{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "6d67dba5-38ec-459a-9132-4a56c6a814cd", "metadata": {}, "outputs": [], "source": [ "Comment and Unit Test Generater \n", "\n", "The requirement: \n", "* use an LLM to generate docstring and comments for Python code\n", "* use an LLM to generate unit test\n", "\n", "This is my week 4 day 5 project." ] }, { "cell_type": "code", "execution_count": 24, "id": "ea1841f6-4afc-4d29-ace8-5ca5a3915c8c", "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "import os\n", "import io\n", "import sys\n", "import json\n", "import requests\n", "from dotenv import load_dotenv\n", "from openai import OpenAI\n", "import google.generativeai\n", "import anthropic\n", "from IPython.display import Markdown, display, update_display\n", "import gradio as gr\n", "import subprocess\n", "from huggingface_hub import login, InferenceClient\n", "from transformers import AutoTokenizer" ] }, { "cell_type": "code", "execution_count": 3, "id": "11957fd3-6c61-4496-aef1-8223cb9ec4ce", "metadata": {}, "outputs": [], "source": [ "# environment\n", "\n", "load_dotenv()\n", "os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", "os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')\n", "os.environ['HF_TOKEN'] = os.getenv('HF_TOKEN', 'your-key-if-not-using-env')" ] }, { "cell_type": "code", "execution_count": 4, "id": "ee7b08fd-e678-4234-895e-4e3a925e60f0", "metadata": {}, "outputs": [], "source": [ "# initialize\n", "\n", "openai = OpenAI()\n", "claude = anthropic.Anthropic()\n", "OPENAI_MODEL = \"gpt-4o\"\n", "CLAUDE_MODEL = \"claude-3-5-sonnet-20240620\"" ] }, { "cell_type": "code", "execution_count": 25, "id": "c8023255-9c98-4fbc-92e4-c553bed3b605", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.\n" ] } ], "source": [ "hf_token = os.environ['HF_TOKEN']\n", "login(hf_token, add_to_git_credential=True)" ] }, { "cell_type": "code", "execution_count": 28, "id": "f8ce3f5e-74c4-4d35-bfbc-91c5be85e094", "metadata": {}, "outputs": [], "source": [ "code_qwen = \"Qwen/CodeQwen1.5-7B-Chat\"\n", "CODE_QWEN_URL = \"https://g39mbjooiiwkbgyz.us-east-1.aws.endpoints.huggingface.cloud\"" ] }, { "cell_type": "code", "execution_count": 49, "id": "1bbc66b6-52ae-465e-a368-edc8f097fe9d", "metadata": {}, "outputs": [], "source": [ "def system_prompt_for_comment():\n", " system=\"\"\"\n", " You are a Python documentation expert. When writing documentation:\n", " - Follow PEP 257 and Google docstring style guidelines\n", " - Write clear, concise explanations\n", " - Include practical examples\n", " - Highlight edge cases and limitations\n", " - Use type hints in docstrings\n", " - Add inline comments only for complex logic\n", " - Never skip documenting parameters or return values\n", " - Validate that all documentation is accurate and complete\n", " \"\"\"\n", " return system" ] }, { "cell_type": "code", "execution_count": 50, "id": "b089f87b-53ae-40ad-8d06-b9924bb998a0", "metadata": {}, "outputs": [], "source": [ "def system_prompt_for_unit_test():\n", " system=\"\"\"\n", " You are an expert Python testing engineer who specializes in creating comprehensive unit tests. Follow these principles:\n", " - Use pytest as the testing framework\n", " - Follow the Arrange-Act-Assert pattern\n", " - Test both valid and invalid inputs\n", " - Include edge cases and boundary conditions\n", " - Write descriptive test names that explain the scenario being tested\n", " - Create independent tests that don't rely on each other\n", " - Use appropriate fixtures and parametrize when needed\n", " - Add clear comments explaining complex test logic\n", " - Cover error cases and exceptions\n", " - Achieve high code coverage while maintaining meaningful tests\n", " \"\"\"\n", " return system" ] }, { "cell_type": "code", "execution_count": 51, "id": "22193622-f3a0-4894-a6c4-eb6d88097861", "metadata": {}, "outputs": [], "source": [ "def user_prompt_for_comment(code):\n", " user = f\"\"\"\n", " Please document this Python code with:\n", " \n", " 1. A docstring containing:\n", " - A clear description of purpose and functionality\n", " - All parameters with types and descriptions\n", " - Return values with types\n", " - Exceptions that may be raised\n", " - At least one usage example\n", " - Any important notes or limitations\n", " \n", " 2. Strategic inline comments for:\n", " - Complex algorithms or business logic\n", " - Non-obvious implementation choices\n", " - Performance considerations\n", " - Edge cases\n", " \n", " Here's the code to document:\n", " \\n{code}\n", " \"\"\"\n", " return user;" ] }, { "cell_type": "code", "execution_count": 52, "id": "81e61752-ec2f-44c1-86a2-ff3234a0358c", "metadata": {}, "outputs": [], "source": [ "def user_prompt_for_unit_test(code):\n", " user = f\"\"\"\n", " Please generate unit tests for the following Python code. Include:\n", " \n", " 1. Test cases for:\n", " - Normal/expected inputs\n", " - Edge cases and boundary values\n", " - Invalid inputs and error conditions\n", " - Different combinations of parameters\n", " - All public methods and functions\n", " \n", " 2. For each test:\n", " - Clear test function names describing the scenario\n", " - Setup code (fixtures if needed)\n", " - Test data preparation\n", " - Expected outcomes\n", " - Assertions checking results\n", " - Comments explaining complex test logic\n", " \n", " 3. Include any necessary:\n", " - Imports\n", " - Fixtures\n", " - Mock objects\n", " - Helper functions\n", " - Test data generators\n", " \n", " Here's the code to test:\n", " \\n{code}\n", " \"\"\"\n", " return user" ] }, { "cell_type": "code", "execution_count": 7, "id": "f31ceed3-0eb2-4962-ab86-2d0302185560", "metadata": {}, "outputs": [], "source": [ "pi = \"\"\"\n", "import time\n", "\n", "def calculate(iterations, param1, param2):\n", " result = 1.0\n", " for i in range(1, iterations+1):\n", " j = i * param1 - param2\n", " result -= (1/j)\n", " j = i * param1 + param2\n", " result += (1/j)\n", " return result\n", "\n", "start_time = time.time()\n", "result = calculate(100_000_000, 4, 1) * 4\n", "end_time = time.time()\n", "\n", "print(f\"Result: {result:.12f}\")\n", "print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 8, "id": "192c30f5-4be6-49b7-a054-11bfcffa91e0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Result: 3.141592658589\n", "Execution Time: 58.228012 seconds\n" ] } ], "source": [ "exec(pi)" ] }, { "cell_type": "code", "execution_count": 53, "id": "d4e920dc-4094-42d8-9255-18f2919df2d4", "metadata": {}, "outputs": [], "source": [ "def messages_for_comment(python):\n", " return [\n", " {\"role\": \"system\", \"content\": system_prompt_for_comment()},\n", " {\"role\": \"user\", \"content\": user_prompt_for_comment(python)}\n", " ]" ] }, { "cell_type": "code", "execution_count": 54, "id": "77500cae-bf84-405c-8b03-2f984108951b", "metadata": {}, "outputs": [], "source": [ "def messages_for_unit_test(python):\n", " return [\n", " {\"role\": \"system\", \"content\": system_prompt_for_unit_test()},\n", " {\"role\": \"user\", \"content\": user_prompt_for_unit_test(python)}\n", " ]" ] }, { "cell_type": "code", "execution_count": 58, "id": "5ec58bf1-4a44-4c21-a71a-2cac359884e5", "metadata": {}, "outputs": [], "source": [ "def stream_comment_gpt(code):\n", " stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for_comment(code), stream=True)\n", " reply = \"\"\n", " for chunk in stream:\n", " fragment = chunk.choices[0].delta.content or \"\"\n", " reply += fragment\n", " #print(fragment, end='', flush=True)\n", " yield reply.replace('```','') \n", " " ] }, { "cell_type": "code", "execution_count": 18, "id": "47c615e2-4eb6-4ce1-ad09-7f2e6dbc3934", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "```python\n", "import time\n", "\n", "def calculate(iterations: int, param1: float, param2: float) -> float:\n", " \"\"\"\n", " Performs a series of mathematical operations in a loop to calculate a result.\n", "\n", " This function iteratively modifies a result variable through a series of arithmetic\n", " operations. Essentially, it calculates the sum of alternating series adjustments,\n", " simulating a specific numerical approximation process.\n", "\n", " Args:\n", " iterations (int): The number of iterations to perform. Must be a positive integer.\n", " param1 (float): The factor applied for multiplication inside the iteration.\n", " param2 (float): The factor subtracted and added inside the iteration for denominator adjustment.\n", "\n", " Returns:\n", " float: The calculated result after completing all iterations.\n", "\n", " Raises:\n", " ZeroDivisionError: If any calculated denominator becomes zero during execution,\n", " which may happen if `i * param1 - param2` or `i * param1 + param2` evaluates to zero.\n", "\n", " Usage Example:\n", " result = calculate(100_000_000, 4, 1)\n", " print(f\"Calculated Result: {result * 4}\")\n", "\n", " Notes:\n", " - The function can be computationally intensive depending on the number of iterations.\n", " - Ensure that `param1` and `param2` are chosen to avoid division by zero.\n", " - Floating-point precision issues might arise due to large iterations count.\n", " \"\"\"\n", " \n", " result = 1.0\n", " for i in range(1, iterations + 1):\n", " # Calculate modified denominator by subtracting param2\n", " j = i * param1 - param2\n", " \n", " # Subtract reciprocal from the result\n", " # Potential ZeroDivisionError if (i * param1 - param2) == 0\n", " result -= (1 / j)\n", " \n", " # Calculate modified denominator by adding param2\n", " j = i * param1 + param2\n", " \n", " # Add reciprocal to the result\n", " # Potential ZeroDivisionError if (i * param1 + param2) == 0\n", " result += (1 / j)\n", " \n", " return result\n", "\n", "\n", "start_time = time.time()\n", "result = calculate(100_000_000, 4, 1) * 4 # Scaling final result by 4 for specific use case\n", "end_time = time.time()\n", "\n", "# Output result with high precision and execution time for measurement\n", "print(f\"Result: {result:.12f}\")\n", "print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", "```\n", "\n", "### Explanation of Changes:\n", "- **Docstring**: The docstring provides a comprehensive explanation of the function's purpose and the calculations it performs, specifying parameter types and behavior.\n", "- **Exceptions**: A note about `ZeroDivisionError` is included, as the calculation might lead to division by zero with certain inputs.\n", "- **Usage Example**: Demonstrates how to call the function with a specific configuration.\n", "- **Notes**: Provides guidance on potential performance concerns and precision limitations.\n", "- **Inline Comments**: Added to clarify key lines where logical computations occur and where division by zero might be a risk." ] } ], "source": [ "stream_comment_gpt(pi)" ] }, { "cell_type": "code", "execution_count": 59, "id": "0b990875-31fd-40e5-bc8c-f6099d362249", "metadata": {}, "outputs": [], "source": [ "def stream_unit_test_gpt(code):\n", " stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for_unit_test(code), stream=True)\n", " reply = \"\"\n", " for chunk in stream:\n", " fragment = chunk.choices[0].delta.content or \"\"\n", " reply += fragment\n", " #print(fragment, end='', flush=True)\n", " yield reply.replace('```','')" ] }, { "cell_type": "code", "execution_count": 73, "id": "3dc90578-4f5e-47f1-b30f-c21b5795e82f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stream_unit_test_gpt(pi)" ] }, { "cell_type": "code", "execution_count": 60, "id": "17380c0f-b851-472b-a234-d86f5c219e50", "metadata": {}, "outputs": [], "source": [ "def stream_comment_claude(code):\n", " result = claude.messages.stream(\n", " model=CLAUDE_MODEL,\n", " max_tokens=2000,\n", " system=system_prompt_for_comment(),\n", " messages=[{\"role\": \"user\", \"content\": user_prompt_for_comment(code)}],\n", " )\n", " reply = \"\"\n", " with result as stream:\n", " for text in stream.text_stream:\n", " reply += text\n", " #print(text, end=\"\", flush=True)\n", " yield reply.replace('```','')" ] }, { "cell_type": "code", "execution_count": 64, "id": "0a2d016d-76a2-4752-bd4d-6f93ddec46be", "metadata": {}, "outputs": [], "source": [ "def stream_unit_test_claude(code):\n", " result = claude.messages.stream(\n", " model=CLAUDE_MODEL,\n", " max_tokens=2000,\n", " system=system_prompt_for_unit_test(),\n", " messages=[{\"role\": \"user\", \"content\": user_prompt_for_unit_test(code)}],\n", " )\n", " reply = \"\"\n", " with result as stream:\n", " for text in stream.text_stream:\n", " reply += text\n", " #print(text, end=\"\", flush=True)\n", " yield reply.replace('```','')" ] }, { "cell_type": "code", "execution_count": 23, "id": "ee43428e-b577-4e95-944d-399f2f3b89ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Here's the documented version of your Python code:\n", "\n", "```python\n", "import time\n", "\n", " float) -> float:rations: int, param1: float, param2:\n", " \"\"\"\n", "Calculates a series sum based on the given parameters.\n", "\n", " This function computes a series sum using the formula:\n", "i*param1 + param2) - 1/(i*param1 - param2)) for i from 1 to iterations.\n", "\n", " Args:\n", " iterations to perform. Must be positive.\n", "float): The first parameter used in the calculation.\n", "(float): The second parameter used in the calculation.\n", "\n", " Returns:\n", ". float: The result of the series sum calculation\n", "\n", " Raises:\n", ". ValueError: If iterations is not positive\n", "is 0 or if param2 is equal to param1.\n", "\n", " Example:\n", " = calculate(1000, 4, 1)\n", ">>> print(f\"{result:.6f}\")\n", ".392699 0\n", "\n", " Note:\n", " The function may be computationally expensive for large numbers of iterations.\n", ", floating-point precision limitations may affect accuracy.\n", " \"\"\"\n", " if iterations <= 0:\n", " must be a positive integer\")rations\n", "\n", " result = 1.0\n", " for i in range(1, iterations + 1):\n", " the seriesalculate the denominators for both terms in\n", "1 - param2 = i * param\n", " param1 + param2\n", "\n", "d division by zero\n", " 0 or j2 == 0:==\n", " calculation\")ise ZeroDivisionError(\"Division by zero in\n", "\n", "d add the second terme first term an\n", " result -= (1 / j1)\n", " result += (1 / j2)\n", "\n", " return result\n", "\n", "# Measure execution time\n", "()art_time = time.time\n", "\n", "# Perform calculation with 100 million iterations\n", " The result is multiplied by 4 as per the original code\n", "000, 4, 1) * 4late(100_000_\n", "\n", "d_time = time.time()\n", "\n", " with high precision for the calculated value\n", "Result: {result:.12f}\")\n", "(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n", "```\n", "\n", " this documented version:\n", "\n", " been added to the `calculate` function, following Google style guidelines and including all the requested elements.\n", "\n", " hints have been added to the function signature for better clarity and to support static type checking.\n", "\n", "d to explain the key steps in the calculation process.\n", "\n", " check for positive iterations has been added to prevent invalid input.\n", "\n", " been added to handle potential errors.\n", "\n", " Comments have been added to the main script to explain the purpose of each step.\n", "\n", " documentation provides a clear understanding of the function's purpose, its parameters, return value, potential exceptions, and includes an example of usage. It also notes potential limitations regarding computational cost and floating-point precision for very large numbers of iterations." ] } ], "source": [ "stream_comment_claude(pi)" ] }, { "cell_type": "code", "execution_count": 63, "id": "0565e33b-9f14-48b7-ae8d-d22dc03b93c9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Here's a comprehensive set of unit tests for the given Python code using pytest:\n", "\n", "```python\n", "import pytest\n", "import time\n", " import isclose\n", "from unittest.mock import patch\n", "\n", "# Import the function to be tested\n", "# Assuming the code is in a file named your_module.py\n", "\n", "# Test data generator\n", "_data():rate_test\n", " return [\n", ", 2, 1, 0.6931471805),\n", " 3, 2, 0.6931471806),\n", ", 3, 0.6931471806),\n", ", 1, 0.6931471806),\n", " ]\n", "\n", " datature for common test\n", "@pytest.fixture\n", "def common_data():\n", "return {\n", " 'iterations': 100,\n", " 'param1': 4,\n", " 'param2': 1\n", " }\n", "\n", "# Normal case tests\n", "rize(\"iterations, param1, param2, expected\", generate_test_data())\n", "cases(iterations, param1, param2, expected):\n", "1, param2) = calculate(iterations, param\n", "(result, expected, rel_tol=1e-9), f\"Expected {expected}, but got {result}\"\n", "\n", " cases and boundary values\n", "_cases():calculate_edge\n", "d inputsst with minimum vali\n", " 0) == 2.0 calculate(1, 1,\n", " \n", " # Test with very large iterations\n", "_result = calculate(10**8, 4, 1)\n", ", 0.6931471806, rel_tol=1e-9)lt\n", "\n", "# Invalid inputs and error conditions\n", "def test_calculate_invalid_inputs():\n", " with pytest.raises(ValueError):\n", "0, 4, 1) # iterations should be positive\n", " \n", "(ZeroDivisionError):es\n", "10, 1, 1) # This will cause division by zero\n", "\n", "TypeError):test.raises(\n", "1) # iterations should be an integer\n", "\n", "# Test with different combinations of parameters\n", "rize(\"iterations, param1, param2\", [\n", "), (100, 2, 2\n", " (1000, 3, 3),\n", "(10000, 5, 5),\n", " (100000, 10, 10)\n", "])\n", " param1, param2):e_parameter_combinations(iterations,\n", " calculate(iterations, param1, param2)\n", " assert isinstance(result, float)\n", " assert result > 0\n", "\n", " execution time\n", "common_data):ulate_execution_time(\n", " time.time()me =\n", " calculate(**common_data)\n", " end_time = time.time()\n", " execution_time = end_time - start_time\n", " f\"Execution took {execution_time} seconds, which is too long\"\n", "\n", " result precision\n", "data):st_calculate_precision(common_\n", "data)esult = calculate(**common_\n", "split('.')[1]) >= 10, \"Result should have at least 10 decimal places\"\n", "\n", "# Test with mocked time function\n", ".time')'time\n", "(mock_time, common_data):ocked_time\n", ", 0.5] # Simulate 0.5 seconds execution time\n", "_time = time.time()\n", " = calculate(**common_data)\n", "d_time = time.time()\n", " end_time - start_time == 0.5\n", "\n", "# Helper function to test monotonicity\n", "_monotonic(lst):\n", " <= lst[i+1] for i in range(len(lst)-1)) or all(lst[i] >= lst[i+1] for i in range(len(lst)-1))\n", "\n", " increasing iterationscity with\n", "def test_calculate_monotonicity():\n", " 1) for i in range(1, 6)]10**i, 4,\n", "), \"Results should be monotonic with increasing iterations\"\n", "\n", " Test with very small and very large parameters\n", ", param1, param2\", [rize(\"iterations\n", "(100, 1e-5, 1e-5),\n", ", 1e5)00, 1e5\n", "])\n", "_parameters(iterations, param1, param2):\n", "1, param2) = calculate(iterations, param\n", "result == float('inf') or result == float('-inf')), \"Result should not be infinity\"\n", "assert not isclose(result, 0, abs_tol=1e-10), \"Result should not be too close to zero\"\n", "\n", "```\n", "\n", " for the `calculate` function:range of scenarios\n", "\n", " with different inputs and expected outputs.\n", " and boundary values, including minimum valid inputs and very large iterations.\n", " Invalid inputs and error conditions, testing for expected exceptions.\n", " Different combinations of parameters to ensure the function works correctly for various inputs.\n", " to ensure the function performs within acceptable time limits.\n", " Precision test to verify the result has sufficient decimal places.\n", " A test with mocked time function to simulate and verify execution time measurement.\n", " if results are consistent with increasing iterations.\n", " with extreme parameters (very small and very large) to ensure numerical stability.\n", "\n", "rization, fixtures, and markers. It also includes necessary imports, helper functions, and a test data generator.\n", "\n", "d `test_your_module.py` in the same directory as your original code file (`your_module.py`). Then run `pytest test_your_module.py` from the command line.\n", "\n", " pytest (`pip install pytest`) before running the tests." ] } ], "source": [ "stream_unit_test_claude(pi)" ] }, { "cell_type": "code", "execution_count": 40, "id": "f13b3a5b-366d-4b28-adda-977a313e6b4d", "metadata": {}, "outputs": [], "source": [ "def stream_comment_model(model, model_url, code):\n", " tokenizer = AutoTokenizer.from_pretrained(model)\n", " messages = messages_for_comment(code)\n", " text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n", " client = InferenceClient(model_url, token=hf_token)\n", " stream = client.text_generation(text, stream=True, details=True, max_new_tokens=3000)\n", " result = \"\"\n", " for r in stream:\n", " #print(r.token.text, end = \"\")\n", " result += r.token.text\n", " yield result \n", " " ] }, { "cell_type": "code", "execution_count": 67, "id": "e2efdb92-fc7a-4952-ab46-ae942cb996bf", "metadata": {}, "outputs": [], "source": [ "def stream_unit_test_model(model, model_url, code):\n", " tokenizer = AutoTokenizer.from_pretrained(model)\n", " messages = messages_for_unit_test(code)\n", " text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n", " client = InferenceClient(model_url, token=hf_token)\n", " stream = client.text_generation(text, stream=True, details=True, max_new_tokens=3000)\n", " result = \"\"\n", " for r in stream:\n", " #print(r.token.text, end = \"\")\n", " result += r.token.text\n", " yield result \n", " " ] }, { "cell_type": "code", "execution_count": 41, "id": "0a756193-fcba-43da-a981-203c10d36488", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stream_comment_model(code_qwen, CODE_QWEN_URL, pi)" ] }, { "cell_type": "code", "execution_count": 70, "id": "12ddcbf4-6286-47a8-847b-5be78e7aa995", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Here are the unit tests for the given Python code:\n", "\n", "```python\n", "import pytest\n", "import time\n", " unittest.mock import patch\n", "\n", "def calculate(iterations, param1, param2):\n", " result = 1.0\n", " for i in range(1, iterations+1):\n", " i * param1 - param2\n", "result -= (1/j)\n", " j = i * param1 + param2\n", "result += (1/j)\n", " return result\n", "\n", "@pytest.fixture\n", " mock_time():\n", "('time.time') as mock_time:\n", "yield mock_time\n", "\n", "_calculate_normal_inputs(mock_time):\n", "mock_time.return_value = 0\n", "result = calculate(100_000_000, 4, 1) * 4\n", "expected_result = 0.0\n", " == expected_result\n", "\n", "_calculate_edge_cases(mock_time):\n", " mock_time.return_value = 0\n", " calculate(0, 4, 1) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", " = calculate(100_000_000, 0, 1) * 4\n", "expected_result = 0.0\n", " result == expected_result\n", "\n", " = calculate(100_000_000, 4, 0) * 4\n", "_result = 0.0\n", " assert result == expected_result\n", "\n", "def test_calculate_invalid_inputs(mock_time):\n", " mock_time.return_value = 0\n", ".raises(TypeError):\n", "calculate(100_000_000, 'a', 1) * 4\n", "with pytest.raises(TypeError):\n", "100_000_000, 4, 'b') * 4\n", ".raises(TypeError):\n", "calculate('a', 4, 1) * 4\n", "test.raises(TypeError):\n", "(100_000_000, 4, 1, 'c') * 4\n", "\n", "def test_calculate_different_combinations(mock_time):\n", " mock_time.return_value = 0\n", "result = calculate(100_000_000, 4, 1) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", " = calculate(100_000_000, 4, -1) * 4\n", "expected_result = 0.0\n", " == expected_result\n", "\n", " calculate(100_000_000, -4, 1) * 4\n", "result = 0.0_\n", "assert result == expected_result\n", "\n", "result = calculate(100_000_000, -4, -1) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", "def test_calculate_execution_time(mock_time):\n", "_time.return_value = 0\n", "_time = mock_time.return_value\n", "calculate(100_000_000, 4, 1) * 4\n", "end_time = mock_time.return_value\n", " expected_execution_time = 0.0\n", " assert (end_time - start_time) == expected_execution_time\n", "```\n", "\n", " covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" ] } ], "source": [ "stream_unit_test_model(code_qwen, CODE_QWEN_URL, pi)" ] }, { "cell_type": "code", "execution_count": 46, "id": "321609ee-b64a-44fc-9090-39f87e1f8e0e", "metadata": {}, "outputs": [], "source": [ "def comment_code(python, model):\n", " if model==\"GPT\":\n", " result = stream_comment_gpt(python)\n", " elif model==\"Claude\":\n", " result = stream_comment_claude(python)\n", " elif model==\"CodeQwen\":\n", " result = stream_comment_model(code_qwen, CODE_QWEN_URL, python)\n", " else:\n", " raise ValueError(\"Unknown model\")\n", " for stream_so_far in result:\n", " yield stream_so_far " ] }, { "cell_type": "code", "execution_count": 69, "id": "d4c560c9-922d-4893-941f-42893373b1be", "metadata": {}, "outputs": [], "source": [ "def get_unit_test(python, model):\n", " if model==\"GPT\":\n", " result = stream_unit_test_gpt(python)\n", " elif model==\"Claude\":\n", " result = stream_unit_test_claude(python)\n", " elif model==\"CodeQwen\":\n", " result = stream_unit_test_model(code_qwen, CODE_QWEN_URL, python)\n", " else:\n", " raise ValueError(\"Unknown model\")\n", " for stream_so_far in result:\n", " yield stream_so_far " ] }, { "cell_type": "code", "execution_count": 35, "id": "f85bc777-bebe-436b-88cc-b9ecdb6306c0", "metadata": {}, "outputs": [], "source": [ "css = \"\"\"\n", ".python {background-color: #306998;}\n", ".cpp {background-color: #050;}\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 74, "id": "ee27cc91-81e6-42c8-ae3c-c04161229d8c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "* Running on local URL: http://127.0.0.1:7881\n", "\n", "To create a public link, set `share=True` in `launch()`.\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, { "name": "stdout", "output_type": "stream", "text": [ "Here are the unit tests for the given Python code:\n", "\n", "```python\n", "import pytest\n", "import time\n", " unittest.mock import patch\n", "\n", "def calculate(iterations, param1, param2):\n", " result = 1.0\n", " for i in range(1, iterations+1):\n", " i * param1 - param2\n", " result -= (1/j)\n", " i * param1 + param2\n", "result += (1/j)\n", " return result\n", "\n", "@pytest.fixture\n", " mock_time():\n", " with patch('time.time') as mock_time:\n", "ield mock_time\n", "\n", "calculate_normal_inputs(mock_time):\n", "time.return_value = 0\n", " calculate(100_000_000, 4, 1) * 4\n", "result = 0.0_\n", "assert result == expected_result\n", "\n", " test_calculate_edge_cases(mock_time):\n", "time.return_value = 0\n", " calculate(0, 4, 1) * 4\n", "_result = 0.0\n", " assert result == expected_result\n", "\n", " result = calculate(100_000_000, 0, 1) * 4\n", "result = 0.0_\n", "assert result == expected_result\n", "\n", "result = calculate(100_000_000, 4, 0) * 4\n", " expected_result = 0.0\n", "assert result == expected_result\n", "\n", " test_calculate_invalid_inputs(mock_time):\n", "_time.return_value = 0\n", "test.raises(TypeError):\n", " calculate(100_000_000, 'a', 1) * 4\n", "with pytest.raises(TypeError):\n", "ulate(100_000_000, 4, 'b') * 4\n", " pytest.raises(TypeError):\n", "ulate('a', 4, 1) * 4\n", "test.raises(TypeError):\n", " calculate(100_000_000, 4, 1, 'c') * 4\n", "\n", "_calculate_different_combinations(mock_time):\n", " mock_time.return_value = 0\n", " result = calculate(100_000_000, 4, 1) * 4\n", " expected_result = 0.0\n", " == expected_result\n", "\n", " calculate(100_000_000, 4, -1) * 4\n", "_result = 0.0\n", " assert result == expected_result\n", "\n", " result = calculate(100_000_000, -4, 1) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", " calculate(100_000_000, -4, -1) * 4\n", "_result = 0.0\n", " assert result == expected_result\n", "\n", "def test_calculate_execution_time(mock_time):\n", "mock_time.return_value = 0\n", "start_time = mock_time.return_value\n", " calculate(100_000_000, 4, 1) * 4\n", " end_time = mock_time.return_value\n", " expected_execution_time = 0.0\n", " assert (end_time - start_time) == expected_execution_time\n", "```\n", "\n", " covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Traceback (most recent call last):\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\queueing.py\", line 625, in process_events\n", " response = await route_utils.call_process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\route_utils.py\", line 322, in call_process_api\n", " output = await app.get_blocks().process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 2047, in process_api\n", " result = await self.call_function(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 1606, in call_function\n", " prediction = await utils.async_iteration(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 714, in async_iteration\n", " return await anext(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 708, in __anext__\n", " return await anyio.to_thread.run_sync(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\to_thread.py\", line 56, in run_sync\n", " return await get_async_backend().run_sync_in_worker_thread(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 2505, in run_sync_in_worker_thread\n", " return await future\n", " ^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 1005, in run\n", " result = context.run(func, *args)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 691, in run_sync_iterator_async\n", " return next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 852, in gen_wrapper\n", " response = next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\AppData\\Local\\Temp\\ipykernel_27660\\2822054561.py\", line 10, in get_unit_test\n", " for stream_so_far in result:\n", "TypeError: 'NoneType' object is not iterable\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Here are the unit tests for the given Python code:\n", "\n", "```python\n", "import pytest\n", "import time\n", "est.mock import patch\n", "\n", "(iterations, param1, param2):\n", "result = 1.0\n", "for i in range(1, iterations+1):\n", "j = i * param1 - param2\n", " -= (1/j)esult\n", "j = i * param1 + param2\n", " += (1/j)esult\n", "return result\n", "\n", "pytest.fixture\n", "_time():\n", " with patch('time.time') as mock_time:\n", "ield mock_time\n", "\n", "calculate_normal_inputs(mock_time):\n", "time.return_value = 0\n", " calculate(100_000_000, 4, 1) * 4\n", "_result = 0.0\n", " assert result == expected_result\n", "\n", "def test_calculate_edge_cases(mock_time):\n", "mock_time.return_value = 0\n", "result = calculate(0, 4, 1) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", " = calculate(100_000_000, 0, 1) * 4\n", "_result = 0.0\n", "assert result == expected_result\n", "\n", "result = calculate(100_000_000, 4, 0) * 4\n", " expected_result = 0.0\n", " result == expected_result\n", "\n", "_calculate_invalid_inputs(mock_time):\n", "time.return_value = 0\n", " with pytest.raises(TypeError):\n", "(100_000_000, 'a', 1) * 4\n", "ises(TypeError):ra\n", "ulate(100_000_000, 4, 'b') * 4\n", " pytest.raises(TypeError):\n", "ulate('a', 4, 1) * 4\n", " pytest.raises(TypeError):\n", "ulate(100_000_000, 4, 1, 'c') * 4\n", "\n", "calculate_different_combinations(mock_time):\n", " mock_time.return_value = 0\n", " result = calculate(100_000_000, 4, 1) * 4\n", " = 0.0pected_result\n", " result == expected_result\n", "\n", " = calculate(100_000_000, 4, -1) * 4\n", "expected_result = 0.0\n", " expected_resultt ==\n", "\n", " result = calculate(100_000_000, -4, 1) * 4\n", "result = 0.0_\n", " == expected_result\n", "\n", " calculate(100_000_000, -4, -1) * 4\n", " = 0.0pected_result\n", " result == expected_result\n", "\n", "def test_calculate_execution_time(mock_time):\n", "_time.return_value = 0\n", "_time = mock_time.return_value\n", "100_000_000, 4, 1) * 4\n", " end_time = mock_time.return_value\n", "_execution_time = 0.0\n", " (end_time - start_time) == expected_execution_time\n", "``\n", "\n", " suite covers all the scenarios mentioned in the problem description. It tests the function with normal inputs, edge cases, invalid inputs, different combinations of parameters, and checks the execution time.<|im_end|>" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Traceback (most recent call last):\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\queueing.py\", line 625, in process_events\n", " response = await route_utils.call_process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\route_utils.py\", line 322, in call_process_api\n", " output = await app.get_blocks().process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 2047, in process_api\n", " result = await self.call_function(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\blocks.py\", line 1606, in call_function\n", " prediction = await utils.async_iteration(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 714, in async_iteration\n", " return await anext(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 708, in __anext__\n", " return await anyio.to_thread.run_sync(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\to_thread.py\", line 56, in run_sync\n", " return await get_async_backend().run_sync_in_worker_thread(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 2505, in run_sync_in_worker_thread\n", " return await future\n", " ^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\anyio\\_backends\\_asyncio.py\", line 1005, in run\n", " result = context.run(func, *args)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 691, in run_sync_iterator_async\n", " return next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\.conda\\envs\\llms\\Lib\\site-packages\\gradio\\utils.py\", line 852, in gen_wrapper\n", " response = next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"C:\\Users\\ebaba\\AppData\\Local\\Temp\\ipykernel_27660\\2822054561.py\", line 10, in get_unit_test\n", " for stream_so_far in result:\n", "TypeError: 'NoneType' object is not iterable\n" ] } ], "source": [ "with gr.Blocks(css=css) as ui:\n", " gr.Markdown(\"## Convert code from Python to C++\")\n", " with gr.Row():\n", " python = gr.Textbox(label=\"Python code:\", value=pi, lines=10)\n", " result = gr.Textbox(label=\"Result code:\", lines=10)\n", " with gr.Row():\n", " model = gr.Dropdown([\"GPT\", \"Claude\",\"CodeQwen\"], label=\"Select model\", value=\"GPT\")\n", " with gr.Row():\n", " comment_button = gr.Button(\"Comment code\")\n", " with gr.Row():\n", " unit_test_button = gr.Button(\"Unit Test code\")\n", " \n", " comment_button.click(comment_code, inputs=[python, model], outputs=[result])\n", " unit_test_button.click(get_unit_test, inputs=[python, model], outputs=[result])\n", "ui.launch(inbrowser=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "06e8279c-b488-4807-9bed-9d26be11c057", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }