Want to deliver faster? Want to recover from failures more quickly? Want to improve your cycle time? This Actionable Continuous Delivery Metrics eBook will provide you insight into your software delivery pipeline, and help you to improve your delivery and team processes.
In almost every project we work on, we use Django admin for support and operations. Over time we experienced an influx of new users and the amount of data we had stored grew rapidly. With a large dataset we started to experience the real cost of some Django admin features.
In this paper, we will talk about the basic steps of text preprocessing. These steps are needed for transferring text from human language to machine-readable format for further processing. We will also discuss text preprocessing tools.
One of the greatest challenges associated with maintaining a complex desktop application like Dropbox is that with hundreds of millions of installs, even the smallest bugs can end up affecting a very large number of users. Bugs inevitably will strike, and while most of them allow the application to recover, some cause the application to terminate. These terminations, or “crashes,” are highly disruptive events: when Dropbox stops, synchronization stops. To ensure uninterrupted sync for our users we automatically detect and report all crashes and take steps to restart our application when they occur.
If you’re planning to learn data analysis, machine learning, or data science tools in python, you’re most likely going to be using the wonderful pandas library.
Algojammer is an experimental, proof-of-concept code editor for writing algorithms in Python. It was mainly written to assist with solving the kind of algorithm problems that feature in competitions like Google Code Jam, Topcoder and HackerRank.
In the first episode, we got to the bottom of the error reported by mypy: we understood exactly what was wrong with the initial code and why it wasn’t type-safe. Now, we need to do something about it. The goal of this episode is not to give the ultimate solution to the problem, but to approach it from different perspectives and provide some (fairly simple) suggestions. Choosing and implementing the right one depends on the specific use case.
Vespene is a modern, streamlined build and self-service automation platform. Vespene is designed to combat chaos in complex software development and operations environments. Our mission is simple: get great people together to build the ultimate system we all want to use.
Michelangelo PyML: Introducing Uber's Platform for Rapid Python ML Model Development | Uber Engineering Blog
As a company heavily invested in AI, Uber aims to leverage machine learning (ML) in product development and the day-to-day management of our business. In pursuit of this goal, our data scientists spend considerable amounts of time prototyping and validating powerful new types of ML models to solve Uber’s most challenging problems (e.g., NLP based smart reply systems, ticket assistance systems, fraud detection, and financial and marketplace forecasting). Once a model type is empirically validated to be best for the task, engineers work closely with data science teams to productionize and make it available for low latency serving at Uber-scale. This cycle of prototyping, validating, and productionizing is central to ML innovation at Uber, and the less friction at each stage of this process, the faster Uber can innovate.
ChessViz reads a chess game as pgn-file and generates a visual representation of the game as chart. The chart shows how the game developed, who was in front, which moves were critical, which moves were forced and different sections (like rookending) of the game are marked. ChessViz is implemented in Python with the packages “python-chess” (https://pypi.org/project/python-chess/) and “plotly” (https://plot.ly/python/).
kamerka - 416 Stars, 48 Fork
Build interactive map of cameras from Shodan
waveglow - 132 Stars, 21 Fork
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
mpDNS - 60 Stars, 11 Fork
Multi-Purpose DNS Server
StarGAN-Voice-Conversion - 25 Stars, 0 Fork
This is a tensorflow implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks https://arxiv.org/abs/1806.02169
instadp - 19 Stars, 5 Fork
Download any users Instagram display picture/profile picture in full quality
XanXSS - 14 Stars, 0 Fork
A simple XSS finding tool
djangohunter - 12 Stars, 6 Fork
Tool designed to help identify incorrectly configured Django applications that are exposing sensitive information.
lswriteups - 12 Stars, 1 Fork
CLI tool to get the links of original writeups from ctftime.org
django-find - 9 Stars, 0 Fork
Easily add search functionality to Django projects
django-auth-tutorial-example - 5 Stars, 2 Fork
Django Authentication Video Tutorial
tfmodel - 4 Stars, 0 Fork
Command-line tool to inspect TensorFlow models
django-postgres-unlimited-varchar - 4 Stars, 0 Fork
A tiny app adding support unlimited varchar fields (no specified max length) in Django/Postgres.