TestDriven.io: Accepting Crypto Payments with Django and Coinbase
Link: https://testdriven.io/blog/django-coinbase/
This tutorial looks at how to accept crypto Payments with Django and Coinbase Commerce.
Link: https://testdriven.io/blog/django-coinbase/
This tutorial looks at how to accept crypto Payments with Django and Coinbase Commerce.
testdriven.io
Accepting Crypto Payments with Django and Coinbase
This tutorial looks at how to accept crypto Payments with Django and Coinbase Commerce.
Test and Code: 166: unittest expectedFailure and xfail
Link: https://testandcode.com/166
xfail isn't just for pytest tests. Python's unittest has @unittest.expectedFailure.
In this episode, we cover:
using @unittest.expectedFailure
the results of passing and failing tests with expectedFa
Link: https://testandcode.com/166
xfail isn't just for pytest tests. Python's unittest has @unittest.expectedFailure.
In this episode, we cover:
using @unittest.expectedFailure
the results of passing and failing tests with expectedFa
Test & Code
Test & Code 166: unittest expectedFailure and xfail
xfail isn't just for pytest tests. Python's unittest has `@unittest.expectedFailure`.
Ben Cook: How to Use the PyTorch Sigmoid Operation
Link: https://sparrow.dev/pytorch-sigmoid/
The PyTorch sigmoid function is an element-wise operation that squishes any real number into a range between 0 and 1. This is a very common activation function to use as the last layer of binary class
Link: https://sparrow.dev/pytorch-sigmoid/
The PyTorch sigmoid function is an element-wise operation that squishes any real number into a range between 0 and 1. This is a very common activation function to use as the last layer of binary class
Sparrow Computing
How to use the PyTorch sigmoid operation - Sparrow Computing
The PyTorch sigmoid function is an element-wise operation. You can apply it with the torch.sigmoid() function or the torch.nn.Sigmoid() class.
Ben Cook: PyTorch Tensor to NumPy Array and Back
Link: https://sparrow.dev/pytorch-numpy-conversion/
NumPy to PyTorch
PyTorch is designed to be pretty compatible with NumPy. Because of this, converting a NumPy array to a PyTorch tensor is simple:
import torch
import numpy as np
x = np.eye(3)
torch.
Link: https://sparrow.dev/pytorch-numpy-conversion/
NumPy to PyTorch
PyTorch is designed to be pretty compatible with NumPy. Because of this, converting a NumPy array to a PyTorch tensor is simple:
import torch
import numpy as np
x = np.eye(3)
torch.
Sparrow Computing
NumPy Arrays to PyTorch Tensors and Back
You can easily convert a NumPy array to a PyTorch tensor and a PyTorch tensor to a NumPy array. This post explains how it works.
Ben Cook: TorchVision Transforms: Image Preprocessing in PyTorch
Link: https://sparrow.dev/torchvision-transforms/
TorchVision, a PyTorch computer vision package, has a simple API for image pre-processing in its torchvision.transforms module. The module contains a set of common, composable image transforms and giv
Link: https://sparrow.dev/torchvision-transforms/
TorchVision, a PyTorch computer vision package, has a simple API for image pre-processing in its torchvision.transforms module. The module contains a set of common, composable image transforms and giv
Sparrow Computing
TorchVision Transforms: Image Preprocessing in PyTorch
This post explains the torchvision.transforms module by describing the API and showing you how to create custom image transforms.
Stack Abuse: Creating a Form in a PDF Document in Python With borb
Link: https://stackabuse.com/creating-a-form-in-a-pdf-document-in-python-with-borb/
The Portable Document Format (PDF) is not a WYSIWYG (What You See is What You Get) format. It was developed to be platform-agnostic, independent of the underlying operating system and rendering engine
Link: https://stackabuse.com/creating-a-form-in-a-pdf-document-in-python-with-borb/
The Portable Document Format (PDF) is not a WYSIWYG (What You See is What You Get) format. It was developed to be platform-agnostic, independent of the underlying operating system and rendering engine
Stack Abuse
Creating a Form in a PDF Document in Python With borb
In this guide, we'll take a look at how to add a fillable, interactive form in a PDF document using Python and borb, with dropdown menus and input text fields.
Real Python: The Real Python Podcast – Episode #82: Welcoming the CPython Developer in Residence
Link: https://realpython.com/podcasts/rpp/82/
Earlier this year, the Python Software Foundation announced the creation of the Developer in Residence role. The first Visionary Sponsors of the PSF have provided funding for this new role for one yea
Link: https://realpython.com/podcasts/rpp/82/
Earlier this year, the Python Software Foundation announced the creation of the Developer in Residence role. The first Visionary Sponsors of the PSF have provided funding for this new role for one yea
Realpython
Episode #82: Welcoming the CPython Developer in Residence – The Real Python Podcast
Earlier this year, the Python Software Foundation announced the creation of the Developer in Residence role. The first Visionary Sponsors of the PSF have provided funding for this new role for one year. What development responsibilities does this job address?…
Python for Beginners: Callable Objects in Python
Link: https://www.pythonforbeginners.com/basics/callable-objects-in-python
You might have heard that functions in python are callable objects. In this article, we will discuss what exactly we mean by the term callable object. We will discuss concepts behind the implementatio
Link: https://www.pythonforbeginners.com/basics/callable-objects-in-python
You might have heard that functions in python are callable objects. In this article, we will discuss what exactly we mean by the term callable object. We will discuss concepts behind the implementatio
PythonForBeginners.com
Callable Objects in Python - PythonForBeginners.com
Callable Objects in Python will help you improve your python skills with easy to follow examples and tutorials. Click here to view code examples.
Ben Cook: How the NumPy append operation works
Link: https://sparrow.dev/numpy-append/
Anyone familiar with Python will know about the list append method:
a = [1, 2, 3]
a.append(4)
print(a)
# Expected result
# [1, 2, 3, 4]
But what if you want to append to a NumPy array? In that case,
Link: https://sparrow.dev/numpy-append/
Anyone familiar with Python will know about the list append method:
a = [1, 2, 3]
a.append(4)
print(a)
# Expected result
# [1, 2, 3, 4]
But what if you want to append to a NumPy array? In that case,
Sparrow Computing
How the NumPy append operation works - Sparrow Computing
Understanding the np.append() operation and when you might want to use it.
Ben Cook: NumPy Where: Understanding np.where()
Link: https://sparrow.dev/numpy-where/
The NumPy where() function is like a vectorized switch that you can use to combine two arrays. For example, let’s say you have an array with some data called and you want to create a new array with 1
Link: https://sparrow.dev/numpy-where/
The NumPy where() function is like a vectorized switch that you can use to combine two arrays. For example, let’s say you have an array with some data called and you want to create a new array with 1
Sparrow Computing
NumPy Where: Understanding np.where() - Sparrow Computing
The NumPy where function is like a vectorized switch that you can use to combine two arrays.
Ben Cook: Basic Counting in Python
Link: https://sparrow.dev/counting-in-python/
I love fancy machine learning algorithms as much as anyone. But sometimes, you just need to count things. And Python’s built-in data structures make this really easy. Let’s say we have a list of strin
Link: https://sparrow.dev/counting-in-python/
I love fancy machine learning algorithms as much as anyone. But sometimes, you just need to count things. And Python’s built-in data structures make this really easy. Let’s say we have a list of strin
Sparrow Computing
Basic Counting in Python - Sparrow Computing
I love fancy machine learning algorithms as much as anyone. But sometimes, you just need to count things. And Python’s built-in data structures make this really easy. Let’s say we have a list of strings: With a list like this, you might care about a few different…
Python⇒Speed: Pip vs Conda: an in-depth comparison of Python's two packaging systems
Link: https://pythonspeed.com/articles/conda-vs-pip/
If you’re using Python in the world of data science or scientific computing, you will soon discover that Python has two different packaging systems: pip and Conda.
Which raises some questions:
How ar
Link: https://pythonspeed.com/articles/conda-vs-pip/
If you’re using Python in the world of data science or scientific computing, you will soon discover that Python has two different packaging systems: pip and Conda.
Which raises some questions:
How ar
Python⇒Speed
Pip vs Conda: an in-depth comparison of Python’s two packaging systems
Python has two packaging systems, pip and Conda. Learn the differences between them so you can pick the right one for you.
Montreal Python User Group: Python 3.10 Translation Sprint
Link: https://montrealpython.org/en/2021/10/py310-i18n-sprint/
Python 3.10 just got released! The official documentation of this incredible version is 52% translated to French. This is a very good start, but we want to do better.
From October 25 to November 25,
Link: https://montrealpython.org/en/2021/10/py310-i18n-sprint/
Python 3.10 just got released! The official documentation of this incredible version is 52% translated to French. This is a very good start, but we want to do better.
From October 25 to November 25,
Podcast.__init__: An Exploration Of Financial Exchange Risk Management Strategies
Link: https://www.pythonpodcast.com/fx-risk-management-strategies-episode-33/
The world of finance has driven the development of many sophisticated techniques for data analysis. In this episode Paul Stafford shares his experiences working in the realm of risk management for fin
Link: https://www.pythonpodcast.com/fx-risk-management-strategies-episode-33/
The world of finance has driven the development of many sophisticated techniques for data analysis. In this episode Paul Stafford shares his experiences working in the realm of risk management for fin
The Python Podcast.__init__
The Python Podcast.__init__: An Exploration Of Financial Exchange Risk Management Strategies
An interview with Paul Stafford about his experiences using computational methods to build risk management strategies for financial exchange markets.
Ben Cook: PyTorch DataLoader Quick Start
Link: https://sparrow.dev/pytorch-dataloader/
PyTorch comes with powerful data loading capabilities out of the box. But with great power comes great responsibility and that makes data loading in PyTorch a fairly advanced topic.
One of the best wa
Link: https://sparrow.dev/pytorch-dataloader/
PyTorch comes with powerful data loading capabilities out of the box. But with great power comes great responsibility and that makes data loading in PyTorch a fairly advanced topic.
One of the best wa
Sparrow Computing
PyTorch DataLoader Quick Start - Sparrow Computing
PyTorch comes with powerful data loading capabilities out of the box. But with great power comes great responsibility and that makes data loading in PyTorch a fairly advanced topic. One of the best ways to learn advanced topics is to start with the happy…
Weekly Python StackOverflow Report: (ccxcvii) stackoverflow python report
Link: http://python-weekly.blogspot.com/2021/10/ccxcvii-stackoverflow-python-report.html
These are the ten most rated questions at Stack Overflow last week.Between brackets: [question score / answers count]Build date: 2021-10-17 06:58:09 GMTWhy is there a difference between `0--3//2` and
Link: http://python-weekly.blogspot.com/2021/10/ccxcvii-stackoverflow-python-report.html
These are the ten most rated questions at Stack Overflow last week.Between brackets: [question score / answers count]Build date: 2021-10-17 06:58:09 GMTWhy is there a difference between `0--3//2` and
Blogspot
(ccxcvii) stackoverflow python report
These are the ten most rated questions at Stack Overflow last week. Between brackets: [ question score / answers count] Build date: 2021...
PyPy: PyPy v7.3.6: release of python 2.7, 3.7, and 3.8
Link: https://www.pypy.org/posts/2021/10/pypy-v736-release.html
PyPy v7.3.6: release of python 2.7, 3.7, and 3.8-beta
The PyPy team is proud to release version 7.3.6 of PyPy, which includes
three different interpreters:
PyPy2.7, which is an interpreter supportin
Link: https://www.pypy.org/posts/2021/10/pypy-v736-release.html
PyPy v7.3.6: release of python 2.7, 3.7, and 3.8-beta
The PyPy team is proud to release version 7.3.6 of PyPy, which includes
three different interpreters:
PyPy2.7, which is an interpreter supportin
PyPy
PyPy v7.3.6: release of python 2.7, 3.7, and 3.8
PyPy v7.3.6: release of python 2.7, 3.7, and 3.8-beta
The PyPy team is proud to release version 7.3.6 of PyPy, which includes
three different interpreters:
PyPy2.7, which is an interpreter supportin
The PyPy team is proud to release version 7.3.6 of PyPy, which includes
three different interpreters:
PyPy2.7, which is an interpreter supportin
Talk Python to Me: #338: Using cibuildwheel to manage the scikit-HEP packages
Link: https://talkpython.fm/episodes/show/338/using-cibuildwheel-to-manage-the-scikit-hep-packages
How do you build and maintain a complex suite of Python packages? Of course, you want to put them on PyPI. The best format there is as a wheel. This means that when developers use your code, it comes
Link: https://talkpython.fm/episodes/show/338/using-cibuildwheel-to-manage-the-scikit-hep-packages
How do you build and maintain a complex suite of Python packages? Of course, you want to put them on PyPI. The best format there is as a wheel. This means that when developers use your code, it comes
talkpython.fm
Using cibuildwheel to manage the scikit-HEP packages
How do you build and maintain a complex suite of Python packages? Of course, you want to put them on PyPI. The best format there is as a wheel. This means that when developers use your code, it comes straight down and requires no local tooling to install…
Mike Driscoll: PyDev of the Week: Talley Lambert
Link: https://www.blog.pythonlibrary.org/2021/10/18/pydev-of-the-week-talley-lambert/
This week we chatted with Talley Lambert (@TalleyJLambert) who is a microscopist and Python enthusiast at Harvard Medical School. You can learn more about what Talley is up to and see his publications
Link: https://www.blog.pythonlibrary.org/2021/10/18/pydev-of-the-week-talley-lambert/
This week we chatted with Talley Lambert (@TalleyJLambert) who is a microscopist and Python enthusiast at Harvard Medical School. You can learn more about what Talley is up to and see his publications
Mouse Vs Python
PyDev of the Week: Talley Lambert - Mouse Vs Python
This week we chatted with Talley Lambert (@TalleyJLambert) who is a microscopist and Python enthusiast at Harvard Medical School. You can learn more about
Inspired Python: Python Pattern Matching Examples: ETL and Dataclasses
Link: https://www.inspiredpython.com/course/pattern-matching/python-pattern-matching-examples-etl-and-dataclasses?r=rss
Python Pattern Matching Examples: ETL and Dataclasses
In I walked you through the theory of Structural Pattern Matching, so now it’s time to apply that knowledge and build something practical.
Let’s
Link: https://www.inspiredpython.com/course/pattern-matching/python-pattern-matching-examples-etl-and-dataclasses?r=rss
Python Pattern Matching Examples: ETL and Dataclasses
In I walked you through the theory of Structural Pattern Matching, so now it’s time to apply that knowledge and build something practical.
Let’s
Inspiredpython
Python Pattern Matching Examples: ETL and Dataclasses
Python’s new Structural Pattern Matching is useful in a wide range of roles, including ETL and data processing. Learn how to combine it with JSON, REST APIs and Python’s dataclasses.