This is my ongoing list of Python Tutorials. I’m currently merging my various Python Tutorials into one cohesive list below as a way to reduce the amount of posts all over my site. Thank you for your patience and please feel free to drop me a Tweet if you have any comments or questions. Disqus Comment Migration Hack (code) I’m working on syncing up my post comments on Disqus again.

I have had some time to continue on my Python Forex Trading Bot (code borrowed from here and tweaked by me) now that we’re all self isolating. This is purely for educational purposes because when I run this sucker, it loses money. Not so much anymore but it’s not profitable. The reason why I say ‘educational purposes’ is that coding is not my first choice of career and I teach myself as I go along.

After a few frustrating events where I had some python code blow up because of dependencies, I started looking hard a using Groovy going forward. For some simple things, Groovy and Python are very easy. For example if I wanted to read the latest sales from Park.IO and print them out, I could do the following in Python on my Mac. import pandas as pd df = pd.read_csv('https://park.io/orders/export.csv') print (df) If I tried that on my old Raspberry Pi, I’d run into dependency issues w.

Right before the New Year I posted an article on Medium titled “Is Passive Investing Going to Kill Us?” It centers around one particular chart where the amount of money flowing into passive investing is staggering. While I’m a big fan of Passive Investing and I’ve been riding its success, I can’t help but wonder if I was just plain lucky. I know that markets love to correct imbalances but the question is when?

Just updating my past post on autogenerating support and resistance lines for the EURUSD. I’ve updated the charts to use Bokeh, a nicer and interactive set of plots. You can zoom in and see the candles at various price levels. I still need to do more labeling work on the charts as I learn how to use the Bokeh library. The thing that’s hanging me up right now is how to correctly label the horizontal support and resistance lines (aka as Spans in Bokeh) with the actual value.

I’ve finally found a way to download SEC.GOV data in a consistent and less stressful way. I want to give the University of Notre Dame Software Repository for Accounting and Finance a shout out for their excellent work. Thanks to them I can finally start taming this beast. I’ve struggled for years trying to figure out how to download SEC data. That repository is so wacky that it’s hard to find filings in there.

On the heels of my last post, I’ve extended those functions to the EURUSD pair. The data starts from this year 2019 and goes through to yesterday. It’s actually a pretty neat script as it takes data from Onada and then generates the support and resistance lines for that particular pair. The next step would be to create a buy/sell order in the Oanda Practice Account. Once I do that it’s then a matter of writing a trading strategy and testing it in real time.

I’m spending time trying to understand the differences between writing classes and functions in Python. Which one is better and why? From what I’m gathering, a lot of people are tired of writing classes in general. Classes are used in Object Oriented Programming (OOP) and some python coders hate it because it’s writing too many lines of code when only a few really matter. So programmers like functional programming (FP) in python instead.

I’m going to be the first to admit that I use Python to send out Tweets to my followers. I have a few scripts that parse RSS feeds and do retweets on an hourly basis. They work fine but they do get ‘gamed’ occasionally. That’s the problem with automation, isn’t it? Getting gamed can cause all kinds of havoc for your brand and reputation, so you have to be careful.

Continuing the stream of consciousness from my Working with Instgram API, JSONPath, and RapidMiner post, I started beta testing a new and improved Instagram Hashtag Tool. I’ve even opened it up to a few beta testers (ping me if you want to try it). It uses a RapidMiner Server on the backend to watch a Dropbox folder. Once you put a text file into the ‘In’ folder, it triggers a process and spits back a spreadsheet in the ‘Out’ folder.

Back in middle school we learned about log tables. We learned how to look them up in a table, interpolate them, and then use the result in our equations. Later on they allowed us to use calculators, which made our lives easier and faster. Fast forward many years to a Sunday morning this October. I was at my dining table with my laptop open, fooling with Pandas and iPython Notebooks (aka Juypter).