# Sugar: Python Syntactic Sugar
A lightweight utility package that provides syntactic sugar and data manipulation tools to make Python code more concise and expressive.
## Installation
```bash
pip install git+https://github.com/gabiteodoru/sugar.git
```
Dependencies:
- pandas
- more_itertools
## Features
### Core Functions
- **Mapping Functions**:
- `imap`: List version of `map()`
- `timap`: Tuple version of `map()`
- `izip`: List version of `zip()`
- `ifilter`: List version of `filter()`
- `dmap`: Apply function to dictionary values
- `dfilter`: Filter dictionary keys based on values
- `flatten`: Flatten nested lists
- `unique`: Return unique values from a list
- **Function Wrappers**: Operations using subtraction syntax
- **Smart String Splitting**: Handle nested brackets, quotes and special characters
- **Data Structure Manipulation**: Functions for dictionaries, lists and pandas DataFrames
- **Concise Data Access**: Simplified syntax for common operations
### Examples
```python
from sugar import *
# List operations
imap(lambda x: x+2, [2, 3, 4]) # [4, 5, 6]
timap(lambda x: x+2, [2, 3, 4]) # (4, 5, 6)
izip([1, 2], ['a', 'b']) # [(1, 'a'), (2, 'b')]
ifilter(lambda x: x > 2, [1, 2, 3, 4]) # [3, 4]
flatten([[1, 2], [3, 4]]) # [1, 2, 3, 4]
unique([1, 2, 2, 3, 3]) # [1, 2, 3]
# Dictionary operations
dmap(lambda x: x*2, {'a': 1, 'b': 2}) # {'a': 2, 'b': 4}
dfilter(lambda x: x > 1, {'a': 1, 'b': 2, 'c': 3}) # ['b', 'c']
# String splitting
'a, b, c'-spl # ['a', 'b', 'c']
'a b c'-spls # ['a', 'b', 'c']
'a>b>c'-splon('>') # ['a', 'b', 'c']
'a b c'-spls-first # 'a'
'a b c'-spls-last # 'c'
# Dictionary operations
'a:x, b:y, c:z'-spld # {'a': 'x', 'b': 'y', 'c': 'z'}
'a:x, b:y, c:z'-spld-flipDict # {'x': 'a', 'y': 'b', 'z': 'c'}
# Condition building
'a==1, b==2'-spland # '(a==1)&(b==2)'
# DataFrame operations
df = pd.DataFrame({'x':'a, a, b'-spl, 'y':'c, d, d'-spl, 'z':[1, 2, 3]})
isUnique(df) # True
qselect(df,'y, colX:x') # DataFrame with columns 'y' and 'colX' (renamed from 'x')
frontCols(df, 'y, z') # DataFrame with columns reordered as ['y', 'z', 'x']
```
### Advanced Features
#### Script Execution
Run Python scripts in the current namespace:
```python
# Execute a script in the current namespace
eval(runpy)('script.py')
```
#### Function Application Syntax
Replace verbose function definitions with concise string expressions:
```python
# Traditional approach
def f(x):
d = {}
d['v'] = x.v.sum()
d['dv'] = (x.v*x.c).sum()
return pd.Series(d, index=['v', 'dv'])
rawData.groupby('s').apply(f)
# With sugar
rawData.groupby('s').apply('v: x.v.sum(), dv: (x.v*x.c).sum()'-fapply)
```
#### Data Classes
- `FriendlyDataClass`: Base class with dictionary-like access
- `Obj`: Enhanced dictionary with attribute access
#### Nested Structure Creation
```python
createNestedStruct('a, b, c', 'x, y', init=[1, 2, 3])
# Creates nested dictionary structure with leaf nodes [1, 2, 3]
```
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
[MIT License](LICENSE)
## Documentation
Documentation generated with assistance from Claude (Anthropic).
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"description": "# Sugar: Python Syntactic Sugar\n\nA lightweight utility package that provides syntactic sugar and data manipulation tools to make Python code more concise and expressive.\n\n## Installation\n\n```bash\npip install git+https://github.com/gabiteodoru/sugar.git\n```\n\nDependencies:\n- pandas\n- more_itertools\n\n## Features\n\n### Core Functions\n\n- **Mapping Functions**: \n - `imap`: List version of `map()`\n - `timap`: Tuple version of `map()`\n - `izip`: List version of `zip()`\n - `ifilter`: List version of `filter()`\n - `dmap`: Apply function to dictionary values\n - `dfilter`: Filter dictionary keys based on values\n - `flatten`: Flatten nested lists\n - `unique`: Return unique values from a list\n- **Function Wrappers**: Operations using subtraction syntax\n- **Smart String Splitting**: Handle nested brackets, quotes and special characters\n- **Data Structure Manipulation**: Functions for dictionaries, lists and pandas DataFrames\n- **Concise Data Access**: Simplified syntax for common operations\n\n### Examples\n\n```python\nfrom sugar import *\n\n# List operations\nimap(lambda x: x+2, [2, 3, 4]) # [4, 5, 6]\ntimap(lambda x: x+2, [2, 3, 4]) # (4, 5, 6)\nizip([1, 2], ['a', 'b']) # [(1, 'a'), (2, 'b')]\nifilter(lambda x: x > 2, [1, 2, 3, 4]) # [3, 4]\nflatten([[1, 2], [3, 4]]) # [1, 2, 3, 4]\nunique([1, 2, 2, 3, 3]) # [1, 2, 3]\n\n# Dictionary operations\ndmap(lambda x: x*2, {'a': 1, 'b': 2}) # {'a': 2, 'b': 4}\ndfilter(lambda x: x > 1, {'a': 1, 'b': 2, 'c': 3}) # ['b', 'c']\n\n# String splitting\n'a, b, c'-spl # ['a', 'b', 'c']\n'a b c'-spls # ['a', 'b', 'c']\n'a>b>c'-splon('>') # ['a', 'b', 'c']\n'a b c'-spls-first # 'a'\n'a b c'-spls-last # 'c'\n\n# Dictionary operations\n'a:x, b:y, c:z'-spld # {'a': 'x', 'b': 'y', 'c': 'z'}\n'a:x, b:y, c:z'-spld-flipDict # {'x': 'a', 'y': 'b', 'z': 'c'}\n\n# Condition building\n'a==1, b==2'-spland # '(a==1)&(b==2)'\n\n# DataFrame operations\ndf = pd.DataFrame({'x':'a, a, b'-spl, 'y':'c, d, d'-spl, 'z':[1, 2, 3]})\nisUnique(df) # True\nqselect(df,'y, colX:x') # DataFrame with columns 'y' and 'colX' (renamed from 'x')\nfrontCols(df, 'y, z') # DataFrame with columns reordered as ['y', 'z', 'x']\n```\n\n### Advanced Features\n\n#### Script Execution\n\nRun Python scripts in the current namespace:\n\n```python\n# Execute a script in the current namespace\neval(runpy)('script.py')\n```\n\n#### Function Application Syntax\n\nReplace verbose function definitions with concise string expressions:\n\n```python\n# Traditional approach\ndef f(x):\n d = {}\n d['v'] = x.v.sum()\n d['dv'] = (x.v*x.c).sum()\n return pd.Series(d, index=['v', 'dv'])\n\nrawData.groupby('s').apply(f)\n\n# With sugar\nrawData.groupby('s').apply('v: x.v.sum(), dv: (x.v*x.c).sum()'-fapply)\n```\n\n#### Data Classes\n\n- `FriendlyDataClass`: Base class with dictionary-like access\n- `Obj`: Enhanced dictionary with attribute access\n\n#### Nested Structure Creation\n\n```python\ncreateNestedStruct('a, b, c', 'x, y', init=[1, 2, 3])\n# Creates nested dictionary structure with leaf nodes [1, 2, 3]\n```\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\n[MIT License](LICENSE)\n\n## Documentation\n\nDocumentation generated with assistance from Claude (Anthropic).\n",
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