# 🐍 Emojify Python - The Ultimate Emoji Programming Experience
**Transform Python into a fully emoji-powered language!** Import modules, write operators, create classes, and more - all with emojis!
🎉 **v1.1.0 Released**: Now with 200+ pre-configured emoji mappings!
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://badge.fury.io/py/emojify-python)
## 🚀 Features
### ✨ Core Features
- 🎯 **Import modules using emojis**: `import 🐼` for pandas
- 🔄 **Emoji aliases**: `import pandas as 🐼`
- 📦 **Emoji variables**: `🎲 = random.randint(1, 6)`
- 🎨 **Custom mappings**: Map any emoji to any module
### 🆕 Enhanced Features (v1.1.0)
- 📚 **200+ Pre-configured Mappings**: Data science, AI/ML, web, cloud, blockchain, and more!
- 🎯 **Popular Preset Sets**: Quick setup with `load_popular_set('data_science')`
- 🔄 **Module Aliases**: Multiple emojis for same module (🔢🔣#️⃣ → numpy)
- ➕➖✖️➗ **Emoji operators**: Math with `x ➕ y`, `a ✖️ b`
- 🎨 **Emoji decorators**: Time functions, cache results, handle errors
- 🔄 **Emoji control flow**: `❓` for if, `🔁` for loops
- 📝 **Emoji functions & classes**: Define with emojis
- 🖥️ **Emoji REPL**: Interactive Python with full emoji support
- 🔍 **Emoji type hints**: Type annotations with emojis
- 🎨 **Syntax highlighting**: Beautiful colored emoji code
- 📁 **Emoji file support**: Save code as `.🐍` files
- ❌ **Better error messages**: Context-aware emoji error handling
- 🧪 **Emoji assertions**: Testing with emoji asserts
## 📦 Installation
```bash
pip install emojify-python
```
## 🚀 Quick Start
### Basic Usage
```python
from emojify_python import enable
# Enable emoji imports globally
enable()
# Now you can import using emojis!
import 🐼 # Imports pandas
import 📊 # Imports matplotlib
import 🔢 # Imports numpy
# Use emoji aliases
import pandas as 🐼
import numpy as 🔢
# Create emoji variables
🎲 = 🐼.DataFrame({'data': [1, 2, 3]})
📈 = 🎲.plot()
```
### Context Manager
Use emojis only within a specific context:
```python
from emojify_python import emojified
with emojified():
import 🐼
🎲 = 🐼.DataFrame({'data': [1, 2, 3]})
print(🎲)
# Outside the context, emoji imports won't work
```
### Decorator
Enable emoji imports for specific functions:
```python
from emojify_python import emojify_function
@emojify_function
def analyze_data():
import 🐼
import 📊
🎲 = 🐼.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})
📊.pyplot.plot(🎲['x'], 🎲['y'])
return 🎲
```
## 🗺️ Default Emoji Mappings
### Data Science & Analysis
- 🐼 → `pandas`
- 📊 → `matplotlib`
- 🔢 → `numpy`
- 🧮 → `scipy`
- 🤖 → `sklearn`
- 📈 → `seaborn`
### Web Frameworks
- 🌐 → `flask`
- ⚡ → `fastapi`
- 🎪 → `django`
- 🚀 → `requests`
### Utilities
- 📅 → `datetime`
- 🔍 → `re`
- 📁 → `pathlib`
- 🎲 → `random`
- 📦 → `json`
- 🔐 → `hashlib`
[See all mappings](https://github.com/arpanghoshal/emojify-python/blob/main/emojify_python/mappings.py)
## 🎨 Custom Mappings
### Add Your Own Mappings
```python
from emojify_python import add_mapping, enable
# Add custom mapping
add_mapping('🎮', 'pygame')
add_mapping('🎨', 'pillow')
enable()
# Now use your custom emojis
import 🎮
import 🎨
🎮.init()
```
### View and Manage Mappings
```python
from emojify_python import (
view_mappings,
list_mappings,
search_mapping,
update_default_mapping,
save_custom_mappings,
load_custom_mappings
)
# View all mappings
all_mappings = view_mappings()
# Search for specific mappings
results = search_mapping('pandas') # Find mappings related to pandas
# List mappings by category
data_mappings = view_mappings(category='data')
# Update default mappings (use with caution)
update_default_mapping('🆕', 'new_module')
# Save custom mappings to file
save_custom_mappings('my_mappings.json')
# Load custom mappings from file
load_custom_mappings('my_mappings.json')
```
## 🛠️ Advanced Usage
### Execute Emoji Code
```python
from emojify_python import exec_emoji_code
code = '''
import 🐼
import 🔢
🎲 = 🐼.DataFrame({
'x': 🔢.array([1, 2, 3]),
'y': 🔢.array([4, 5, 6])
})
print(🎲.describe())
'''
exec_emoji_code(code)
```
### Compile Emoji Code
```python
from emojify_python import compile_emoji_code
code = "🎲 = [i for i in range(10)]"
compiled = compile_emoji_code(code)
exec(compiled)
```
## 🎮 Command Line Interface
Emojify Python comes with a CLI tool:
```bash
# List all emoji mappings
python -m emojify_python list
# Search for mappings
python -m emojify_python search pandas
# Add custom mapping
python -m emojify_python add 🎮 pygame
# Run a Python file with emoji support
python -m emojify_python run my_emoji_script.py
```
## 📚 Examples
### Data Analysis with Emojis
```python
from emojify_python import enable
enable()
import 🐼 as pd
import 🔢 as np
import 📊 as mpl
# Create data
🎲 = pd.DataFrame({
'📅': pd.date_range('2024-01-01', periods=100),
'📈': np.random.randn(100).cumsum(),
'📉': np.random.randn(100).cumsum()
})
# Plot data
🖼️ = 🎲.plot(x='📅', y=['📈', '📉'])
mpl.pyplot.show()
```
### Web API with Emojis
```python
from emojify_python import enable
enable()
from 🌐 import Flask, jsonify
import 📅 as datetime
🚀 = Flask(__name__)
@🚀.route('/api/time')
def get_time():
⏰ = datetime.datetime.now()
return jsonify({'time': str(⏰)})
if __name__ == '__main__':
🚀.run(debug=True)
```
### Machine Learning Pipeline
```python
from emojify_python import enable
enable()
import 🐼 as pd
import 🔢 as np
from 🤖 import model_selection, ensemble
# Load data
📊 = pd.read_csv('data.csv')
🎯 = 📊['target']
📥 = 📊.drop('target', axis=1)
# Split data
X_train, X_test, y_train, y_test = model_selection.train_test_split(
📥, 🎯, test_size=0.2, random_state=42
)
# Train model
🌳 = ensemble.RandomForestClassifier()
🌳.fit(X_train, y_train)
# Evaluate
📈 = 🌳.score(X_test, y_test)
print(f"Accuracy: {📈}")
```
## 🤔 How It Works
Emojify Python uses Python's import hook system to intercept import statements and translate emoji names to their corresponding module names. It:
1. **Registers a custom import finder** in `sys.meta_path`
2. **Transforms emoji identifiers** to valid Python names using AST manipulation
3. **Maps emojis to modules** using a configurable dictionary
4. **Maintains compatibility** with standard Python imports
## ⚠️ Limitations
- Emoji support in Python is handled through transformation, not native support
- Some IDEs may not provide autocomplete for emoji imports
- Debugging may show transformed names instead of emojis
- Not recommended for production code (but great for fun projects!)
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- Inspired by the playful nature of Python
- Thanks to all contributors and emoji enthusiasts
- Special thanks to the Python import system documentation
## 📮 Contact
- GitHub: [@arpanghoshal](https://github.com/arpanghoshal)
- PyPI: [emojify-python](https://pypi.org/project/emojify-python/)
---
**Remember**: While emoji imports are fun, use them responsibly! 🎉
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"description": "# \ud83d\udc0d Emojify Python - The Ultimate Emoji Programming Experience\n\n**Transform Python into a fully emoji-powered language!** Import modules, write operators, create classes, and more - all with emojis! \n\n\ud83c\udf89 **v1.1.0 Released**: Now with 200+ pre-configured emoji mappings! \n\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n[](https://badge.fury.io/py/emojify-python)\n\n## \ud83d\ude80 Features\n\n### \u2728 Core Features\n- \ud83c\udfaf **Import modules using emojis**: `import \ud83d\udc3c` for pandas\n- \ud83d\udd04 **Emoji aliases**: `import pandas as \ud83d\udc3c`\n- \ud83d\udce6 **Emoji variables**: `\ud83c\udfb2 = random.randint(1, 6)`\n- \ud83c\udfa8 **Custom mappings**: Map any emoji to any module\n\n### \ud83c\udd95 Enhanced Features (v1.1.0)\n- \ud83d\udcda **200+ Pre-configured Mappings**: Data science, AI/ML, web, cloud, blockchain, and more!\n- \ud83c\udfaf **Popular Preset Sets**: Quick setup with `load_popular_set('data_science')`\n- \ud83d\udd04 **Module Aliases**: Multiple emojis for same module (\ud83d\udd22\ud83d\udd23#\ufe0f\u20e3 \u2192 numpy)\n- \u2795\u2796\u2716\ufe0f\u2797 **Emoji operators**: Math with `x \u2795 y`, `a \u2716\ufe0f b`\n- \ud83c\udfa8 **Emoji decorators**: Time functions, cache results, handle errors\n- \ud83d\udd04 **Emoji control flow**: `\u2753` for if, `\ud83d\udd01` for loops\n- \ud83d\udcdd **Emoji functions & classes**: Define with emojis\n- \ud83d\udda5\ufe0f **Emoji REPL**: Interactive Python with full emoji support\n- \ud83d\udd0d **Emoji type hints**: Type annotations with emojis\n- \ud83c\udfa8 **Syntax highlighting**: Beautiful colored emoji code\n- \ud83d\udcc1 **Emoji file support**: Save code as `.\ud83d\udc0d` files\n- \u274c **Better error messages**: Context-aware emoji error handling\n- \ud83e\uddea **Emoji assertions**: Testing with emoji asserts\n\n## \ud83d\udce6 Installation\n\n```bash\npip install emojify-python\n```\n\n## \ud83d\ude80 Quick Start\n\n### Basic Usage\n\n```python\nfrom emojify_python import enable\n\n# Enable emoji imports globally\nenable()\n\n# Now you can import using emojis!\nimport \ud83d\udc3c # Imports pandas\nimport \ud83d\udcca # Imports matplotlib\nimport \ud83d\udd22 # Imports numpy\n\n# Use emoji aliases\nimport pandas as \ud83d\udc3c\nimport numpy as \ud83d\udd22\n\n# Create emoji variables\n\ud83c\udfb2 = \ud83d\udc3c.DataFrame({'data': [1, 2, 3]})\n\ud83d\udcc8 = \ud83c\udfb2.plot()\n```\n\n### Context Manager\n\nUse emojis only within a specific context:\n\n```python\nfrom emojify_python import emojified\n\nwith emojified():\n import \ud83d\udc3c\n \ud83c\udfb2 = \ud83d\udc3c.DataFrame({'data': [1, 2, 3]})\n print(\ud83c\udfb2)\n\n# Outside the context, emoji imports won't work\n```\n\n### Decorator\n\nEnable emoji imports for specific functions:\n\n```python\nfrom emojify_python import emojify_function\n\n@emojify_function\ndef analyze_data():\n import \ud83d\udc3c\n import \ud83d\udcca\n \n \ud83c\udfb2 = \ud83d\udc3c.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})\n \ud83d\udcca.pyplot.plot(\ud83c\udfb2['x'], \ud83c\udfb2['y'])\n return \ud83c\udfb2\n```\n\n## \ud83d\uddfa\ufe0f Default Emoji Mappings\n\n### Data Science & Analysis\n- \ud83d\udc3c \u2192 `pandas`\n- \ud83d\udcca \u2192 `matplotlib`\n- \ud83d\udd22 \u2192 `numpy`\n- \ud83e\uddee \u2192 `scipy`\n- \ud83e\udd16 \u2192 `sklearn`\n- \ud83d\udcc8 \u2192 `seaborn`\n\n### Web Frameworks\n- \ud83c\udf10 \u2192 `flask`\n- \u26a1 \u2192 `fastapi`\n- \ud83c\udfaa \u2192 `django`\n- \ud83d\ude80 \u2192 `requests`\n\n### Utilities\n- \ud83d\udcc5 \u2192 `datetime`\n- \ud83d\udd0d \u2192 `re`\n- \ud83d\udcc1 \u2192 `pathlib`\n- \ud83c\udfb2 \u2192 `random`\n- \ud83d\udce6 \u2192 `json`\n- \ud83d\udd10 \u2192 `hashlib`\n\n[See all mappings](https://github.com/arpanghoshal/emojify-python/blob/main/emojify_python/mappings.py)\n\n## \ud83c\udfa8 Custom Mappings\n\n### Add Your Own Mappings\n\n```python\nfrom emojify_python import add_mapping, enable\n\n# Add custom mapping\nadd_mapping('\ud83c\udfae', 'pygame')\nadd_mapping('\ud83c\udfa8', 'pillow')\n\nenable()\n\n# Now use your custom emojis\nimport \ud83c\udfae\nimport \ud83c\udfa8\n\n\ud83c\udfae.init()\n```\n\n### View and Manage Mappings\n\n```python\nfrom emojify_python import (\n view_mappings,\n list_mappings,\n search_mapping,\n update_default_mapping,\n save_custom_mappings,\n load_custom_mappings\n)\n\n# View all mappings\nall_mappings = view_mappings()\n\n# Search for specific mappings\nresults = search_mapping('pandas') # Find mappings related to pandas\n\n# List mappings by category\ndata_mappings = view_mappings(category='data')\n\n# Update default mappings (use with caution)\nupdate_default_mapping('\ud83c\udd95', 'new_module')\n\n# Save custom mappings to file\nsave_custom_mappings('my_mappings.json')\n\n# Load custom mappings from file\nload_custom_mappings('my_mappings.json')\n```\n\n## \ud83d\udee0\ufe0f Advanced Usage\n\n### Execute Emoji Code\n\n```python\nfrom emojify_python import exec_emoji_code\n\ncode = '''\nimport \ud83d\udc3c\nimport \ud83d\udd22\n\n\ud83c\udfb2 = \ud83d\udc3c.DataFrame({\n 'x': \ud83d\udd22.array([1, 2, 3]),\n 'y': \ud83d\udd22.array([4, 5, 6])\n})\nprint(\ud83c\udfb2.describe())\n'''\n\nexec_emoji_code(code)\n```\n\n### Compile Emoji Code\n\n```python\nfrom emojify_python import compile_emoji_code\n\ncode = \"\ud83c\udfb2 = [i for i in range(10)]\"\ncompiled = compile_emoji_code(code)\nexec(compiled)\n```\n\n## \ud83c\udfae Command Line Interface\n\nEmojify Python comes with a CLI tool:\n\n```bash\n# List all emoji mappings\npython -m emojify_python list\n\n# Search for mappings\npython -m emojify_python search pandas\n\n# Add custom mapping\npython -m emojify_python add \ud83c\udfae pygame\n\n# Run a Python file with emoji support\npython -m emojify_python run my_emoji_script.py\n```\n\n## \ud83d\udcda Examples\n\n### Data Analysis with Emojis\n\n```python\nfrom emojify_python import enable\nenable()\n\nimport \ud83d\udc3c as pd\nimport \ud83d\udd22 as np\nimport \ud83d\udcca as mpl\n\n# Create data\n\ud83c\udfb2 = pd.DataFrame({\n '\ud83d\udcc5': pd.date_range('2024-01-01', periods=100),\n '\ud83d\udcc8': np.random.randn(100).cumsum(),\n '\ud83d\udcc9': np.random.randn(100).cumsum()\n})\n\n# Plot data\n\ud83d\uddbc\ufe0f = \ud83c\udfb2.plot(x='\ud83d\udcc5', y=['\ud83d\udcc8', '\ud83d\udcc9'])\nmpl.pyplot.show()\n```\n\n### Web API with Emojis\n\n```python\nfrom emojify_python import enable\nenable()\n\nfrom \ud83c\udf10 import Flask, jsonify\nimport \ud83d\udcc5 as datetime\n\n\ud83d\ude80 = Flask(__name__)\n\n@\ud83d\ude80.route('/api/time')\ndef get_time():\n \u23f0 = datetime.datetime.now()\n return jsonify({'time': str(\u23f0)})\n\nif __name__ == '__main__':\n \ud83d\ude80.run(debug=True)\n```\n\n### Machine Learning Pipeline\n\n```python\nfrom emojify_python import enable\nenable()\n\nimport \ud83d\udc3c as pd\nimport \ud83d\udd22 as np\nfrom \ud83e\udd16 import model_selection, ensemble\n\n# Load data\n\ud83d\udcca = pd.read_csv('data.csv')\n\ud83c\udfaf = \ud83d\udcca['target']\n\ud83d\udce5 = \ud83d\udcca.drop('target', axis=1)\n\n# Split data\nX_train, X_test, y_train, y_test = model_selection.train_test_split(\n \ud83d\udce5, \ud83c\udfaf, test_size=0.2, random_state=42\n)\n\n# Train model\n\ud83c\udf33 = ensemble.RandomForestClassifier()\n\ud83c\udf33.fit(X_train, y_train)\n\n# Evaluate\n\ud83d\udcc8 = \ud83c\udf33.score(X_test, y_test)\nprint(f\"Accuracy: {\ud83d\udcc8}\")\n```\n\n## \ud83e\udd14 How It Works\n\nEmojify Python uses Python's import hook system to intercept import statements and translate emoji names to their corresponding module names. It:\n\n1. **Registers a custom import finder** in `sys.meta_path`\n2. **Transforms emoji identifiers** to valid Python names using AST manipulation\n3. **Maps emojis to modules** using a configurable dictionary\n4. **Maintains compatibility** with standard Python imports\n\n## \u26a0\ufe0f Limitations\n\n- Emoji support in Python is handled through transformation, not native support\n- Some IDEs may not provide autocomplete for emoji imports\n- Debugging may show transformed names instead of emojis\n- Not recommended for production code (but great for fun projects!)\n\n## \ud83e\udd1d Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.\n\n## \ud83d\udcc4 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## \ud83d\ude4f Acknowledgments\n\n- Inspired by the playful nature of Python\n- Thanks to all contributors and emoji enthusiasts\n- Special thanks to the Python import system documentation\n\n## \ud83d\udcee Contact\n\n- GitHub: [@arpanghoshal](https://github.com/arpanghoshal)\n- PyPI: [emojify-python](https://pypi.org/project/emojify-python/)\n\n---\n\n**Remember**: While emoji imports are fun, use them responsibly! \ud83c\udf89\n",
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