Implement find_level, which takes a tree t and an integer level and returns a list of all the values that have depth level. If no such values exist, return the empty list. For a refresher on the depth of a node, check out here.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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### Python Code: Tree Data Structure

This section presents a Python implementation of a simple tree data structure. The code defines a `Tree` class with methods for initialization, representation, and string conversion.

```python
class Tree:
    def __init__(self, value, branches=()):
        self.value = value
        for branch in branches:
            assert isinstance(branch, Tree)
        self.branches = list(branches)

    def __repr__(self):
        if self.branches:
            branches_str = ', ' + repr(self.branches)
        else:
            branches_str = ''
        return 'Tree({0}{1})'.format(self.value, branches_str)

    def __str__(self):
        def print_tree(t, indent=0):
            tree_str = ' ' * indent + str(t.value) + "\n"
            for b in t.branches:
                tree_str += print_tree(b, indent + 1)
            return tree_str
```

### Explanation

- **Class Definition:**
  - `Tree`: Represents a tree node with a value and optional branches (children), initialized as an empty tuple by default.

- **Initialization Method:**
  - `__init__(self, value, branches=())`: Initializes a tree node with a provided value and optional list of branches. It ensures all branches are instances of the `Tree` class.

- **Representation Method:**
  - `__repr__(self)`: Returns a string representing the tree, displaying its value and branches.

- **String Conversion Method:**
  - `__str__(self)`: Provides a formatted string representation of the tree, with each level of the tree indented for clarity.

The `print_tree` function within the `__str__` method helps recursively construct a visual representation of the tree structure, enhancing readability and providing insights into the hierarchical relationships within the tree.
Transcribed Image Text:### Python Code: Tree Data Structure This section presents a Python implementation of a simple tree data structure. The code defines a `Tree` class with methods for initialization, representation, and string conversion. ```python class Tree: def __init__(self, value, branches=()): self.value = value for branch in branches: assert isinstance(branch, Tree) self.branches = list(branches) def __repr__(self): if self.branches: branches_str = ', ' + repr(self.branches) else: branches_str = '' return 'Tree({0}{1})'.format(self.value, branches_str) def __str__(self): def print_tree(t, indent=0): tree_str = ' ' * indent + str(t.value) + "\n" for b in t.branches: tree_str += print_tree(b, indent + 1) return tree_str ``` ### Explanation - **Class Definition:** - `Tree`: Represents a tree node with a value and optional branches (children), initialized as an empty tuple by default. - **Initialization Method:** - `__init__(self, value, branches=())`: Initializes a tree node with a provided value and optional list of branches. It ensures all branches are instances of the `Tree` class. - **Representation Method:** - `__repr__(self)`: Returns a string representing the tree, displaying its value and branches. - **String Conversion Method:** - `__str__(self)`: Provides a formatted string representation of the tree, with each level of the tree indented for clarity. The `print_tree` function within the `__str__` method helps recursively construct a visual representation of the tree structure, enhancing readability and providing insights into the hierarchical relationships within the tree.
**Question 3: Find Level**

Implement `find_level`, which takes a tree `t` and an integer `level` and returns a list of all the values that have depth `level`. If no such values exist, return the empty list. For a refresher on the depth of a node, check out [here](#).

```python
def find_level(t, level):
    """
    >>> t = Tree(1, [Tree(2, [Tree(4), Tree(5)]), Tree(6, [Tree(7)])])
    >>> find_level(t, 2)
    [4, 5, 7]
    >>> find_level(t, 1)
    [2, 6]
    >>> find_level(t, 5)
    []
    """
    "*** YOUR CODE HERE ***"
```

In this section, you are tasked with completing the function `find_level` to identify elements at a specific depth in a tree data structure. The examples show how the function should behave given a tree and a specified depth level.
Transcribed Image Text:**Question 3: Find Level** Implement `find_level`, which takes a tree `t` and an integer `level` and returns a list of all the values that have depth `level`. If no such values exist, return the empty list. For a refresher on the depth of a node, check out [here](#). ```python def find_level(t, level): """ >>> t = Tree(1, [Tree(2, [Tree(4), Tree(5)]), Tree(6, [Tree(7)])]) >>> find_level(t, 2) [4, 5, 7] >>> find_level(t, 1) [2, 6] >>> find_level(t, 5) [] """ "*** YOUR CODE HERE ***" ``` In this section, you are tasked with completing the function `find_level` to identify elements at a specific depth in a tree data structure. The examples show how the function should behave given a tree and a specified depth level.
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