Writing a Raffle Script

Due to the COVID Pandemic, many things are … different. One thing that needed to be different this year was the way that students at my daughters middle school got to spend their ‘Hero Points’.

Hero Points are points earned for good behavior. In a typical year the students would get to spend them at the student store, but with all of the closures, this wasn’t possible. For the students in my daughter’s 8th grade this was a big deal as they’re going on to High School next year, so we can just roll them over to next year!

Instead of having the kids ‘spend’ their Hero Points the PTO offered up the solution of a raffle based on the number of Hero Points they had. But they weren’t sure how to do it.

I jumped at the chance to write something like this up (especially after all of my works on the PyBites platform) and so my wife volunteered me 😁

In order to really get my head wrapped around the problem, I wanted to treat my solution like a real world analog. For example, in a real work raffle, when you get your tickets, there are two tickets with the same number. One that you get to hold onto, and one that goes into a bowl (or other vessel) that is randomly drawn from.

How many tickets?

Each student had some number of Hero Points. The PTO decided that 10 Hero Points would equal 1 Raffle ticket. Further, it was decided that we would ALWAYS round up. This means that 1 Hero Point would equal 1 Raffle Ticket, but that 9 Hero Points would also equal 1 Raffle Ticket.

Create tickets

I decided to use a namedtuple to store the Raffle Tickets. Specifically, I store the student name, ticket numbers they drew, and the number of tickets they have

Raffle_Tickets = namedtuple('Raffle_Tickets', ['name', 'ticket_numbers', 'tickets'])

The list of student names and total Hero Points was stored in an Excel File (.xlsx) so I decided to use the Pandas Package to import it and manipulate it into a dataframe. The structure of the excel file is: Student Name, Grade, Available Points.

df = pd.read_excel (r'/Users/ryan/Documents/python-files/8th  Hero Points.xlsx')

After a bit of review it turned out that there were a couple of students with NEGATIVE Hero Points. I’m not really sure how that happened, but I was not properly accounting for that originally, so I had to update my dataframe.

The code below filters the dataframe to only return students with positive ‘Available Points’ and then reindex. Finally, it calculates the number of Raffle tickets by dividing by 10 and rounding up using Python’s ceil function. It puts all of this into a list called tickets. We append our tickets list to the original dataframe.

df = df[df['Available Points'] >0]
df.reset_index(inplace=True, drop=True)
tickets = []
for i in df['Available Points'] / 10:
df['Tickets'] = tickets

Our dataframe now looks like this: Student Name, Grade, Available Points, Tickets.

Next, we need to figure out the Raffle ticket numbers. To do that I count the total number of Tickets available. I’m also using some extra features of the range function which allows me to set the start number of the Raffle.1

total_number_of_tickets = sum(df['Tickets'])
ticket_number_start = 1000000
ticket_number_list = []
for i in range(ticket_number_start, ticket_number_start+total_number_of_tickets):

Once we have the list of ticket numbers I want to make a copy of it … remember there are two tickets, one that goes in the bowl and one that the student ‘gets’. Extending the metaphor of having two different, but related, tickets, I decided to use the deepcopy function on the ticket_number_list to create a list called assigned_ticket_number_list.

For more on deepcopy versus (shallow) copy see the documentation

assigned_ticket_number_list = deepcopy(ticket_number_list)

Finally, I reindex the dataframe just to add a bit more randomness to the list

df = df.reindex(np.random.permutation(df.index))

Assign Tickets

Next we’ll assign the tickets randomly to the students.

raffle_list = []
for student in range(df.shape[0]):
    student_ticket_list = []
    for i in range(df.loc[student].Tickets):
        assigned_ticket_number = randint(0, len(assigned_ticket_number_list)-1)
    raffle_list.append(Raffle_Tickets(df.loc[student].Name, student_ticket_list, len(student_ticket_list)))

OK … the code above looks pretty dense, but basically all we’re doing is looping through the students to determine the number of tickets they each have. Once we have that we loop through the available ticket numbers and randomly assign it to the student. At the end we add a namedtuple object called Raffle_Tickets that we defined above to the raffle_list to store the student’s name, their ticket numbers, and the number of tickets that they received.

Draw Tickets

Now we want to ‘draw’ the tickets from the ‘bowl’. We want to select 25 winners, but we also don’t want to have any student win more than once. Honestly, the ’25 winning tickets with 25 distinct winners’ was the hardest part to get through.

selected_tickets = []
for i in range(25):
    selected_ticket_number_index = randint(0, len(ticket_number_list) - 1)
    selected_ticket_number = ticket_number_list[selected_ticket_number_index]
    for r in raffle_list:
        if selected_ticket_number in r.ticket_numbers:
            ticket_number_list = [x for x in ticket_number_list if x not in r.ticket_numbers]

We see above that we’ll select 25 items from the ‘bowl’ of tickets. We select the tickets one at a time. For each ticket we determine what set of tickets that selected ticket is in. Once we know that, we then remove all tickets associated with that winning ticket so that we can guarantee 25 unique winners.

Find the Winners

We now have 25 tickets with 25 winners. Now we just need to get their names!

for r in raffle_list:
    for t in r.ticket_numbers:
        student_winning_list = []
        if t in selected_tickets:
            winners_list.append((Raffle_Tickets(, student_winning_list, len(student_winning_list))))

Again, we construct a list of namedtuple Raffle\_Tickets only this time it’s just the winners.

Output winners

Whew! Now that we have the results we want to write them to a file.

with open('/Users/ryan/PyBites/Raffle/winners_new.txt', 'w+') as f:
    for winner in winners_list:
        tickets = ticket_count(
        percent_chance_of_winning = tickets / total_number_of_tickets * 100
        percent_chance_of_winning_string = "{:.2f}".format(percent_chance_of_winning)
        f.write(f'{} with winning ticket {winner.ticket_numbers[0]}. They had {tickets} tickets and a {percent_chance_of_winning_string}% chance of winning.\n')

One of the reasons that I stored the number of tickets above was so that we could see what the chance was of a student winning given the number of tickets they started with.

For each student we output to a line to a file with the student’s name, the winning tickets number, the number of tickets they started with and their chance of winning (the ratio of tickets the student had to the total number of starting tickets)


This was a fun project for me because it was needed for a real world application, allowed me to use MANY of the concepts I learned at PyBites AND helped my daughter’s school.

  1. Why am I doing this, versus just stating a 0? Mostly because I wanted the Raffle Ticket numbers to look like real Raffle Ticket Numbers. How many times have you seen a raffle ticket with number 0 on it?
PyCharm Python

Issues with psycopg2 … again

In a previous post I had written about an issue I’d had with upgrading, installing, or just generally maintaining the python package psycopg2 (link).

I ran into that issue again today, and thought to myself, “Hey, I’ve had this problem before AND wrote something up about it. Let me go see what I did last time.”

I searched my site for psycopg2 and tried the solution, but I got the same forking error.

OK … let’s turn to the experts on the internet.

After a while I came across this article on StackOverflow but this specific answer helped get me up and running.

A side effect of all of this is that I upgraded from Python 3.7.5 to Python 3.8.1. I also updated all of my brew packages, and basically did a lot of cleaning up that I had neglected.

Not how I expected to spend my morning, but productive nonetheless.

Django Python

My First Django Project

I’ve been writing code for about 15 years (on and off) and Python for about 4 or 5 years. With Python it’s mostly small scripts and such. I’ve never considered myself a ‘real programmer’ (Python or otherwise).

About a year ago, I decided to change that (for Python at the very least) when I set out to do 100 Days Of Web in Python from Talk Python To Me. Part of that course were two sections taught by Bob regarding Django. I had tried learn Flask before and found it … overwhelming to say the least.

Sure, you could get a ‘hello world’ app in 5 lines of code, but then what? If you wanted to do just about anything it required ‘something’ else.

I had tried Django before, but wasn’t able to get over the ‘hump’ of deploying. Watching the Django section in the course made it just click for me. Finally, a tool to help me make AND deploy something! But what?

The Django App I wanted to create

A small project I had done previously was to write a short script for my Raspberry Pi to tell me when LA Dodger (Baseball) games were on (it also has beloved Dodger Announcer Vin Scully say his catch phrase, “It’s time for Dodger baseball!!!”).

I love the Dodgers. But I also love baseball. I love baseball so much I have on my bucket list a trip to visit all 30 MLB stadia. Given my love of baseball, and my new found fondness of Django, I thought I could write something to keep track of visited stadia. I mean, how hard could it really be?

What does it do?

My Django Site uses the MLB API to search for games and allows a user to indicate a game seen in person. This allows them to track which stadia you’ve been to. My site is composed of 4 apps:

  • Users
  • Content
  • API
  • Stadium Tracker

The API is written using Django Rest Framework (DRF) and is super simple to implement. It’s also really easy to changes to your models if you need to.

The Users app was inspired by Will S Vincent ( a member of the Django Software Foundation, author, and podcaster). He (and others) recommend creating a custom user model to more easily extend the User model later on. Almost all of what’s in my Users App is directly taken from his recommendations.

The Content App was created to allow me to update the home page, and about page (and any other content based page) using the database instead of updating html in a template.

The last App, and the reason for the site itself, is the Stadium Tracker! I created a search tool that allows a user to find a game on a specific day between two teams. Once found, the user can add that game to ‘Games Seen’. This will then update the list of games seen for that user AND mark the location of the game as a stadium visited. The best part is that because the game is from the MLB API I can do some interesting things:

  1. I can get the actual stadium from visited which allows the user to indicate historic (i.e. retired) stadia
  2. I can get details of the game (final score, hits, runs, errors, stories from MLB, etc) and display them on a details page.

That’s great and all, but what does it look like?

The Search Tool

Stadia Listing

National League West

American League West

What’s next?

I had created a roadmap at one point and was able to get through some (but not all) of those items. Items left to do:

  • Get Test coverage to at least 80% across the app (currently sits at 70%)
  • Allow users to be based on social networks (right now I’m looking at Twitter, and Instagram) probably with the Django Allauth Package
  • Add ability to for minor league team search and stadium tracking (this is already part of the MLB API, I just never implemented it)
  • Allow user to search for range of dates for teams
  • Update the theme … it’s the default MUI CSS which is nice, but I’d rather it was something a little bit different
  • Convert Swagger implementation from django-rest-swagger to drf-yasg

Final Thoughts

Writing this app did several things for me.

First, it removed some of the tutorial paralysis that I felt. Until I wrote this I didn’t think I was a web programmer (and I still don’t really), and therefore had no business writing a web app.

Second, it taught me how to use git more effectively. This directly lead to me contributing to Django itself (in a very small way via updates to documentation). It also allowed me to feel comfortable enough to write my first post on this very blog.

Finally, it introduced me to the wonderful ecosystem around Django. There is so much to learn, but the great thing is that EVERYONE is learning something. There isn’t anyone that knows it all which makes it easier to ask questions! And helps me in feeling more confident to answer questions when asked.

The site is deployed on Heroku and can be seen here. The code for the site can be seen here.

This article was also posted on the Blog

Django PyCharm Python

Mischief Managed

A few weeks back I decided to try and update my Python version with Homebrew. I had already been through an issue where the an update like this was going to cause an issue, but I also knew what the fix was.

With this knowledge in hand I happily performed the update. To my surprise, 2 things happened:

  1. The update seemed to have me go from Python 3.7.6 to 3.7.3
  2. When trying to reestablish my Virtual Environment two packages wouldn’t installed: psycopg2 and django-heroku

Now, the update/backdate isn’t the end of the world. Quite honestly, next weekend I’m going to just ditch homebrew and go with the standard download from because I’m hoping that this non-sense won’t be an issue anymore

The second issue was a bit more irritating though. I spent several hours trying to figure out what the problem was, only to find out, there wasn’t one really.

The ‘fix’ to the issue was to

  1. Open PyCharm
  2. Go to Setting
  3. Go to ‘Project Interpreter’
  4. Click the ‘+’ to add a package
  5. Look for the package that wouldn’t install
  6. Click ‘Install Package’
  7. Viola … mischief managed

The next time this happens I’m just buying a new computer

PyCharm Python

Fixing a PyCharm issue when updating Python made via HomeBrew

I’ve written before about how easy it is to update your version of Python using homebrew. And it totally is easy.

The thing that isn’t super clear is that when you do update Python via Homebrew, it seems to break your virtual environments in PyCharm. 🤦‍♂️

I did a bit of searching to find this nice post on the JetBrains forum which indicated

unfortunately it’s a known issue: . Please close Pycharm and remove jdk.table.xml file from ~/Library/Preferences/.PyCharm2018.1/options directory, then start Pycharm again.

OK. I removed the file, but then you have to rebuild the virtual environments because that file is what stores PyCharms knowledge of those virtual environments.

In order to get you back to where you need to be, do the following (after removing the jdk.table.xml file:

  1. pip-freeze > requirements.txt
  2. Remove old virtual environment rm -r venv
  3. Create a new Virtual Environemtn with PyCharm
    1. Go to Preferences
    2. Project > Project Interpreter
    3. Show All
    4. Click ‘+’ button
  4. pip install -r requirements.txt
  5. Restart PyCharm
  6. You’re back

This is a giant PITA but thankfully it didn’t take too much to find the issue, nor to fix it. With that being said, I totally shouldn’t have to do this. But I’m writing it down so that once Python 3.8 is available I’ll be able to remember what I did to fix going from Python 3.7.1 to 3.7.5.

100DaysOfCode Python

My Experience with the 100 Days of Web in Python

As soon as I discovered the Talk Python to me Podcast, I discovered the Talk Python to me courses. Through my job I have a basically free subscription to PluralSight so I wasn’t sure that I needed to pay for the courses when I was effectively getting courses in Python for free.

After taking a couple ( well, truth be told, all ) of the Python courses at PluralSight, I decided, what the heck, the courses at Talk Python looked interesting, Michael Kennedy has a good instructor’s voice and is genuinely excited about Python, and if it didn’t work out, it didn’t work out.

I’m so glad I did, and I’m so glad I went through the 100 Days of Web in Python course.

On May 2, 2019 I saw that the course had been released and I tweeted

This x 1000000! Thank you so much @TalkPython. I can’t wait to get started!

I started on the course on May 4, 2019 and completed it August 11, 2019. Full details on the course are here.

Of the 28 concepts that were reviewed over the course, my favorites things were learning Django and Django Rest Framework and Pelican. Holy crap, those parts were just so much fun for me. Part of my interest in Django and DRF comes from William S Vincent’s books and Podcast Django Chat, but having actual videos to watch to get me through some of the things that have been conceptually tougher for me was a godsend.

The other part that I really liked was actual deployment to a server. I had tried (about 16 months ago) to deploy a Django app to Digital Ocean and it was an unmitigated disaster. No static files no matter what I did. I eventually gave up.

In this course I really learned how to deploy to both Heroku and a Linux box on Digital Ocean, and so now I feel much more confident that the app I’m working on (more on that below) will actually see the light of day on something other than a dev machine!

The one thing that I started to build (and am continuing to work on) is an app with a DRF backend and a Vue.js front end that allows a user to track which Baseball stadia they’ve been to. So far I have an API set up via DRF (hosted at Heroku) and sketches of what to do in Vue.js. There’s also a Django front end (but it’s not the solution I really want to use).

Writing code for 100 days is hard. Like really hard. For nearly 20 of those days I was on a family vacation in the Mid Western part of the US, but I made time for both the coding, and my family. My family was super supportive of my goal which was helpful, but the content in the course was really interesting and challenging and made me want to do it every day, which was also super helpful.

On day 85 I got a video from Bob that helped get me through the last 2 weeks. It was encouraging, and helpful which is just what I needed. So thank you Bob.

At the end I also got a nice congratulatory video from Julian, which was surprising to say the least, especially because he called out some of the things that I tweeted that I enjoyed about the class, addressed me by name, and just genuinely made me feel good about my accomplishment!

OK. I just wrapped up the 100 Days of Code with Python and the web. Now what?

I took a week off to recuperate and am now ready to ‘get back to it’.

After all, I’ve got baseball stadia to track in my app!

Talk Python to me Podcast

Why I like the Talk Python Podcast

When I started listening to it

Listening to the back catalog (nearly all of it)


Upgrading Python in a Virtual Environment

I have been wanting to use my Heroku account for a while with something a little more interesting than a Jupiter Notebook.

I was hoping to try and do something with Django … but there’s a lot to using Django. I have some interesting things I’m doing on my local machine, but it’s not quite ready yet.

I had googled to find other Python Web frameworks and saw that Bottle was an even more light weight framework than Flask, so I thought, hey, maybe I can do something with that.

I found this tutorial on how to do something relatively simple with Bottle and deploying to Heroku. Just what I wanted!

I got through to the end of the tutorial and deployed to Heroku. The terminal output from the Heroku command indicated that a newer version of Python (3.7.3) was available than the one I was on (3.7.1).

I figured it would be easy enough to upgrade to the newest version of Python on my Mac because I had done it before.

I don’t know why I thought the virtual environment would be different than the local install of Python 3 but it turns out they are more tightly coupled than I thought.

Upgrading to 3.7.3 broke the virtual environment I had in PyCharm. I did a bit a googling to see how to upgrade a virtual environment and found nothing. Like literally nothing.

It was … disheartening. But after a good night’s sleep I had a thought! What if I just delete the virtual environment directory and then recreated it.

I ran this command to remove the virtual environment:

rm -R venv

Then created a virtual environment in PyCharm and now I have 3.7.3 in my virtual environment.

I had to make some changes to the files for deployment to Heroku, but that’s all covered in the tutorial mentioned above.

Sometimes the answer is to just restart it … and sometimes the answer is delete it and start over.


I was listening to an episode of Python Bytes and heard Michael Kennedy (of Talk Python to Me fame) describing basically the same issue I had. Turns out, he solved it the same way I did. Nice to know i’m In good company.


Keeping Python up to date on macOS

Sometimes the internet is a horrible, awful, ugly thing. And then other times, it’s exactly what you need.

I have 2 Raspberry Pi each with different versions of Python. One running python 3.4.2 and the other running Python 3.5.3. I have previously tried to upgrade the version of the Pi running 3.5.3 to a more recent version (in this case 3.6.1) and read 10s of articles on how to do it. It did not go well. Parts seemed to have worked, while others didn’t. I have 3.6.1 installed, but in order to run it I have to issue the command python3.6 which is fine but not really what I was looking for.

For whatever reason, although I do nearly all of my Python development on my Mac, it hadn’t occurred to me to upgrade Python there until last night.

With a simple Google search the first result came to Stackoverflow (what else?) and this answer.

brew update
brew upgrade python3

Sometimes things on a Mac do ‘just work’. This was one of those times.

I’m now running Python 3.7.1 and I’ll I needed to do was a simple command in the terminal.

God bless the internet.

PyCharm Python

Moving my Pycharm Directory or How I spent my Saturday after jacking up my PyCharm environment

Every once in a while I get a wild hair and decide that I need to ‘clean up’ my directories. This never ends well and I almost always mess up something, but I still do it.

Why? I’m not sure, except that I forget that I’ll screw it up. 🤦‍♂️

Anyway, on a Saturday morning when I had nothing but time I decided that I’d move my PyCharm directory from /Users/ryan/PyCharm to /Users/ryan/Documents/PyCharm for no other reason than because.

I proceeded to use the command line to move the folder

mv /Users/ryan/PyCharm/ /Users/ryan/Documents/PyCharm/

Nothing too big, right. Just a simple file movement.

Not so much. I then tried to open a project in PyCharm and it promptly freaked out. Since I use virtual environments for my Python Project AND they tend to have paths that reference where they exist, suddenly ALL of my virtual environments were kind of just gone.


OK. No big deal. I just undid my move

mv /Users/ryan/Documents/PyCharm/ /Users/ryan/PyCharm

That should fix me up, right?

Well, mostly. I had to re-register the virtual environments and reinstall all of the packages in my projects (mostly not a big deal with PyCharm) but holy crap it was scary. I thought I had hosed my entire set of projects (not that I have anything that’s critical … but still).

Anyway, this is mostly a note to myself.

The next time you get a wild hair to move stuff around, just keep it where it is. There’s no reason for it (unless there is).

But seriously, ask yourself first, “If I don’t move this what will happen?” If the answer is anything less than “Something awful” go watch a baseball game, or go to the pool, or write some code. Don’t mess with your environment unless you really want to spend a couple of hours unmasking it up!