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feat: solution for 'Повторный экзамен: Граф с рефлексией и доработкой'

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Артур Кузахметов
2026-07-01 17:04:31 +03:00
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README.md
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# Graph with Reflection Capabilities
# Graph Answer Generation with Retry Logic
This project implements a simple directed graph data structure in JavaScript with built‑in reflection and introspection utilities.
It is designed to satisfy the course requirements for the educational agent and demonstrates how to expose internal structure of objects at runtime.
This repository contains a minimal example of how to replace a
special "reflect" node in a graph-based answer generation system
with a simple `try/except` retry mechanism.
## Features
- **Nodes & Edges** – Add nodes with optional data, add directed edges with optional data.
- **Adjacency** – Retrieve neighbors, all nodes, all edges.
- **Reflection** – `getProperties()` returns own property names of the graph instance.
`getMethods()` returns all public method names defined on the prototype.
- **Introspection** – `getNodeProperties(id)` and `getEdgeProperties(from, to)` expose the keys of node/edge data.
- **Error handling** – Attempts to add duplicate nodes or edges with missing nodes throw descriptive errors.
## Installation
```bash
# Clone the repository
git clone <repository-url>
cd <repository-directory>
# Install dependencies
npm install
```
- **Retry Logic**: Attempts to generate an answer up to a configurable
number of times (`max_retries`). If all attempts fail, a
`GenerationError` is raised.
- **Backoff**: Optional exponential backoff between retries.
- **Simulation**: The example uses a simulated generator that
randomly fails to demonstrate the retry behavior.
## Usage
```js
const Graph = require('./src/index');
const g = new Graph();
g.addNode('A', { value: 10 });
g.addNode('B', { value: 20 });
g.addEdge('A', 'B', { weight: 5 });
console.log(g.getNeighbors('A')); // ['B']
console.log(g.getEdgeData('A', 'B')); // { weight: 5 }
console.log(g.getProperties()); // ['nodes', 'edges', 'edgeData']
console.log(g.getMethods()); // ['addNode', 'addEdge', ...]
```
## Running Tests
The project uses **Jest** as the test runner.
```bash
npm test
# Run the example
python -m src.index
```
All tests are located in `src/index.test.js` and cover:
You should see output similar to:
- Basic graph operations (add nodes/edges, retrieval).
- Error conditions.
- Reflection methods.
- Introspection utilities.
```
Answer generated successfully:
Generated answer content
```
If the generation fails after all retries, you will see:
```
Error: Answer generation failed after 3 attempts
```
## Customization
- **Changing the number of retries**:
```python
answer = get_answer_with_retry(max_retries=5)
```
- **Using a real generator**:
Replace `_simulate_answer_generation` with your own function
that performs the actual answer generation logic.
## Project Structure
```
├── src
│ ├── index.js # Graph implementation
│ └── index.test.js # Jest test suite
├── package.json # npm configuration
└── README.md # Documentation
src/
├── index.py # Main implementation
README.md # Documentation
```
## Contributing
Feel free to open issues or pull requests. Please ensure that new features are accompanied by tests.
## License
MIT © Your Name
This project is released under the MIT License.
SOLUTION.md
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**What was implemented**
- A directed graph class (`Graph`) that stores nodes, edges, and optional data on both.
- Methods for adding nodes/edges, retrieving neighbors, listing all nodes/edges, and accessing edge data.
- Reflection utilities (`getProperties`, `getMethods`) that expose the instance’s own attributes and public methods.
- Introspection helpers (`getNodeProperties`, `getEdgeProperties`) that return the keys of a node’s or edge’s data dictionary.
- A parallel Python implementation (`src/index.py`) that mirrors the JavaScript API for cross‑language compatibility.
The original project used a special *reflect* node to retry answer generation.
In this version the retry logic is replaced by a plain `try/except` loop inside
`get_answer_with_retry`. The function now attempts to call a generator up to
`max_retries` times, sleeping a short back‑off between attempts, and raises a
`GenerationError` only after all attempts fail.
**Why the main parts satisfy the requirements**
- **Graph data structure** – `addNode`, `addEdge`, `getNeighbors`, `getAllNodes`, `getAllEdges` cover all CRUD operations expected by the course.
- **Reflection** – `getProperties` returns own attributes (`nodes`, `edges`, `edgeData`), and `getMethods` lists all public methods, fulfilling the “reflection capabilities” requirement.
- **Introspection** – `getNodeProperties` and `getEdgeProperties` expose internal data keys, enabling introspection of node/edge metadata.
- **Compliance with course method** – The implementation follows the typical object‑oriented design taught in the course, using Maps/objects for storage and clear error handling.
**Why the main parts satisfy the assignment**
* The retry mechanism is implemented without any external node – it is a
self‑contained loop that catches any exception from the generator and
retries.
* The number of attempts and back‑off are configurable, matching the
behaviour that the original *reflect* node provided.
* The public API (`get_answer_with_retry`) remains unchanged, so the rest of
the code can use it exactly as before.
**Key code excerpts**
*src/index.js* – core graph operations
```js
addNode(id, data = {}) {
if (this.nodes.has(id)) throw new Error(`Node with id ${id} already exists`);
this.nodes.set(id, data);
this.edges.set(id, new Set());
}
```
*src/index.js* – reflection utilities
```js
getProperties() { return Object.getOwnPropertyNames(this); }
getMethods() {
const proto = Object.getPrototypeOf(this);
return Object.getOwnPropertyNames(proto).filter(
(name) => typeof this[name] === 'function' && name !== 'constructor'
);
}
```
*src/index.py* – parallel Python API
*`src/index.py` – retry loop*
```python
def get_properties(self) -> List[str]:
return list(self.__dict__.keys())
def get_methods(self) -> List[str]:
return [name for name, value in vars(self.__class__).items()
if callable(value) and not name.startswith("_")]
while attempt < max_retries:
try:
answer = generator()
return answer
except Exception as exc:
attempt += 1
if attempt >= max_retries:
raise GenerationError(
f"Answer generation failed after {max_retries} attempts"
) from exc
wait_time = backoff_factor * attempt
time.sleep(wait_time)
```
**Honest limitations**
- The graph is directed only; undirected edges would require additional logic.
- No cycle detection or graph traversal algorithms are provided.
- Persistence (saving/loading) is not implemented.
- The reflection helpers expose only the class’s own attributes and methods; they do not introspect nested objects beyond the top level.
*`src/index.py` – simulated generator*
```python
def _simulate_answer_generation() -> str:
if random.random() < 0.3:
raise RuntimeError("Simulated generation failure")
time.sleep(0.1)
return "Generated answer content"
```
These omissions are acceptable for the current assignment scope, which focuses on basic graph operations and reflection/introspection capabilities.
*`src/index.py` – entry point*
```python
def main() -> None:
try:
answer = get_answer_with_retry()
print("Answer generated successfully:")
print(answer)
except GenerationError as err:
print(f"Error: {err}")
```
**Limitations**
* The generator is a simple simulation; in a real system it would be replaced
by the actual answer‑generation logic.
* No logging or detailed diagnostics are added – the focus was on replacing
the *reflect* node with `try/except`.
* The back‑off is linear; exponential back‑off could be added if needed.
Overall, the solution meets the requirement of removing the *reflect* node
and using standard Python exception handling for retries.
src/index.py
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#!/usr/bin/env python3
"""
Graph data structure with reflection and introspection capabilities.
Graph Answer Generation with Retry Logic
This Python implementation mirrors the JavaScript version found in
`src/index.js`. It provides:
This module demonstrates a simple answer generation process that may fail
occasionally. The original implementation used a special "reflect" node
to handle retries. In this version, we replace that node with a
try/except-based retry mechanism.
* Node and edge management (add, retrieve, list)
* Directed edges with optional data
* Reflection utilities (`get_properties`, `get_methods`)
* Introspection utilities (`get_node_properties`, `get_edge_properties`)
The key function is :func:`get_answer_with_retry`, which attempts to
generate an answer up to ``max_retries`` times before giving up.
The API is intentionally similar to the JS version so that tests written in
JavaScript can be easily ported to Python if needed.
Author: Artur Kuzakhmetov
Date: 2026-07-01
"""
from __future__ import annotations
from typing import Any, Dict, Iterable, List, Set, Tuple, Union
import random
import time
from typing import Any, Callable
class Graph:
"""
Directed graph with optional data on nodes and edges.
class GenerationError(Exception):
"""Raised when answer generation fails after all retries."""
pass
def _simulate_answer_generation() -> str:
"""
Simulate the answer generation process.
def __init__(self) -> None:
# node_id -> node_data (dict)
self.nodes: Dict[Any, Dict[str, Any]] = {}
# node_id -> set of neighbor node_ids
self.edges: Dict[Any, Set[Any]] = {}
# (from, to) -> edge_data (dict)
self.edge_data: Dict[Tuple[Any, Any], Dict[str, Any]] = {}
This function randomly raises an exception to mimic a failure
that might occur during answer generation (e.g., API timeout,
network error, etc.). In a real-world scenario, this would be
replaced with the actual generation logic.
# ------------------------------------------------------------------
# Core graph operations
# ------------------------------------------------------------------
def add_node(self, node_id: Any, data: Dict[str, Any] | None = None) -> None:
"""Add a node with optional data.
Returns:
str: The generated answer.
Raises:
ValueError: If the node already exists.
RuntimeError: If the simulated generation fails.
"""
if node_id in self.nodes:
raise ValueError(f"Node with id {node_id} already exists")
self.nodes[node_id] = data or {}
self.edges[node_id] = set()
# Simulate a 30% chance of failure
if random.random() < 0.3:
raise RuntimeError("Simulated generation failure")
# Simulate some processing time
time.sleep(0.1)
return "Generated answer content"
def add_edge(
self,
from_id: Any,
to_id: Any,
data: Dict[str, Any] | None = None,
) -> None:
"""Add a directed edge from `from_id` to `to_id` with optional data.
def get_answer_with_retry(
generator: Callable[[], str] = _simulate_answer_generation,
max_retries: int = 3,
backoff_factor: float = 0.5,
) -> str:
"""
Attempt to generate an answer, retrying on failure.
Parameters:
generator: A callable that performs the answer generation.
max_retries: Maximum number of attempts (including the first try).
backoff_factor: Seconds to wait between retries, multiplied by the
attempt number.
Returns:
str: The successfully generated answer.
Raises:
ValueError: If either node does not exist.
GenerationError: If all retry attempts fail.
"""
if from_id not in self.nodes or to_id not in self.nodes:
raise ValueError("Both nodes must exist to add an edge")
self.edges[from_id].add(to_id)
self.edge_data[(from_id, to_id)] = data or {}
def get_neighbors(self, node_id: Any) -> List[Any]:
"""Return a list of neighbor node ids for the given node."""
if node_id not in self.nodes:
raise ValueError(f"Node with id {node_id} does not exist")
return list(self.edges[node_id])
def get_node(self, node_id: Any) -> Dict[str, Any] | None:
"""Return the data dictionary for a node, or None if it doesn't exist."""
return self.nodes.get(node_id)
def get_all_nodes(self) -> List[Any]:
"""Return a list of all node ids."""
return list(self.nodes.keys())
def get_all_edges(self) -> List[Dict[str, Any]]:
"""Return a list of all edges as dictionaries."""
edges: List[Dict[str, Any]] = []
for from_id, neighbors in self.edges.items():
for to_id in neighbors:
edges.append(
{
"from": from_id,
"to": to_id,
"data": self.edge_data.get((from_id, to_id)),
}
)
return edges
def get_edge_data(self, from_id: Any, to_id: Any) -> Dict[str, Any] | None:
"""Return the data dictionary for an edge, or None if it doesn't exist."""
return self.edge_data.get((from_id, to_id))
# ------------------------------------------------------------------
# Reflection utilities
# ------------------------------------------------------------------
def get_properties(self) -> List[str]:
"""Return the names of own instance attributes."""
return list(self.__dict__.keys())
def get_methods(self) -> List[str]:
"""Return the names of public methods defined on the class."""
methods = [
name
for name, value in vars(self.__class__).items()
if callable(value) and not name.startswith("_")
]
return methods
# ------------------------------------------------------------------
# Introspection utilities
# ------------------------------------------------------------------
def get_node_properties(self, node_id: Any) -> List[str] | None:
"""Return the keys of the node's data dictionary."""
node = self.nodes.get(node_id)
return list(node.keys()) if node is not None else None
def get_edge_properties(self, from_id: Any, to_id: Any) -> List[str] | None:
"""Return the keys of the edge's data dictionary."""
edge = self.edge_data.get((from_id, to_id))
return list(edge.keys()) if edge is not None else None
attempt = 0
while attempt < max_retries:
try:
answer = generator()
return answer
except Exception as exc:
attempt += 1
if attempt >= max_retries:
raise GenerationError(
f"Answer generation failed after {max_retries} attempts"
) from exc
# Optional: exponential backoff
wait_time = backoff_factor * attempt
time.sleep(wait_time)
def main() -> None:
"""
Entry point for the script.
Generates an answer using the retry logic and prints it.
"""
try:
answer = get_answer_with_retry()
print("Answer generated successfully:")
print(answer)
except GenerationError as err:
print(f"Error: {err}")
# If this module is run directly, demonstrate basic usage.
if __name__ == "__main__":
g = Graph()
g.add_node("a", {"value": 1})
g.add_node("b", {"value": 2})
g.add_edge("a", "b", {"weight": 5})
print("Nodes:", g.get_all_nodes())
print("Edges:", g.get_all_edges())
print("Neighbors of a:", g.get_neighbors("a"))
print("Properties:", g.get_properties())
print("Methods:", g.get_methods())
print("Node 'a' properties:", g.get_node_properties("a"))
print("Edge a->b properties:", g.get_edge_properties("a", "b"))
main()