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Add instructions for tests and demonstration
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‎CHANGELOG.md

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# v1.2.3
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![](https://img.shields.io/badge/Version-v1.2.3-green)
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## 🌟 Add
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- `docs/README.md`: instructions for docs, provide some tool suggestions to help you quickly build your own document.
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- `tests/README.md`: instructions for testing, provide the whole procedure of testing.
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- `examples/demo.ipynb`: provide an example of how to demonstrate your project.
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## 🗑️ Delete
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- `docs/.gitkeep`
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- `tests/.gitkeep`
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- `examples/.gitkeep`
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---
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# v1.2.2
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![](https://img.shields.io/badge/Version-v1.2.2-green)

‎README.md

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## 📦 A Project Template for Self-developed Python Package
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![Package Version](https://img.shields.io/badge/Version-v1.2.2-green)
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[![Package Version](https://img.shields.io/badge/Version-v1.2.3-green)](https://github.com/Ahzyuan/Python-package-template/releases/tag/v1.2.3)
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[![License](https://img.shields.io/badge/License-MIT-khaki)](https://opensource.org/license/MIT)
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![Pypi Template](https://img.shields.io/badge/PyPI-Package_pattern-yellow?logo=pypi&labelColor=%23FAFAFA)
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‎examples/.gitkeep

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‎examples/demo.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Demonstrate your project here\n",
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"\n",
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"- With `Jupyter Notebook`, you can showcase your project, including code, results and visualizations.\n",
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"\n",
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"- `Jupyter Notebook` can save the running results of code blocks, including output text, images, tables, etc.\n",
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"\n",
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"- Therefore, if your project has rich outputs, you can show the correct operation method and its effect of your project here."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# --------------------- Below is an example ---------------------"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Looking in indexes: https://test.pypi.org/simple\n",
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"Collecting patest\n",
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" Using cached https://test-files.pythonhosted.org/packages/c5/1f/83a14b343305c5c0a453f49d1ce7d160bd542734109e1796918caf8c91d1/patest-1.0.0-py3-none-any.whl.metadata (6.9 kB)\n",
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"Requirement already satisfied: isort in /home/hzy/.conda/envs/hzy_env/lib/python3.12/site-packages (from patest) (4.3.21)\n",
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"Using cached https://test-files.pythonhosted.org/packages/c5/1f/83a14b343305c5c0a453f49d1ce7d160bd542734109e1796918caf8c91d1/patest-1.0.0-py3-none-any.whl (6.4 kB)\n",
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"Installing collected packages: patest\n",
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"Successfully installed patest-1.0.0\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"# Note: the `patest` here is a simple package created by myself\n",
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"# that only use for this demo.\n",
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"%pip install patest -i https://test.pypi.org/simple"
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]
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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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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Greetings, dear Sir Ahzyuan!\n",
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"Greetings, dear Sir Ahzyuan!\n",
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"Greetings, dear Sir Ahzyuan!\n",
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"None\n"
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]
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}
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],
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"source": [
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"# This is an example of calling the `patest` api in code.\n",
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"\n",
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"from patest import greet\n",
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"\n",
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"print(greet(name='Ahzyuan',\n",
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" gender='masculine',\n",
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" knight=True,\n",
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" count=3))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Greetings, dear Ms. Ahzyuan!\n",
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"Greetings, dear Ms. Ahzyuan!\n",
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"Greetings, dear Ms. Ahzyuan!\n"
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]
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}
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],
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"source": [
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"# This is an example of calling the `patest` command-line tool.\n",
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"\n",
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"!patest Ahzyuan --gender feminine --count 3"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "hzy_env",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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‎tests/README.md

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# Testing your project
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> This directory is used to store the testing code for the project.
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- Testing your Python projects is an important job to ensure code quality, stability and performance.
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- However, given that the implementation details and testing requirements varying from project to project, we can not provide a universal pattern for code testing.
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- But, we will provide the whole procedure of testing here. Hope it will be helpful for you. ✨
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---
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<details>
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<summary>① 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐩𝐫𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧</summary>
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1. 𝗗𝗲𝗳𝗶𝗻𝗲 𝗼𝗯𝗷𝗲𝗰𝘁𝗶𝘃𝗲𝘀 𝗼𝗳 𝘁𝗲𝘀𝘁𝗶𝗻𝗴
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- 🧪 **Functional testing**: Verify whether each function works as expected.
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- 📊 **Performance testing**: Evaluate project performance under load (response time, throughput, etc.).
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- 🧩 **Compatibility test**: Check project performance on different Python versions.
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- 🔬 *For projects involving databases, network communications, etc., additional safety tests may be needed to ensure user safety.*
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2. 𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗱𝗮𝘁𝗮
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- 📈 **Create simulated data**: Use fake data or generators (such as `Faker`) to create test data.
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- 🛢 **Database configuration**: Configure a test database(such as SQLite) for rapid testing.
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</details>
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<details>
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<summary>② 𝐂𝐫𝐞𝐚𝐭𝐞 𝐭𝐞𝐬𝐭 𝐜𝐚𝐬𝐞𝐬</summary>
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1. 𝗨𝗻𝗶𝘁 𝘁𝗲𝘀𝘁
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- 🛠️ **Tool Recommendation**: [`nose2`](https://github.com/nose-devs/nose2), [`pytest`](https://github.com/pytest-dev/pytest)
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- 📖 **Method**: Write test cases for each function and class method to cover all code paths. Use assertions to verify if expected results match actual results.
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```python
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# Example of using assertions.
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def test_addition():
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assert 1 + 1 == 2
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```
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2. 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘁𝗲𝘀𝘁𝗶𝗻𝗴: Ensure modules/components work together correctly.
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- 🛠️ **Tool Recommendation**: Use `unittest.mock` or `pytest-mock` to mock external services or APIs.
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```python
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import pytest
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from unittest.mock import patch
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@patch('my_module.external_api_call')
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def test_external_api_integration(mock_api_call):
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mock_api_call.return_value = {'data': 'expected'}
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result = my_module.fetch_data()
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assert result == 'expected'
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```
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3. 𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝘁𝗲𝘀𝘁𝗶𝗻𝗴
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- 🤖 **Simulate user operations**: Conduct a comprehensive test of the entire application process from beginning to end.
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- 🚀 **Automation script**: Write automation scripts to ensure that these tests can be run quickly after every code change.
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</details>
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<details>
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<summary>③ 𝐏𝐞𝐫𝐟𝐨𝐫𝐦 𝐭𝐞𝐬𝐭𝐬</summary>
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1. 🧐 **Manual testing**: Invite real users to conduct tests to ensure that the project meets user needs.
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2. 💻 **Automated testing**: Integrate testing into CI/CD pipelines such as `GitHub Actions`.
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</details>
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<details>
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<summary>④ 𝐓𝐞𝐬𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐚𝐧𝐝 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭</summary>
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1. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗿𝗲𝘀𝘂𝗹𝘁 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀
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- ❌ **Failure analysis**: Determine whether it is a code error, a test data problem or an environmental issue.
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- 📋 **Coverage report**: Use tools (such as `coverage`) to ensure that tests cover all critical paths.
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```bash
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# Generate coverage report
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coverage run -m pytest
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coverage report
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```
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2. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻
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- ⚙️ **Optimize test cases**: Optimize test cases according to test results to improve the accuracy and efficiency of testing.
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- ✏️ **Refactor code**: For code segments that are difficult to test, consider refactoring to make them easier to test.
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</details>

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