lambdamusic

## Error handling in Python is done through the use of exceptions that are caught in try blocks and handled in except blocks. If an error is encountered, a TRy block code execution is stopped and transferred down to the except block, as shown in the following syntax:

try:
    f = open("test.txt")
except IOError:
    print "Cannot open file."

## In addition to using an except block after the try block, you can also use the finally block. The code in the finally block will be executed regardless of whether an exception occurs.

f = open("test.txt")

jednano

Git Cheat Sheet

Initial Setup

Initialize a repo

Create an empty git repo or reinitialize an existing one

git init

itsmattsoria

SHORTCUTS

Key/Command	Description
Tab	Auto-complete files and folder names
Ctrl + A	Go to the beginning of the line you are currently typing on
Ctrl + E	Go to the end of the line you are currently typing on
Ctrl + U	Clear the line before the cursor
Ctrl + K	Clear the line after the cursor
Ctrl + W	Delete the word before the cursor
Ctrl + T	Swap the last two characters before the cursor

Overdrivr

# -*- coding: utf-8 -*-
from pyqtgraph.Qt import QtGui, QtCore
import numpy as np
from numpy import arange, sin, cos, pi
import pyqtgraph as pg
import sys

class Plot2D():
    def __init__(self):
        self.traces = dict()

CMCDragonkai

Matplotlib Backends

Matplotlib is a plotting library. It relies on some backend to actually render the plots. The default backend is the agg backend. This backend only renders PNGs. On Jupyter notebooks the matplotlib backends are special as they are rendered to the browser. Generally you will not need to explicitly set the backend on a Jupyter notebook. This does introduce a discrepancy between code that runs in Jupyter and code that runs as a script natively in the Python interpreter. So you need to understand that the 2 environments are not the same

akey7

import numpy as np
from scipy.io.wavfile import write

# Samples per second
sps = 44100

# Frequency / pitch of the sine wave
freq_hz = 440.0

# Duration

akey7

# See for tiao.io/posts/notebooks/save-matplotlib-animations-as-gifs/ more information and notes below
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation, rc
from IPython.display import HTML, Image

# equivalent to rcParams['animation.html'] = 'html5'
rc('animation', html='html5')

fig, ax = plt.subplots()

akey7

def mode(xs):
    """
    This returns the mode of the values in xs. xs is a standard
    Python list with discrete values, which can be of any hashable
    value.

    Fo this problem, think about using a dictionary in some way.
    What could be the keys? The values? Also remember that dictionaries
    are UNORDERED--in other words, there is no guaranteed order.

akey7

def median(xs):
    """
    When given a standard Python list of numbers, this function will
    return the median value. There are a few cases to consider:

    1. xs is an empty list: return None

    2. A list with one element: returns that element

    3. A list with an odd number of elements: Returns the middle value.

honux77

#!/bin/bash

# put this in ec2 ubuntu user-data

mkdir /home/ubuntu/script/
cat <<'EOF' >> /home/ubuntu/script/slack.sh

#!/bin/bash
ip=`/usr/bin/curl -s -w '\n' http://169.254.169.254/latest/meta-data/public-ipv4`
instance=`/usr/bin/curl -s -w '\n' http://169.254.169.254/latest/meta-data/instance-id`