Python Programming
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Dynamically Regrouping QuerySets In Templates - Building SaaS #73
In this episode, we worked on a new view to display course resources. While building out the template, I used some template tags to dynamically regroup a queryset into a more useful data format for rendering.
I started a new view before the stream to display content, but I had not filled it in before the stream started.
We added new data to the context, and did some adjustments to the URL based on the required inputs for the view.
Once I had the data, I quickly iterated in the template to see the parts that I included. I needed to display the course resources in a different way from how the queryset provided them so I used the built-in regroup template tag to organize the data differently. regroup saved me from doing a bunch of manipulation in the view code.
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PyCharm: Webinar: “virtualenv – a deep dive” with Bernat Gabor
virtualenv is a tool that builds virtual environments for Python. It was first created in September 2007 and just went through a rewrite from scratch. Did you ever want to know what parts virtual environments can be broken down into? Or how they work? And how does virtualenv differ from the Python builtin venv? This is the webinar you want.
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Python 3.8.6
This is the sixth maintenance release of Python 3.8
The Python 3.8 series is the newest major release of the Python programming language, and it contains many new features and optimizations.
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Python 3.8.6 is now available
Python 3.8.6 is the sixth maintenance release of Python 3.8.
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Facial Detection in Python with OpenCV
Facial detection is a powerful and common use-case of Machine Learning. It can be used to automatize manual tasks such as school attendance and law enforcement. In the other hand, it can be used for biometric authorization.
In this article, we'll perform facial detection in Python, using OpenCV.
[...]
With OpenCV installed, we can import it as cv2 in our code.
To read an image in, we will use the imread() function, along with the path to the image we want to process. The imread() function simply loads the image from the specified file in an ndarray. If the image could not be read, for example in case of a missing file or an unsupported format, the function will return None.
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Sending Emails With CSV Attachment Using Python
In this tutorial, we will learn how to send emails with CSV attachments using Python.
Pre-Requirements
I am assuming you already have an SMTP server setup if not you can use the Gmail SMTP or Maligun or anything similar to that.
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Sending Email With Zip Files Using Python
In this tutorial, we will learn how to send emails with zip files using Python’s built-in modules.
Pre-Requirements
I am assuming that you already have an SMTP (Simple Mail Transfer Protocol ) server setup if not you can use Gmail SMTP or something like mailgun. A simple google search will land you on multiple ways to get free SMTP servers.
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Is Python better than R for data science?
If data science is going to remain a main-stream in the next 5 years, it needs to add value not only in terms of proof of concept (as it is doing now) but also in terms of production (as it is failing in over 70% of cases, as Gartner recently surveyed). While R is an absolute winner in terms of classical pattern recognition libraries and statistical methods, python has a better ability to write production-ready codes.
Above point raises another important point, that is best practices of software engineering (e.g., uml architecture designs, unit testing, coding review, scrum) are going to be absolute requirements in near future for data scientists, in addition to the expected knowledge in machine learning and statistics. The reason is that proper software, production ready, codes require proper architecture design, with proper reviews and testing.
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