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‎syllabus/badge_calc.ipynb‎

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"id": "fa6b2857",
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"metadata": {},
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"source": [
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"# Badge Calculations \n",
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"# Detailed Grade Calculations \n",
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"\n",
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"```{important} \n",
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"This page is generated with code and calculations, you can view them for more precise implementations of what the english sentences mean. \n",
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "51238030",
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"metadata": {
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"tags": [
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "c6f0b2ef",
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"metadata": {
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"tags": [
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"A 206"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"tags": [
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"4 community practice_makeup 1.0 0.857143 0.857143"
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"metadata": {},
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"tags": [

‎syllabus/badges.md‎

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extension: .md
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format_name: myst
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format_version: 0.13
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jupytext_version: 1.10.3
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jupytext_version: 1.15.1
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kernelspec:
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display_name: Python 3
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display_name: Python 3 (ipykernel)
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language: python
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name: python3
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---
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# Badge Procedures
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# Badge Deadlines and Procedures
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This page includes more visual versions of the information on the badge page. You should read both, but this one is often more helpful, because some of the processes take a lot of words to explain and make more sense with a diagram for a lot of people.
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```{code-cell} ipython3
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%matplotlib inline
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import os
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from datetime import date,timedelta
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import calendar
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import pandas as pd
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import numpy as np
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import seaborn as sns
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from myst_nb import glue
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# style note: when I wrote this code, it was not all one cell. I merged the cells
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# for display on the course website, since Python is not the main outcome of this course
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# semester settings
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first_day = date(2023,9,5)
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last_day = date(2023,12,12)
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no_class_ranges = [(date(2023,11,23),date(2023,11,26)),
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(date(2023,11,13)),
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(date(2023,10,10))]
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meeting_days =[1,3] # datetime has 0=Monday
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spring_break = (date(2023,3,11),date(2023,3,19))
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penalty_free_end = date(2023, 9, 28)
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def day_off(cur_date,skip_range_list):
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'''
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is the current date a day off?
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Parameters
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----------
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cur_date : datetime.date
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date to check
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skip_range_list : list of datetime.date objects or 2-tuples of datetime.date
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dates where there is no class, either single dates or ranges specified by a tuple
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Returns
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-------
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day_is_off : bool
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True if the day is off, False if the day has class
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'''
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# default to not a day off
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day_is_off=False
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#
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for skip_range in skip_range_list:
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if type(skip_range) == tuple:
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# if any of the conditions are true that increments and it will never go down, flase=0, true=1
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day_is_off += skip_range[0]<=cur_date<=skip_range[1]
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else:
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day_is_off += skip_range == cur_date
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#
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return day_is_off
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# enumerate weeks
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meeting_days =[1,3] # spring
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mtg_delta = timedelta(meeting_days[1]-meeting_days[0])
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week_delta = timedelta(7)
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during_sb = lambda d: spring_break[0]<d<spring_break[1]
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possible = [(first_day+week_delta*w, first_day+mtg_delta+week_delta*w) for w in range(weeks)]
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weekly_meetings = [[c1,c2] for c1,c2 in possible if not(day_off(c1,no_class_ranges))]
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meetings = [m for w in weekly_meetings for m in w]
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meetings_string = [m.isoformat() for m in meetings]
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weekly_meetings
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# possible = [(first_day+week_delta*w, first_day+mtg_delta+week_delta*w) for w in range(weeks)]
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# weekly_meetings = [[c1,c2] for c1,c2 in possible if not(during_sb(c1))]
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meetings = [m for w in weekly_meetings for m in w if not(m in skips)]
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# build a table for the dates
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badge_types = ['experience', 'review', 'practice']
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target_cols = ['review_target','practice_target']
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df_cols = badge_types + target_cols
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badge_target_df = pd.DataFrame(index=meetings, data=[['future']*len(df_cols)]*len(meetings),
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columns=df_cols).reset_index().rename(
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columns={'index': 'date'})
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# set relative dates
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today = date.today()
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start_deadline = date.today() - timedelta(7)
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complete_deadline = date.today() - timedelta(14)
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# mark eligible experience badges
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badge_target_df['experience'][badge_target_df['date'] <= today] = 'eligible'
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# mark targets, cascading from most recent to oldest to not have to check < and >
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badge_target_df['review_target'][badge_target_df['date'] <= today] = 'active'
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badge_target_df['practice_target'][badge_target_df['date'] <= today] = 'active'
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badge_target_df['review_target'][badge_target_df['date']
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<= start_deadline] = 'started'
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badge_target_df['practice_target'][badge_target_df['date']
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<= start_deadline] = 'started'
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badge_target_df['review_target'][badge_target_df['date']
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<= complete_deadline] = 'completed'
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badge_target_df['practice_target'][badge_target_df['date']
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<= complete_deadline] = 'completed'
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# mark enforced deadlines
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badge_target_df['review'][badge_target_df['date'] <= today] = 'active'
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badge_target_df['practice'][badge_target_df['date'] <= today] = 'active'
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badge_target_df['review'][badge_target_df['date']
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<= start_deadline] = 'started'
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badge_target_df['practice'][badge_target_df['date']
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<= start_deadline] = 'started'
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badge_target_df['review'][badge_target_df['date']
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<= complete_deadline] = 'completed'
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badge_target_df['practice'][badge_target_df['date']
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<= complete_deadline] = 'completed'
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badge_target_df['review'][badge_target_df['date']
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<= penalty_free_end] = 'penalty free'
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badge_target_df['practice'][badge_target_df['date']
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<= penalty_free_end] = 'penalty free'
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# convert to numbers and set dates as index for heatmap compatibility
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status_numbers_hm = {status:i+1 for i,status in enumerate(['future','eligible','active','penalty free','started','completed'])}
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badge_target_df_hm = badge_target_df.replace(status_numbers_hm).set_index('date')
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# set column names to shorter ones to fit better
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badge_target_df_hm = badge_target_df_hm.rename(columns={'review':'review(e)','practice':'practice(e)',
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'review_target':'review(t)','practice_target':'practice(t)',})
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# build a custom color bar
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n_statuses = len(status_numbers_hm.keys())
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manual_palette = [sns.color_palette("pastel", 10)[7],
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sns.color_palette("colorblind", 10)[2],
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sns.color_palette("muted", 10)[2],
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sns.color_palette("colorblind", 10)[9],
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sns.color_palette("colorblind", 10)[8],
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sns.color_palette("colorblind", 10)[3]]
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# generate the figure, with the colorbar and spacing
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ax = sns.heatmap(badge_target_df_hm,cmap=manual_palette,linewidths=1)
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# mote titles from bottom tot op
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ax.xaxis.tick_top()
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# pull the colorbar object for handling
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colorbar = ax.collections[0].colorbar
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# fix the location fo the labels on the colorbar
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r = colorbar.vmax - colorbar.vmin
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colorbar.set_ticks([colorbar.vmin + r / n_statuses * (0.5 + i) for i in range(n_statuses)])
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colorbar.set_ticklabels(list(status_numbers_hm.keys()))
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# add a title
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today_string = today.isoformat()
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glue('today',today_string,display=False)
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glue('today_notdisplayed',"not today",display=False)
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ax.set_title('Badge Status as of '+ today_string);
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```
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## Prepare work and Experience Badges Process
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```{warning}
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Where the "approved" tag represents and approving reivew on the PR.
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## Review and Practice Badge
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rev --> approved[Dr. Brown approves] --> merge[Merge the PR]
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merge --o earned
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```
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```
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```{code-cell} ipython3
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```

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