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Detailed Flask Web Development Series : Python
Hey guys,I’ve been working on building a really detailed course around the Flask framework to get many beginners started with web development with Python.Course Page: http://ift.tt/2wRGZrh are the first few videos of the series, I’ve also have written tutorials with the videos as well:Overview & InstallationVideoBlog PostHello World & Flask Application StructureVideoBlog PostFlask Templates, Jinja2 Tutorial, Bootstrap Integration, and Custom Error PagesVideoBlog PostThe next few videos and guides will be coming out in the next few days/weeks, and I’ll be releasing new content on a regular basis.My goal is to create the best foundational web development course with the Flask framework to get as many people started with Flask as a stepping stone in web development with Python.If you guys enjoy the content, I will also be working on a detailed series like this with Django as well.Here are some of the following videos that will be coming up with the series:Web Forms with FlaskDatabase Integrations with FlaskThen I will be working on content that will actually have you build a complete blog application with users, blog posts, and all sorts of other really cool stuff.With the current content so far, I would love to hear some feedback as well.~ CW via /r/Python
IFTTT  reddit  Python 
september 2017 by rtluckie
I want to save you the time of reading this article: Hidden gems: 14 Python libraries too good to overlook : Python
This slideshow article doesn't include much info about the libraries, but that's okay because you are probably familiar with most of these "hidden gems." There are only 13 libraries because the first slide is an intro. The author could have done better imo.Pillow -- Image processingGooey -- add a GUI interface to your python CLI programsPeewee -- a small, expressive ORM for mySQL, PostgreSQL, and SQLiteScrapy -- a web scraping frameworkApache Libcloud -- A single API wrapper to many cloud providers (like linode, rackspace, etc.)Pygame -- make multimedia programs, like games.Numpy -- useful for scientific computing. If you use this, you should also check out SciPy and Pandas.Sh -- call shell sub-processes as if they were functions.Python-docx -- process/create MS Word documents. (I also recommend checking out openpyxl for Excel docs)PyFilesystem -- abstract your entire filesystem similar to the way a file object abstracts a single file.EbookLib -- process EPUB2/EPUB3 ebook formats. Kindle format under development per github page.Cython -- write C extensions for python.Behold -- debugging toolProps to /u/COAST_TO_RED_LIGHTSEdit: Please stop upvoting this. I just wrote it because I was annoyed at the terrible content this website produced and the ridiculous, anti-reader slideshow format they chose. Upvote this guy giving away his book content or this guy helping you add Python 3 support instead. via /r/Python
IFTTT  reddit  Python 
february 2017 by rtluckie
Python for Algorithmic Trading and Investing tutorial series : Python
Hi there, my name is Harrison and I frequently do Python programming tutorials on PythonProgramming.net and YouTube.com/sentdex. All tutorials are free in both text and video forms.The latest series that I have put out is Python for Finance. The aim of this series is to show what can be done with Python in the field of finance and algorithmic trading using data science (spoiler alert: a lot!).Even though you probably aren’t going to get rich, you might save yourself a lot of money (when you back test your silly trading idea and realize it’s bad), and you’ll learn about statistics and data science with Python along the way.I start the series off with a simplistic introduction to using Python+Pandas+Matplotlib to get stock data, visualize stock data, and to manipulate this data.From here, we get into Quantopian, which is a Python-based platform built on top of the Zipline library for back-testing, but has since expanded out to enable quite a bit more than that.We use Quantopian both for simplistic back testing, but also for doing research into future trading strategies, since Quantopian also provides a bunch of free data like minute pricing data, fundamentals along with tools like Alphalens for analyzing various factors that you believe to be beneficial to a trading strategy.If you would like to check it out, the series starts here: Python for Finance introductionIf you are already familiar with Pandas and want to jump straight into the strategies and using Quantopian for back-testing and research: Algorithmic trading and research with QuantopianIf you have any questions, requests, or suggestions, feel free to ask here or on the respective tutorials. via /r/Python
IFTTT  reddit  Python 
february 2017 by rtluckie
Say Hello to Visual Alchemist (Update) : Python
A few days ago, I'd released the draft version of VA, a small web-based tool to create database models and generate corresponding sqlalchemy classes on-the-fly.Little did I know that I'll receive such a huge response on /r/python for this. So, I decided to pursue it further and added these extra features:Create primary/foreign-key relations on canvas by simple drag/drop.Saves canvas in local data-store (HTML5-enabled browsers only).Ability to export/import the canvas to/from JSON files.Enjoy!EDIT: Special Thanks to /u/Ostwind for referring me to jsPlumb, an excellent JavaScript library to create drag-drop connections - that helped me with the primary/foreign keys implementation. via /r/Python
IFTTT  reddit  Python 
june 2015 by rtluckie
NLTK Tutorial series - Basics, then Live Sentiment Analysis on Twitter : Python
Wrapped up releasing the NLTK 3 tutorial series on YouTube and posted it to http://pythonprogramming.netDirect link to the start of the course: http://pythonprogramming.net/tokenizing-words-sentences-nltk-tutorial/NLTK is used for natural language processing (using computers to read text.)In this series, we cover the basics of NLTK, doing things like tokenizing, chunking, part of speech tagging, and named entity recognition, then how to train a text-classifier (sentiment classifier), and then we apply our sentiment analysis classifier to a live twitter stream and we graph it on a live matplotlib graph for the cherry on top. Off to pyqt next! via /r/Python
IFTTT  reddit  Python 
may 2015 by rtluckie
Is there a service out there where I can pay for consultation with an experienced (python) software engineer over skype for an hourly fee? My company needs assistance writing tests over legacy code, and I want a testing expert to help me. : Python
All too common scenario. Tech startup for cloud software. Fast, mobile development, and the software specifications are changing rapidly with every new customer. Testing was an after thought, and now we have a huge code base with no tests.We have code with deep inheritance structures, intimate database and third party library integration, etc.I have a solid grasp on unit testing, but I just need someone who has gone through this before to bounce ideas off of to make sure I'm moving in the right direction.Is there any way I can purchase this service? via /r/Python
IFTTT  reddit  Python 
may 2015 by rtluckie

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