Python Weekly 419

Time:2020-4-4

An article, course, or lecture

How to use Dropbox security to build a tool for threat detection and event response of log system

https://blogs.dropbox.com/tech/2019/10/how-dropbox-security-builds-better-tools-for-threat-detection-and-incident-response/

Traditionally, the most common way to build threat detection and response tools is to separate the automation part from the investigation part. In our experience, this can lead to a lot of crashes. In Dropbox, we have built a general basic abstract model for our log system, which can detect alertbox, covenant and forerunner in all stages of the event response cycle. Integration leverages powerful open source tools to enable us to quickly browse data and automate alerts, so we can focus on more complex threats.

Python 3.8

https://docs.python.org/3.8/whatsnew/3.8.html

This article introduces the new features of Python 3.8 compared with 3.7.

Complete Python library import guide: absolute import, relative Import and other methods

https://www.pythonforthelab.com/blog/complete-guide-to-imports-in-python-absolute-relative-and-more/

How to construct your code to make the import structure clear.

How does haptik migrate a lot of code from Python 2 to Python 3?

How Haptik carried out their largest Python 3 Migration

This article describes how haptik completed the entire Python 2 to Python 3 code migration project with 0 down.

Segmentation and confrontation algorithm in Python Ultimate Guide

https://skerritt.blog/divide-and-conquer-algorithms/

A very easy to understand segmentation and confrontation algorithm.

The simple nature of Y combiner (described in Python)

https://lptk.github.io/programming/2019/10/15/simple-essence-y-combinator.html

Y combiner is the core concept of lambda syntax, which is the basis of high-level programming language. The Y combiner allows you to define a recursion without using a self referencing function. I’ve read most articles devoted to y-composers that first show y-composers (which are quite difficult to understand), and then try to explain how they work. I don’t think it’s a good way. In this article, I will take another approach: I will first describe the essence of Y combiner in simple terms, or explain how to recurse without self reference, and then deduce the general concept of Y combiner.

Using Python’s Django to upload files to AWS S3https://stackabuse.com/uploading-files-to-aws-s3-with-python-and-django/

In this article, we’ll explore how Django handles file uploads and how to use cloud storage to extend this capability to meet our needs.

Using pandas’ qcut and cut functions to merge data

https://pbpython.com/pandas-qcut-cut.html

The qcut and cut functions of pandas are used to store continuous data values in discrete buckets or bins. This article describes the differences between the two commands and how to use them.

Drawing with pyqtgraph

https://www.learnpyqt.com/courses/graphics-plotting/plotting-pyqtgraph/

In this tutorial, we’ll walk through creating a drawing widget using pyqtgraph, and then demonstrate custom drawing with line colors, line types, axis labels, background colors, and multiple lines.

How to deploy flask using mongodb and docker

https://www.digitalocean.com/community/tutorials/how-to-set-up-flask-with-mongodb-and-docker

In this tutorial, you will build, package, and run web applications using flask, nginx, and mongodb in the docker container. Learn to define the entire stack configuration in the docker-compose.yml file, and understand the configuration files of python, mongodb and nginx. Flask requires a web server to handle HTTP requests, so you’ll also learn to use gunicorn, the python WSGI HTTP service, to handle the application. As a reverse proxy, nginx forwards the request to gunicorn for processing.

Why is my verification set loss lower than the training set loss?

Why is my validation loss lower than my training loss?

In this tutorial, you will learn three main reasons why the loss value of verification set may be lower than that of training set when you train your deep learning neural network model.

Python property access and descriptor protocol:https://amir.rachum.com/blog/2019/10/16/descriptors/

Tens of thousands of scientific papers have been affected by some misconceptions about Python:http://www.blog.pythonlibrary.org/2019/10/13/thousands-of-scientific-papers-may-be-invalid-due-to-misunderstanding-python/

Step by step to teach you how to use sentry to monitor errors in real time in Django web applications:https://blog.hlab.tech/a-step-by-step-tutorial-on-how-to-monitor-software-errors-in-real-time-using-sentry-in-django-web-applications/

Using spotify API interface to analyze user’s music habits:https://nvbn.github.io/2019/10/14/playlist-analysis/

An interesting project, tool, or library

Detectron 2 library analyzing music habits

https://nvbn.github.io/2019/10/14/playlist-analysis/

Detectron 2 is the next generation software system of Facebook AI research, which implements the latest object detection algorithm. Detectron 2 is a complete rewrite of detectron.

PyTorch Mobile

https://pytorch.org/mobile/home/

Deploy pyttorch on IOS and Android devices.

pyChart.js

https://github.com/IridiumIO/pyChart.js

Chart.js is an interactive drawing library for Python’s Django framework.

pfun

https://github.com/suned/pfun

A small library using the type module is designed to use the static type checking function in Python.

cast-sh

https://github.com/hericlesme/cast-sh

An instance of the terminal running in the browser.

CrypTen

https://github.com/facebookresearch/CrypTen

Machine learning framework for privacy protection.

sotabench-eval

https://github.com/paperswithcode/sotabench-eval

A simple machine learning evaluator based on common standards.

TorchBeast

https://github.com/facebookresearch/torchbeast

A pytorch framework for distributed RL.

image_to_numpy

https://github.com/ageitgey/image_to_numpy

Load the image file into the numpy array with EXIF vector support to prevent image distortion!

Daudin

https://github.com/terrycojones/daudin

A python command line shell.

New version

Python 3.8.0:https://www.python.org/downloads/release/python-380/

Python 3.8.0 is the latest version of Python programming language. Compared with version 3.7, many new functions and optimizations have been added. Now the stable version can be downloaded and used.

Django 3.0 beta 1:https://www.djangoproject.com/weblog/2019/oct/14/django-30-beta-1-released/

PyPy v7.2:https://morepypy.blogspot.com/2019/10/pypy-v72-released.html

This article is translated from Python weekly 419. It has been deleted and is not for commercial use.

Python Weekly 419

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