generated from mwc/lab_dice
7bfef15ec7
full house. Then I imported them to play.py so they would be integrated into the game. OOP felt more comfortable than the data science problems, but was more challenging than the drawing projects since the feedback again is not visual. However, this feels like a middle ground between the two. I think that the use of something familiar, like Yahtzee was a huge help in this proess. I can conceptialize the adjustments I am making becasue I have done them before. Additionally, it felt like the steps for the game itself were very confusing, but the goals were managable. I understood how to piece together the goals and make the applicable. Looking ahead, I am anticipating the challenge of building out a game of my own. This is going to be a challenge! The part of OOP that I related to was the confines given (a game, a die, a goal) then the challenge being operating within them to accomplish tasks. Creating from sratch is tough! ... but not in a bad way. I will just ahve to establish my own confines/rules, then develop. It is a challenge to create from scratch when I have not mastered the rules yet. I look forward to continuing to develop this skill! If yahtzee was written in Unit 1, I would invision it to be well, a visual. The die itself would roll and that would act as the "roll." That being said, the goals and steps of winning the game seem like they are a little out of reach of Unit 1. It would be the rolling of the dice and that's it. If this was in Unit 2, the game may have been converted into a data set. The instances may have already been run and documented in a spreadsheet that was uploaded. Then that data would have been analyzed and plotted as data, rather than as a game. the goals could have been evaluated as statisical instacnes to be analyzed rather than turns to be played. |
||
|---|---|---|
| .commit_template | ||
| .gitignore | ||
| dice_stats.py | ||
| die.py | ||
| play.py | ||
| poetry.lock | ||
| pyproject.toml | ||
| yahtzee.py | ||
| yahtzee_goals.py | ||