sainb

	Function	Command
	Get a list of all your environments	conda env list
	Get a list of all the packages installed in your current active environment	conda list
	Create an environment called [ENV_NAME]	conda create --name [ENV_NAME]
	Create an environment called [ENV_NAME] and install pandas and numpy	conda create --name [ENV_NAME] pandas numpy
	Activate an environment called [ENV_NAME]	conda activate [ENV_NAME]
	Create an environment folder called env in the current working directory (e.g. /Users/Daniel/project_1/) and install pandas and numpy	conda create --prefix ./env pandas numpy
	Activate an environment stored in a folder called env which is located within /Users/Daniel/project_1/	conda activate /Users/daniel/project_1/env
	Deactivate an environment	conda deactivate
	Export your current active environment to a YAML file called environment (see why below)	conda env export > environment.yaml

Installing Cassandra on Mac OS X

Install Homebrew

Homebrew is a great little package manager for OS X. If you haven't already, installing it is pretty easy:

ruby -e "$(curl -fsSL https://raw.github.com/Homebrew/homebrew/go/install)"

Command Cheatsheet

Convert Maven build to gradle

gradle init
Initialise new project folder structure (Java example)

gradle init --type java-library

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

Clarify and agree on the scope of the system

User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

General rules

Follow standard conventions.
Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
Boy scout rule. Leave the campground cleaner than you found it.
Always find root cause. Always look for the root cause of a problem.



	@RunWith(PowerMockRunner.class) – Tell Junit that run this test using PowerMockRunner

	@PrepareForTest(A.class) – This is needed when we need to test static methods of A class

	AService mock = PowerMockito.mock(A.class) – Creating a mock for A class

	PowerMockito.when(mock.mockedMethod()).thenReturn(value) – When mockedMethod is called in the code, then return the value specified here.

	from bayes_opt import BayesianOptimization
	from sklearn.cross_validation import KFold
	import xgboost as xgb

	def xgbCv(train, features, numRounds, eta, gamma, maxDepth, minChildWeight, subsample, colSample):
	# prepare xgb parameters
	params = {
	"objective": "reg:linear",
	"booster" : "gbtree",
	"eval_metric": "mae",