
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                codecakes
                / README.md
            
            
              Created
              January 30, 2020 20:20
                — forked from rrag/README.md
            
              
                Yet another tutorial and Cheat sheet to Functional programming
              
          
    There are many tutorials and articles available online which explain functional programming. Examples show small functions, which are composed into others which again get composed. It is hard to imagine how it would all work, then come the analogies and then the math. While the math is necessary to understand it can be difficult to grasp initially. The analogies on the other hand, (at least for me) are not relatable. Some articles assume the reader knows the different terminologies of FP. Over all I felt it is not inviting to learn.
This introduction is for those who have had a tough time understanding those analogies, taken the plunge to functional programming but still have not been able to swim. This is yet another tutorial on functional programming
Terminology

Functions as first class citizens

Functions are first class means they are just like anyone else, or rather they are not special, they behave the same as say primitives or strings or objects.

  
## 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

## gist:7b949b1f323e8792d5a382da023a1463
<!doctype html>
<title>Site Maintenance</title>
<style>
  body { text-align: center; padding: 150px; }
  h1 { font-size: 50px; }
  body { font: 20px Helvetica, sans-serif; color: #333; }
  article { display: block; text-align: left; width: 650px; margin: 0 auto; }
  a { color: #dc8100; text-decoration: none; }
  a:hover { color: #333; text-decoration: none; }
</style>

## install-postgres-10-ubuntu.md

      
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                codecakes
                / install-postgres-10-ubuntu.md
            
            
              Created
              January 15, 2018 09:24
                — forked from alistairewj/install-postgres-10-ubuntu.md
            
              
                Install PostgreSQL 10 on Ubuntu
              
          
    Install PostgreSQL 10 on Ubuntu

This is a quick guide to install PostgreSQL 10 - tested on Ubuntu 16.04 but likely can be used for Ubuntu 14.04 and 17.04 as well, with one minor modification detailed below.
(Optional) Uninstall other versions of postgres

To make life simple, remove all other versions of Postgres. Obviously not required, but again, makes life simple.
dpkg -l | grep postgres


## upgrade.md

      
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                codecakes
                / upgrade.md
            
            
              Created
              March 21, 2017 07:28
                — forked from chrismccord/upgrade.md
            
              
                Phoenix 1.2.x to 1.3.0 Upgrade Instructions
              
          
    If you want a run-down of the 1.3 changes and the design decisions behidn those changes, check out the LonestarElixir Phoenix 1.3 keynote: https://www.youtube.com/watch?v=tMO28ar0lW8
To use the new phx.new project generator, you can install the archive with the following command:
$ mix archive.install https://github.com/phoenixframework/archives/raw/master/phx_new.ez

Bump your phoenix dep

Phoenix v1.3.0 is a backwards compatible release with v1.2.x. To upgrade your existing 1.2.x project, simply bump your phoenix dependency in mix.exs:

  
## useful_pandas_snippets.py
# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

## model.ex
defmodule Model do
  schema "models" do
    field :foo, :string
    has_many :children, Model, foreign_key: :parent_id
    belongs_to :parent, Model, foreign_key: :parent_id
  end

  @doc """
    Recursively loads parents into the given struct until it hits nil
  """
	#!/bin/bash

	# See https://github.com/docker-library/mongo/pull/63

	docker run --rm --volumes-from my-mongo-server mongo unlink "/data/db/mongod.lock"
	docker run --rm --volumes-from my-mongo-server mongo --repair
	# set the base image to Debian
	# https://hub.docker.com/_/debian/
	FROM debian:latest

	# replace shell with bash so we can source files
	RUN rm /bin/sh && ln -s /bin/bash /bin/sh

	# update the repository sources list
	# and install dependencies
	RUN apt-get update \
	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
	<!doctype html>
	<title>Site Maintenance</title>
	<style>
	body { text-align: center; padding: 150px; }
	h1 { font-size: 50px; }
	body { font: 20px Helvetica, sans-serif; color: #333; }
	article { display: block; text-align: left; width: 650px; margin: 0 auto; }
	a { color: #dc8100; text-decoration: none; }
	a:hover { color: #333; text-decoration: none; }
	</style>
	# List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	# Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	# Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(valuelist)]
	defmodule Model do
	schema "models" do
	field :foo, :string
	has_many :children, Model, foreign_key: :parent_id
	belongs_to :parent, Model, foreign_key: :parent_id
	end

	@doc """
	Recursively loads parents into the given struct until it hits nil
	"""