The purpose of this post is to show how a sponsorship/marketing manager might track their athletes or brand ambassadors. The code we’re writing below can be used for many other applications such as tracking general trends across locales or HR insidiously monitoring if employees are discussing the company in a manner consistent with social media policies (just kidding!) Since we’re doing something specific I hope this post doesn’t get lost in the sea of yet another web scraping or twitter data mining post using yet another beginner’s abstracted away R or Python package.
PyCon 2016’s Startup Row got our campaign on the road on March 9th in San Francisco, meeting with the local SF Python user group at Yelp headquarters. Six early-stage companies that use Python gave their pitches, competing for an opportunity to exhibit in the PyCon Expo Hall on Startup Row. The roster of candidate startups included Alpaca, Bauxy, Beansprock, Opsulutely, Watt Time, and UtilityAPI.
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
Sarah Holderness is the Python instructor at Code School. Although she originally planned to be a high school math teacher, Holderness found her love of programming during a required programming class in college and has been hooked on creating things ever since.
Admin dashboard is one of the Django’s useful feature. Admin dashboard allows super users to create, read, update, delete database objects. The super users have full control over the data. Staff user can login into admin dashboard but can’t access data. In few cases, staff users needs restricted access . Super user can access all data from various in built and third party apps.
Migrations are one of Django’s most useful features, but for me, personally, it was a dreadful task to take care of model changes. Despite reading the docs, I was still scared of migration conflicts or losing the data or having to manually modify the migration files or this or that. The thing is, migrations are awesome, helpful, and once you understand them, you will have no problems with any of the things mentioned above.
qutebrowser is a very active project with a big community: More than 60 people have contributed over 250 changesets (pull requests), and hundreds of people are actively using it. In the past 2.5 years, nearly 7500 changes (commits) were uploaded. It is currently based on the QtWebKit rendering engine which is getting dated and has various issues, described in more detail below.
With this campaign, I hope being able to work full-time for a month (or more!) on qutebrowser. The goal is to add support for the newer QtWebEngine backend, which is based on the Chromium project (like Google's Chrome browser).
Recently I have been playing with some ideas about applying static analysis to Python and building a Python editor in Jetbrains MPS.
To do any of this I would need to first build a model of Python code. Recently we have seen how to parse Python code, however we still need to consider all the packages our code use. Some of those could be builtin or be implemented through C extensions. That means we do not have python code for them. In this post I look into retrieving a list of all modules and then inspect their contents.
This is a simple recipe to show that Python generators are pluggable, i.e., they can be passed as arguments into functions, and then used inside those functions.
Today, we're thrilled to host Jacob Kaplan-Moss. Jacob's a former Herokai and long-time core contributor to Django, and he's here to share an in-depth look at something that he believes will define the future of the framework. Channels introduces some new concepts to Django. Channels are essentially task queues: messages get pushed onto the channel by producers, and then given to one of the consumers listening on that channel. If you’ve used channels in Go, the concept should be fairly familiar. The main difference is that Django channels work across a network and allow producers and consumers to run transparently across many dynos and/or machines. This network layer is called the channel layer.
I worked on a Python web app a while ago that was struggling with using too much memory in production. A helpful technique for debugging this issue was adding a simple API endpoint that exposed memory stats while the app was running.
The datetime module includes functions and classes for doing date and time parsing, formatting, and arithmetic. This post is part of the Python Module of the Week series for Python 3.
If you use scrapy for crawling check out their march edition of tips.
If you already know the basics of Python and now you want to go to the next level, then this is the book for you! This book is for intermediate level Python programmers only. There won't be any beginner chapters here. Kickstarter campaign for the book.
Man Group is one of the world’s largest independent alternative investment managers, and a leader in high-alpha, liquid investment strategies. Across its four investment managers (Man AHL, Man FRM, Man GLG and Man Numeric), Man Group has a diverse offering in hedge funds and long only products across equity, credit, managed futures, convertibles, emerging markets, global macro and multi-manager solutions. At 30 September 2015, Man Group’s funds under management were $76.8 billion.
Los Angeles, CA, United States
Table Connection is a marketplace/platform that is unlike anything on the market and will revolutionize nightlife. We are looking for someone to come and help build out this service from the grassroots. Any experience working with marketplaces is a plus. The ideal person will be able to dedicate 10+ hours per week to this project. We are looking for someone that can build web scrapers and develop a backend architecture that can serve mobile clients though a restful web API.
We're passionate about helping mission-driven companies grow their teams faster and make positive change in the world. Companies delegate their candidate sourcing efforts to our human-assisted AI, which does everything from finding the perfect candidates and drafting highly personalized outreach, to maintaining those relationships over time. Candidates frequently send messages about how much they appreciated our service, and our customers rave about us,
Simulate reverse causality using quantum suicide.
TensorFlow implementation of Neural Variational Inference for Text Processing
:package: Awesome cli tool to try out python packages - It's never been easier!
Like datetime.timedelta, for date arithmetic.
Example projects using Django Channels
Swift autocompleter for Sublime Text, via the adorable SourceKitten framework
installing a Flask webapp on a Digital Ocean (or Linode, etc.) Ubuntu box
Convolutional Neural Networks for Sentence Classification in Keras
Replaces the default unhide operator in blender with a menu, allowing selective unhiding.
A tool created with Python to check if a domain's DNS is already pointing to an specific IP address.
Scrape Twitter for long hashtags that could be used as passwords