code review prep

1_development_workflows/deliverables.md

@@ -9,7 +9,8 @@ interests, and anything else you'd like to share.
 
 - [ ] You created your Profile README repository using
       [the template `username` repository](https://github.com/MIT-Emerging-Talent/username)
-- [ ] All of the CI checks pass under the Actions tab
+- [ ] Your repository’s name matches your GitHub username.
+- [ ] All of the CI checks pass under the Actions tab. _Or_ you commented the lines that failed CI checks explaining why you broke the rule to get the README you wanted. (eg. “I used HTML to align the image in the center”)
 
 ## Suggested Study
 

2_predictive_stepping/README.md

@@ -40,7 +40,7 @@ then communicating with everyone involved to deliver quality software within
 your project's constraints. This diagram shows the different channels of
 communication in a simple Python program:
 
-![a program](./.assets/what_is_programming.png)
+![a program](../.assets/what_is_programming.png)
 
 > PS. In the examples and exercises for this chapter you will be both the
 > developer and the user, running the program and interacting with it from

2_predictive_stepping/lesson_plan.md

@@ -59,7 +59,7 @@ class: center
 
 ## What is Programming?
 
-<img alt="What is programming?" src="./.assets/what_is_programming.png" height="100%"  width="100%">
+<img alt="What is programming?" src="../.assets/what_is_programming.png" height="100%"  width="100%">
 
 ---
 

3_documenting_and_testing/behavior_strategy_implementation.md

@@ -113,14 +113,14 @@ for index in range(2, 500):
 
     assert two_back + one_back == current, f"entry {index} is not correct"
 
-# %% does the function return the same or different arrays?
+# %% does the function return the same or different lists?
 
-array_1 = fibonacci_list(4)
-array_2 = fibonacci_list(6)
+list_1 = fibonacci_list(4)
+list_2 = fibonacci_list(6)
 
-# the function returned two different arrays with the same values
-assert array_1 == array_2, "the arrays store the same values"
-assert array_1 is not array_2, "the variables do not reference the same array"
+# the function returned two different lists with the same values
+assert list_1 == list_2, "the lists store the same values"
+assert list_1 is not list_2, "the variables do not reference the same list"
 ```
 
 </details>

4_debugging/philosophy_of_debugging.md

@@ -143,7 +143,7 @@ simple. For the above example the symptom corresponds to the line where the
 variable went out of bounds or to the `print`s which produced the garbage output.
 The incorrect behavior will correspond to a variable with a bad value. Identify
 the variable(s) with bad values. For this example, suppose that the program
-crashes on line 112 because i is -1 and tries to index an array.
+crashes on line 112 because i is -1 and tries to index an list.
 
 The critical question is: where did i get its value? There are basically three
 ways a variable can get a value: the variable appears on the left hand side of a

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/0_docstring.py

@@ -3,7 +3,7 @@
 This function does not modify the argument list.
 
 Parameters:
-  list[dict[str, str]]: an array of dicts with string keys and string values
+  list[dict[str, str]]: an list of dicts with string keys and string values
   str: the function will remove all dicts that don't have this key
 
 Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/1a_generated_tests.py

@@ -7,7 +7,7 @@ def f(lst, key):
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/1b_manual_refactor_tests.py

@@ -7,7 +7,7 @@ def f(lst, key):
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/2b_manual_refactor_function.py

@@ -7,7 +7,7 @@ def f(lst, key):
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/2c_generated_refactor_function.py

@@ -8,7 +8,7 @@ def f(lst, key):
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/2d_manual_refactor_function.py

@@ -7,7 +7,7 @@ def f(lst, sort_key):
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

5_tdd_with_llms/examples/filter_and_sort_dictionaries_with_llm/3_polish_implementation.py

@@ -17,7 +17,7 @@ def filter_and_sort_dictionaries(
     This function does not modify the argument list.
 
     Parameters:
-      list[dict[str, str]]: an array of dicts with string keys and string values
+      list[dict[str, str]]: an list of dicts with string keys and string values
       str: the function will remove all dicts that don't have this key
 
     Returns: a list of dicts where each dict contains the given key,

6_recursion/2_visualize_recursion/exercises/count_items.py

@@ -12,7 +12,7 @@
 - comment @trace_recursion and debug the function
 or copy the function into one of these sites:
 - https://www.recursionvisualizer.com
-- (https://recursion.vercel.app
+- https://recursion.vercel.app
 - https://recursion-visualizer.vercel.app
 - https://visualgo.net/en/recursion
 

6_recursion/2_visualize_recursion/exercises/fibonacci.py

@@ -12,7 +12,7 @@
 - comment @trace_recursion and debug the function
 or copy the function into one of these sites:
 - https://www.recursionvisualizer.com
-- (https://recursion.vercel.app
+- https://recursion.vercel.app
 - https://recursion-visualizer.vercel.app
 - https://visualgo.net/en/recursion
 

6_recursion/2_visualize_recursion/exercises/fibonacci_memo.py

@@ -12,7 +12,7 @@
 - comment @trace_recursion and debug the function
 or copy the function into one of these sites:
 - https://www.recursionvisualizer.com
-- (https://recursion.vercel.app
+- https://recursion.vercel.app
 - https://recursion-visualizer.vercel.app
 - https://visualgo.net/en/recursion
 

6_recursion/3_use_recursion/1_debug/fibonacci.py

@@ -13,10 +13,7 @@
 
 @trace_recursion
 def fibonacci(n: int) -> int:
-    """
-    
-    """
-    if n < 0:
+    if n <= 0:
         return 0
 
     if n == 1:
@@ -30,6 +27,7 @@ def fibonacci(n: int) -> int:
 print(fibonacci(0), 'should be', 0)
 print(fibonacci(1), 'should be', 1)
 print(fibonacci(2), 'should be', 1)
+print(fibonacci(3), 'should be', 2)
 print(fibonacci(4), 'should be', 3)
 print(fibonacci(6), 'should be', 8)
 print(fibonacci(8), 'should be', 21)

6_recursion/3_use_recursion/1_debug/fibonacci_memo.py

@@ -34,6 +34,7 @@ def fibonacci_memo(n: int, memo: dict = {}) -> int:
 print(fibonacci_memo(0), 'should be', 0)
 print(fibonacci_memo(1), 'should be', 1)
 print(fibonacci_memo(2), 'should be', 1)
+print(fibonacci_memo(3), 'should be', 2)
 print(fibonacci_memo(4), 'should be', 3)
 print(fibonacci_memo(6), 'should be', 8)
 print(fibonacci_memo(8), 'should be', 21)

6_recursion/code_along_using_recursion.py

@@ -13,14 +13,6 @@
 
 @trace_recursion
 def reverse_list(to_reverse: list) -> list:
-    """
-    behavior description
-
-    base case :
-        argument description  ->  turn-around description
-    recursive case:
-        argument description  ->  ƒ(break-down description) build-up description 
-    """
     base_case = _ # must use to_reverse
     if base_case:
         turn_around = _
@@ -36,7 +28,6 @@ def reverse_list(to_reverse: list) -> list:
 
 
 print(reverse_list([]), 'should be', [])
-print(reverse_list([1]), 'should be', [1])
-print(reverse_list(['a', 'b']), 'should be', ['a', 'b'])
+print(reverse_list([1, 2]), 'should be', [2, 1])
 print(reverse_list([1, 2, 3]), 'should be', [3, 2, 1])
 print(reverse_list([3, 2, 1, 0, -1, -2, 3]), 'should be', [3, -2, -1, 0, 1, 2, 3])

6_recursion/lesson_plan.md

@@ -156,11 +156,11 @@ class: middle, center
 ```py
 # a recursive strategy for counting the items in a list
 def count_items(list_of_things: list) -> int:
-    # base case:  an empty array
+    # base case:  an empty list
     if len(list_of_things) == 0:
       return 0 # turn-around:  an empty list has 0 items
 
-    # break-down:  create an array with 1 fewer items
+    # break-down:  create an list with 1 fewer items
     list_without_last_item = list_of_things[:-1]
     # recursion:  recursively count items in the smaller list
     previously_counted = count_items(list_without_last_item)
@@ -217,10 +217,10 @@ def count_items(list_of_things: list) -> int:
   recursive case:
     a non-empty list ->  ƒ(the list one item removed) + 1
   """
-    if len(list_of_things) == 0: # base case
-      return 0 # turn-around
-    #         recursion,  break-down, build-up
-    return count_items(list_of_things[:-1]) + 1
+  if len(list_of_things) == 0: # base case
+    return 0 # turn-around
+  #         recursion,  break-down, build-up
+  return count_items(list_of_things[:-1]) + 1
 
 # use the recursive solution to count items in this list
 count_items(['a', 'b', 'c', 'd'])
@@ -260,14 +260,15 @@ class: middle, center
 # breaking down & recursing
 count_items(['a', 'b', 'c', 'd'])
 count_items(['a', 'b', 'c']) + 1
-count_items(['a', 'b']) + 1 + 1
-count_items(['a']) + 1 + 1 + 1
+(count_items(['a', 'b']) + 1) + 1
+((count_items(['a']) + 1) + 1) + 1
 # base case
-count_items([]) + 1 + 1 + 1 + 1
-# turning around & building up
-0 + 1 + 1 + 1 + 1
-1 + 1 + 1 + 1
-2 + 1 + 1
+(((count_items([]) + 1) + 1) + 1) + 1
+# turning around
+(((0 + 1) + 1) + 1) + 1
+# building up
+((1 + 1) + 1) + 1
+(2 + 1) + 1
 3 + 1
 4
 ```

7_code_review/README.md

@@ -9,7 +9,7 @@ colleague's code and let them know what is good, what could be better, and
 suggest improvements if you can. The most important thing to keep in mind when
 writing a code review is:
 
-- _Talk about the code, not the person._
+- _Review the code, not the person._
 
 If there is something you would change in the code don't say "_you_ used a bad
 variable name", say something like "_this variable name_ could be more clear".

7_code_review/deliverables.md

@@ -0,0 +1,22 @@
+# Deliverables
+
+Working in a shared repository, you will each:
+
+- push 2+ completed code challenges with documentation and tests
+- review 2+ of your classmates’ solutions using the code review checklist
+
+This is a chance to practice using GitHub features for code review, project management, and code quality automation.  What you learn in this exercise will prepare you for the group Data Science projects in the certificate program.  
+
+## Checklist
+
+- [ ] Your group used the repository we create for you
+- [ ] Your group’s collaboration documents are all completed
+- [ ] Your group’s project board is well-maintained
+- [ ] All issues and pull requests have the correct labels (if necessary) so they are easy to find
+- [ ] The code review checklist for each PR is completed before merging to `main`
+- [ ] Each pull request either passes CI checks, or the failing CI checks are discussed in code review
+- [ ] Each pull request is reviewed by at least one classmate using GitHub code review features before merging to `main`
+- [ ] All code review discussions are positive and constructive - _review the code, not the person_
+- [ ] Your group used helpful branch naming conventions
+
+!! **Note** !! _You will not be assessed on how hard your coding challenges are_ !! !!