March 10, 2019
What are args and kwargs and when to use them
If you have worked with Python for long enough, probably you have
encountered code that uses *args and **kwargs as arguments in
functions. Even if you haven't, it is a very neat feature that allows
you to achieve great flexibility while developing code. In this article,
we are going to discuss what and how to use flexible arguments in
functions.
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March 5, 2019
Using pyZMQ for inter-process communication: Part 2
In this article, we are going to cover how you can leverage the possibilities of ZMQ to exchange data between different processes in Python. We have covered the basics of pyZMQ in part 1. This is a fairly advanced tutorial, in which we are not only going to use pyZMQ, but also the multiprocessing library, HDF5, and openCV. We are going to acquire images from the webcam as fast as possible, we are going to save the data to disk during the acquisition, and we are going to perform some basic analysis.
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Feb. 12, 2019
Building a CRM with Jupyter Notebooks
This tutorial is going to be off-topic compared to the others on the
website. It was born out of a question regarding how to send
personalized e-mails to several people on a list, and I thought it could
be useful to post a tutorial online. This will help people interested in
building a simple Customer Relationship Manager (CRM) and it will also
show scientists that the skills they develop while working in the lab
can be used in various contexts.
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Feb. 4, 2019
Deep and Shallow Copies of Objects
Copying objects in Python seems like a trivial task, but it can have
unexpected implications in your programs. Copying data may be achieved
by either duplicating the data or by storing references to the objects,
having a much lower impact on the memory. In this article, we are going
to review the differences between deep and shallow copies of objects in
Python, including custom classes.
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Feb. 2, 2019
The with command and custom classes
There is a common pattern when programming that is opening a resource,
doing something with it and closing it. This is what you normally do
with a file, a network connection or a device. Python offers you a
command to handle this pattern: the 'with' context manager. In this
article, we are going to see how you can develop classes that follow the
same pattern.
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Dec. 17, 2018
Using pyZMQ for inter-process communication: Part 1
Working with threads and processes in Python (and in any other language)
always posses the challenge on how to exchange information between them.
We are not talking about parallelizing code in a traditional way, where
an expensive computation is spread through different cores, but rather
being able to share the computational load among different cores with an
architecture that allows changes at runtime.
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Dec. 14, 2018
PyNTA: Nanoparticle Tracking Analysis
PyNTA is a program that aims at bridging the gap between data acquisition and analysis for experiments of nanoparticle tracking. PyNTA is my first public release of a package on PyPI, the Python repository. It is a desktop application that can be used to record images from a camera, track nanoparticles and build histograms of the distribution of sizes. It is still in beta, but the basic functionality is there.
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Aug. 27, 2018
Step by Step Guide to Building a GUI
In this tutorial, we are going to build a Graphical User Interface (GUI)
to acquire images from your webcam. We are going to use OpenCV to
quickly acquire an image from your camera and PyQt5 to build the user
interface. You may find a lot of tutorials online on how to use Python
for different tasks, but it is very hard to find a complete guide on how
to build a desktop application using Python.
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Aug. 27, 2018
What are Hashable Objects
To understand hashable objects in Python, it is important to review what
a hash table is. Following the article on
Wikipedia, a hash table is a
data structure that can map keys to values and that implements a hash
function to compute the index to an array of buckets or slots. Heavy
words, I know.
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Aug. 24, 2018
Mutable and Immutable Attributes of Classes
We have seen how to leverage the differences between mutable and immutable objects and what happens when you use mutable types as default function arguments. However, we haven't discussed what happens when you use mutable types as default attributes of classes.
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Aug. 24, 2018
Mutable or Immutable Tuples
Broadly speaking, Python variables belong to one of two types:
mutable and immutable. We have discussed this yesterday, in the
Introduction To Mutable and Immutable Data
Types. The first one refers
to those elements that can be changed without the need of creating a new
one, while the latter refers to those that cannot be changed after
instantiation. A paradigmatic example of immutable objects is tuples.
However, as we are going to see in this article, tuples may seem to
change.
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Aug. 23, 2018
Mutable and Immutable Objects
Mutable objects can be changed without recreating them. This opens the door to very interesting patterns, but they can also give issues if one is not aware. We explore what mutable and immutable objects are and explore how to use their properties.
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Aug. 12, 2018
Storing Data with SQLite
SQLite is the best approach to learn about databases. They require minimal setup, and the entire database is a single file. In this tutorial we explore how to store data using a database.
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Aug. 11, 2018
Storing Binary Data and Serializing
Last week we have seen how to store data into plain text files that can
be read by any editor or by other programs. We have also seen that if
you separate your data with commas your file will follow a standard and
it will be automatically compatible with other applications, such as
spreadsheets. One of the main limitations of this strategy is that if
the data itself contains a comma, your file will not be readable
anymore.
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Aug. 10, 2018
Introduction to Storing Data in Files
Storing data to reuse it later is a central part in most Python
applications. Whether you are doing a measurement in the lab or
developing a web application, you will need to save information in a
persistent way. For example, you would like to analyze your results
after you have performed an experiment. Or you would like to keep a list
of e-mails of people who registered on your website.
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June 4, 2018
Learning (not) to Handle Exceptions
When you develop code, it is almost impossible not to run into an
error. Some problems are going to arise as soon as you start your
program, for example, if you forgot to close a parenthesis, or forgot
the : after an if-statement. However, errors at runtime are also
very frequent and harder to deal with. In this article, you are going
to learn how to handle exceptions, i.e. how to avoid program crashes
when you can anticipate that an error may appear.
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May 31, 2018
Documenting with Sphinx and Readthedocs
If you have ever followed a guide on how to start programming, most
likely you have encounter reflections about the importance of adding
comments to your code. Comments allow you to understand what the
developer was thinking when programming, maybe left some traces of what
could be improved. If you are developing software in places where people
change often, it is crucial to leave extra information behind, to speed
up the catching up of the new developers.
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May 29, 2018
Implementing Threads for Measurements
Probably you have run into the problem of wanting to update a plot while
acquiring a signal, but finding that Python is busy during the
acquisition. This happens, for example, when functions or methods take
long to execute and you can't regain control until it is done. Python
has at least two different ways of solving this issue, one is the
threading module and the other is the multiprocessing module.
They look the same but are fundamentally different, and therefore you
need to understand their differences in order to decide when to use one
or the other.
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May 22, 2018
A Primer on Classes in Python
Python is an object-oriented programming (OOP) language. Object-oriented
programming is a programming design that allows developers not only to
define the type of data of a variable but also the operations that can
act on that data. For example, a variable can be of type integer, float,
string, etc. We know that we can multiply an integer to another, or
divide a float by another, but that we cannot add an integer to a
string. Objects allow programmers to define operations both between
different objects as with themselves. For example, we can define an
object person, add a birthday and have a function that returns the
person's age.
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May 18, 2018
How to use decorators Part 2
Decorators are a very useful programming pattern that allows changing
the behavior of functions with little refactoring. Decorators allow
developers to abstract common options from functions, but mastering
their use in Python can be challenging. In this article, we are going to
go in depth regarding different options when implementing decorators.
The topics covered are:
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