The Adventures of Dash Daring in Code & Music & Business
I wanted to try writing an Android app. In spite of using plain old Java I wanted to give the new kid on the block Kotlin (from the Jetbrains folks) a try.
Coming from a Python background it’s good to see that Kotlin doesn’t use semi-colons! But the curly braces from Java make code blocks are still there, hmpf… Continue reading “Learning Kotlin – Part 1”
10h before sleep – no caffeine
3h before sleep – no more eating
2h before sleep – no more work
1h before sleep – no more tv / tablet
0 times snoozing the alarm clock in the morning
So when I want to get to bed at around 22:00 (10pm) my schedule would look like the following
After one week my experience is this:
Some tweeking
I shifted my sleep time from 22:00 – 6:00 to 22:30 – 6:30
As the Junior Data Scientist of Knight Industries we created a table to keep track of all our operatives: SQL-Basics: Create, Read, Update, Delete
Devon asks us to keep track of our operations aka missions as well. For the first implementation let us assume that a mission has one operative and an operative can participate in multiple missions. that’s what we call an 1 to many relationship.
+------------+ +----------+ | |1 active in n| | | operative +-----------------+ missions | | | | | +------------+ +----------+
Missions have an id, a code name like “Phantom Liberty”, an operative id and a total cost. Continue reading “SQL-Basics: Relations”
In SQL-Basics
we learned the standard SQL statements to create a table, insert data into it, retrieving data from tables and altering data. Now we want to do even
Devon is a data driven man and to evaluate our mission, he likes to know from us:
SELECT COUNT(*) FROM missions;
SELECT SUM(total_cost) FROM missions; SELECT MIN(total_cost) FROM missions; SELECT MAX(total_cost) FROM missions; SELECT AVG(total_cost) FROM missions; SELECT * FROM missions ORDER BY total_cost DESC LIMIT 5;
import unicodecsv
def read_csv(filename):
with open(filename, 'rb') as f:
reader = unicodecsv.DictReader(f)
return list(reader)
In Distributing your own package on PyPi I wrote about my first package on PyPI. Here are some refinements aka lessons learned:
I wondered why the project description on PyPi was empty. Solution: You need a long_description. If You already have a README.md, you can read it into a string and use this as the description.
But you have to add long_description_content_type=’text/markdown’ as well.
from setuptools import setup
# read the contents of your README file
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='flask_url_mapping',
version='0.6',
packages=['flask_url_mapping'],
url='https://github.com/jboegeholz/flaskurls',
download_url='https://github.com/jboegeholz/flaskurls/archive/0.2.tar.gz',
license='MIT',
author='Joern Boegeholz',
author_email='boegeholz.joern@gmail.com',
description='Django-style URL handling for Flask',
long_description=long_description,
long_description_content_type='text/markdown',
install_requires=["Flask", "Flask-Login"]
)
If your package relies on the usage of other python packages you should add them to your setup.py as well via install_requires.
setup(
name='flask_url_mapping',
version='0.6',
packages=['flask_url_mapping'],
url='https://github.com/jboegeholz/flaskurls',
download_url='https://github.com/jboegeholz/flaskurls/archive/0.2.tar.gz',
license='MIT',
author='Joern Boegeholz',
author_email='boegeholz.joern@gmail.com',
description='Django-style url handling for Flask',
install_requires=["Flask", "Flask-Login"]
)
When you finished reading part 1 of the introduction you might have wondered how to draw more than one line or curve into on plot. I will show you now.
To make it a bit more interesting we generate two functions: sine and cosine. We generate our x-values with numpy’s linspace function
import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 2*np.pi) sin = np.sin(x) cos = np.cos(x) plt.plot(x, sin, color='b') plt.plot(x, cos, color='r') plt.show()
You can plot two or more curves by repeatedly calling the plot method.
That’s fine as long as the individual plots share the same axis-description and values.
fig = plt.figure() p1 = fig.add_subplot(2, 1, 1) p2 = fig.add_subplot(2, 1, 2) p1.plot(x, sin, c='b') p2.plot(x, cos, c='r'
The add_subplot method allows us to put many plots into one “parent” plot aka figure. The arguments are (number_of_rows, number_of_columns, place in the matrix) So in this example we have 2 rows in 1 column, sine is in first, cosine in second position:
when you have a 2 by 2 matrix it is counted from columns to row
fig = plt.figure() p1 = fig.add_subplot(221) p2 = fig.add_subplot(222) p3 = fig.add_subplot(223) p4 = fig.add_subplot(224) p1.plot(x, sin, c='b') p2.plot(x, cos, c='r') p3.plot(x, -sin, c='g') p4.plot(x, -cos, c='y')
The code is available as a Jupyter Notebook on my github
One of the things I always forget is date and time in Python.
So message to myself:
The strftime method is used for formatting (string_format_time)
import datetime start_date = datetime.datetime.now() DATE_FORMAT = '%d/%m/%Y %H:%M' print(start_date.strftime(DATE_FORMAT))
Since Python 3.3 You can chain dictionaries which contain the same key in a prioritized order:
from collections import ChainMap
prio_1 = {"param_1": "foo"}
prio_2 = {"param_1": "foobar", "param_2": "bar"}
combined = ChainMap(prio_1, prio_2)
print(combined["param_1"]) # outputs 'foo'
print(combined["param_2"]) # outputs 'bar'
Everyone is talking about error culture and that companies should embrace it. Jurgen Appelo sheds some light on this topic by bisecting the term “error” and introducing a tool to celebrate the right kind of errors.
