| Name | unpacking JSON |
| Version |
1!0.1.4
JSON |
| download |
| home_page | None |
| Summary | Unpacking, spreading, or splatting positional arguments and keyword arguments in Python |
| upload_time | 2025-09-03 23:54:42 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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| keywords |
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spread
spreading
unpack
unpacking
|
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|
# unpacking
[](https://pypi.org/project/unpacking/)
[](https://github.com/cctien/unpacking/actions/workflows/python-package.yml)
[](./LICENSE)
Unpacking, spreading, or splatting positional arguments and keyword arguments in Python.
This library provides functional tools as classes that give you versions of your original functions which use unpacking expressions ([Python reference](https://docs.python.org/3/reference/expressions.html#calls), [PEP 448](https://peps.python.org/pep-0448/)) for the function calls underneath.
## Table of Contents
- [unpacking](#unpacking)
- [Table of Contents](#table-of-contents)
- [Why Use Unpacking?](#why-use-unpacking)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Examples](#examples)
- [Basic Example](#basic-example)
- [Partial Argument Matching](#partial-argument-matching)
- [Multiprocessing Examples](#multiprocessing-examples)
- [Simple Example](#simple-example)
- [Data Processing Example](#data-processing-example)
- [Common Patterns](#common-patterns)
- [Working with Configuration Objects](#working-with-configuration-objects)
- [Chaining with Other Functional Tools](#chaining-with-other-functional-tools)
- [API Reference](#api-reference)
- [`starred(func) -> callable`](#starredfunc---callable)
- [`doublestarred(func) -> callable`](#doublestarredfunc---callable)
- [`unpacking(func) -> callable`](#unpackingfunc---callable)
- [`starredpart(func) -> callable`](#starredpartfunc---callable)
- [`doublestarredpart(func) -> callable`](#doublestarredpartfunc---callable)
- [`unpackingpart(func) -> callable`](#unpackingpartfunc---callable)
## Why Use Unpacking?
- **Multiprocessing**: Easily map functions over lists of mixed argument structures
- **Dynamic function calls**: Handle variable argument formats cleanly without manual unpacking
- **Functional programming**: Create reusable argument-unpacking patterns
- **Code simplification**: Reduce boilerplate when working with argument collections
## Installation
```bash
pip install -U unpacking
```
## Quick Start
```python
from unpacking import unpacking
def your_function(x, y, z=None):
return f"{x} + {y} + {z}"
# Works with both lists and dicts automatically
result1 = unpacking(your_function)([1, 2, 3]) # Uses *args
result2 = unpacking(your_function)({"x": 1, "y": 2}) # Uses **kwargs
```
## Examples
### Basic Example
```python
from unpacking import starred, doublestarred, unpacking
def add(x, y):
return x + y
args = [1, 2]
kwargs = {"x": 1, "y": 2}
# Traditional unpacking
print(add(*args)) # 3
print(add(**kwargs)) # 3
# Using unpacking library
print(starred(add)(args)) # 3
print(doublestarred(add)(kwargs)) # 3
# `unpacking` automatically detects the appropriate unpacking method
print(unpacking(add)(args)) # 3
print(unpacking(add)(kwargs)) # 3
```
### Partial Argument Matching
Handle cases where you have more arguments than the function needs:
```python
from unpacking import starredpart, doublestarredpart, unpackingpart
def add(x, y):
return x + y
args_excess = [1, 2, 3] # Extra argument ignored
kwargs_excess = {"x": 1, "y": 2, "z": 3} # Extra keyword ignored
print(starredpart(add)(args_excess)) # 3
print(doublestarredpart(add)(kwargs_excess)) # 3
print(unpackingpart(add)(args_excess)) # 3
print(unpackingpart(add)(kwargs_excess)) # 3
```
### Multiprocessing Examples
#### Simple Example
```python
from concurrent.futures import ProcessPoolExecutor
from unpacking import unpacking
def add(x, y):
return x + y
args_list = [[1, 2], [3, 4]]
kwargs_list = [{"x": 1, "y": 2}, {"x": 3, "y": 4}]
with ProcessPoolExecutor(2) as executor:
print(tuple(executor.map(unpacking(add), args_list))) # (3, 7)
print(tuple(executor.map(unpacking(add), kwargs_list))) # (3, 7)
```
#### Data Processing Example
```python
from concurrent.futures import ProcessPoolExecutor
from unpacking import unpacking
def process_data(file_path, format_type, compression=None):
"""Process a data file with specified format and optional compression."""
# Simulate processing logic
result = f"Processed {file_path} as {format_type}"
if compression:
result += f" with {compression} compression"
return result
# Mixed argument formats - some positional, some keyword, some partial
tasks = [
["data1.csv", "csv", "gzip"], # All positional
["data2.json", "json"], # Partial positional
{"file_path": "data3.xml", "format_type": "xml"}, # Keyword only
{"file_path": "data4.parquet", "format_type": "parquet", "compression": "snappy"} # All keyword
]
with ProcessPoolExecutor() as executor:
results = list(executor.map(unpacking(process_data), tasks))
for result in results:
print(result)
```
## Common Patterns
### Working with Configuration Objects
```python
from unpacking import unpacking
def create_connection(host, port, username, password=None, timeout=30):
return f"Connected to {host}:{port} as {username}"
configs = [
{"host": "localhost", "port": 5432, "username": "admin"},
{"host": "remote.db", "port": 3306, "username": "user", "password": "secret"},
]
connections = [unpacking(create_connection)(config) for config in configs]
```
### Chaining with Other Functional Tools
```python
from functools import partial
from unpacking import unpacking
def add_and_multiply(x, y, multiplier=1):
return (x + y) * multiplier
# Create a specialized function
add_and_double = partial(unpacking(add_and_multiply), multiplier=2)
args_list = [[2, 3], [4, 5], [1, 6]]
results = list(map(add_and_multiply, args_list)) # [10, 18, 14]
```
## API Reference
### `starred(func) -> callable`
Returns a function that calls `func(*args)` when given an iterable.
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks positional arguments from an iterable
**Example:**
```python
starred_func = starred(your_function)
result = starred_func([arg1, arg2, arg3]) # Equivalent to your_function(*[arg1, arg2, arg3])
```
### `doublestarred(func) -> callable`
Returns a function that calls `func(**kwargs)` when given a mapping.
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks keyword arguments from a mapping
**Example:**
```python
doublestarred_func = doublestarred(your_function)
result = doublestarred_func({"x": 1, "y": 2}) # Equivalent to your_function(**{"x": 1, "y": 2})
```
### `unpacking(func) -> callable`
Automatically detects whether to use `*args` or `**kwargs` unpacking based on the argument type.
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks arguments appropriately
**Behavior:**
- For sequences (list, tuple): uses `*args` unpacking
- For mappings (dict): uses `**kwargs` unpacking
**Example:**
```python
unpacking_func = unpacking(your_function)
result1 = unpacking_func([1, 2, 3]) # Uses *args
result2 = unpacking_func({"x": 1, "y": 2}) # Uses **kwargs
```
### `starredpart(func) -> callable`
Like `starred()`, but only passes as many positional arguments as the function accepts.
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks only the needed positional arguments
### `doublestarredpart(func) -> callable`
Like `doublestarred()`, but only passes keyword arguments that the function accepts.
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks only the needed keyword arguments
### `unpackingpart(func) -> callable`
Like `unpacking()`, but only passes as many arguments as the function needs (works with both positional and keyword arguments).
**Parameters:**
- `func`: The function to wrap
**Returns:** A new function that unpacks only the needed arguments
Raw data
{
"_id": null,
"home_page": null,
"name": "unpacking",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": "Chih-chan Tien <chihchan.tien@gmail.com>",
"keywords": "splat, splatting, spread, spreading, unpack, unpacking",
"author": null,
"author_email": "Chih-chan Tien <chihchan.tien@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/2c/df/a6af838f261dc7b10e0c088f1931b016febe5c69b69b8fcd454b5eab72ab/unpacking-1!0.1.4.tar.gz",
"platform": null,
"description": "# unpacking\n\n[](https://pypi.org/project/unpacking/)\n[](https://github.com/cctien/unpacking/actions/workflows/python-package.yml)\n[](./LICENSE)\n\nUnpacking, spreading, or splatting positional arguments and keyword arguments in Python.\n\nThis library provides functional tools as classes that give you versions of your original functions which use unpacking expressions ([Python reference](https://docs.python.org/3/reference/expressions.html#calls), [PEP 448](https://peps.python.org/pep-0448/)) for the function calls underneath.\n\n## Table of Contents\n\n- [unpacking](#unpacking)\n - [Table of Contents](#table-of-contents)\n - [Why Use Unpacking?](#why-use-unpacking)\n - [Installation](#installation)\n - [Quick Start](#quick-start)\n - [Examples](#examples)\n - [Basic Example](#basic-example)\n - [Partial Argument Matching](#partial-argument-matching)\n - [Multiprocessing Examples](#multiprocessing-examples)\n - [Simple Example](#simple-example)\n - [Data Processing Example](#data-processing-example)\n - [Common Patterns](#common-patterns)\n - [Working with Configuration Objects](#working-with-configuration-objects)\n - [Chaining with Other Functional Tools](#chaining-with-other-functional-tools)\n - [API Reference](#api-reference)\n - [`starred(func) -> callable`](#starredfunc---callable)\n - [`doublestarred(func) -> callable`](#doublestarredfunc---callable)\n - [`unpacking(func) -> callable`](#unpackingfunc---callable)\n - [`starredpart(func) -> callable`](#starredpartfunc---callable)\n - [`doublestarredpart(func) -> callable`](#doublestarredpartfunc---callable)\n - [`unpackingpart(func) -> callable`](#unpackingpartfunc---callable)\n\n## Why Use Unpacking?\n\n- **Multiprocessing**: Easily map functions over lists of mixed argument structures\n- **Dynamic function calls**: Handle variable argument formats cleanly without manual unpacking\n- **Functional programming**: Create reusable argument-unpacking patterns\n- **Code simplification**: Reduce boilerplate when working with argument collections\n\n## Installation\n\n```bash\npip install -U unpacking\n```\n\n## Quick Start\n\n```python\nfrom unpacking import unpacking\n\ndef your_function(x, y, z=None):\n return f\"{x} + {y} + {z}\"\n\n# Works with both lists and dicts automatically\nresult1 = unpacking(your_function)([1, 2, 3]) # Uses *args\nresult2 = unpacking(your_function)({\"x\": 1, \"y\": 2}) # Uses **kwargs\n```\n\n## Examples\n\n### Basic Example\n\n```python\nfrom unpacking import starred, doublestarred, unpacking\n\ndef add(x, y):\n return x + y\n\nargs = [1, 2]\nkwargs = {\"x\": 1, \"y\": 2}\n\n# Traditional unpacking\nprint(add(*args)) # 3\nprint(add(**kwargs)) # 3\n\n# Using unpacking library\nprint(starred(add)(args)) # 3\nprint(doublestarred(add)(kwargs)) # 3\n\n# `unpacking` automatically detects the appropriate unpacking method\nprint(unpacking(add)(args)) # 3\nprint(unpacking(add)(kwargs)) # 3\n```\n\n### Partial Argument Matching\n\nHandle cases where you have more arguments than the function needs:\n\n```python\nfrom unpacking import starredpart, doublestarredpart, unpackingpart\n\ndef add(x, y):\n return x + y\n\nargs_excess = [1, 2, 3] # Extra argument ignored\nkwargs_excess = {\"x\": 1, \"y\": 2, \"z\": 3} # Extra keyword ignored\n\nprint(starredpart(add)(args_excess)) # 3\nprint(doublestarredpart(add)(kwargs_excess)) # 3\nprint(unpackingpart(add)(args_excess)) # 3\nprint(unpackingpart(add)(kwargs_excess)) # 3\n```\n\n### Multiprocessing Examples\n\n#### Simple Example\n\n```python\nfrom concurrent.futures import ProcessPoolExecutor\nfrom unpacking import unpacking\n\ndef add(x, y):\n return x + y\n\nargs_list = [[1, 2], [3, 4]]\nkwargs_list = [{\"x\": 1, \"y\": 2}, {\"x\": 3, \"y\": 4}]\n\nwith ProcessPoolExecutor(2) as executor:\n print(tuple(executor.map(unpacking(add), args_list))) # (3, 7)\n print(tuple(executor.map(unpacking(add), kwargs_list))) # (3, 7)\n```\n\n#### Data Processing Example\n\n```python\nfrom concurrent.futures import ProcessPoolExecutor\nfrom unpacking import unpacking\n\ndef process_data(file_path, format_type, compression=None):\n \"\"\"Process a data file with specified format and optional compression.\"\"\"\n # Simulate processing logic\n result = f\"Processed {file_path} as {format_type}\"\n if compression:\n result += f\" with {compression} compression\"\n return result\n\n# Mixed argument formats - some positional, some keyword, some partial\ntasks = [\n [\"data1.csv\", \"csv\", \"gzip\"], # All positional\n [\"data2.json\", \"json\"], # Partial positional\n {\"file_path\": \"data3.xml\", \"format_type\": \"xml\"}, # Keyword only\n {\"file_path\": \"data4.parquet\", \"format_type\": \"parquet\", \"compression\": \"snappy\"} # All keyword\n]\n\nwith ProcessPoolExecutor() as executor:\n results = list(executor.map(unpacking(process_data), tasks))\n for result in results:\n print(result)\n```\n\n## Common Patterns\n\n### Working with Configuration Objects\n\n```python\nfrom unpacking import unpacking\n\ndef create_connection(host, port, username, password=None, timeout=30):\n return f\"Connected to {host}:{port} as {username}\"\n\nconfigs = [\n {\"host\": \"localhost\", \"port\": 5432, \"username\": \"admin\"},\n {\"host\": \"remote.db\", \"port\": 3306, \"username\": \"user\", \"password\": \"secret\"},\n]\n\nconnections = [unpacking(create_connection)(config) for config in configs]\n```\n\n### Chaining with Other Functional Tools\n\n```python\nfrom functools import partial\nfrom unpacking import unpacking\n\ndef add_and_multiply(x, y, multiplier=1):\n return (x + y) * multiplier\n\n# Create a specialized function\nadd_and_double = partial(unpacking(add_and_multiply), multiplier=2)\n\nargs_list = [[2, 3], [4, 5], [1, 6]]\nresults = list(map(add_and_multiply, args_list)) # [10, 18, 14]\n```\n\n## API Reference\n\n### `starred(func) -> callable`\n\nReturns a function that calls `func(*args)` when given an iterable.\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks positional arguments from an iterable\n\n**Example:**\n\n```python\nstarred_func = starred(your_function)\nresult = starred_func([arg1, arg2, arg3]) # Equivalent to your_function(*[arg1, arg2, arg3])\n```\n\n### `doublestarred(func) -> callable`\n\nReturns a function that calls `func(**kwargs)` when given a mapping.\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks keyword arguments from a mapping\n\n**Example:**\n\n```python\ndoublestarred_func = doublestarred(your_function)\nresult = doublestarred_func({\"x\": 1, \"y\": 2}) # Equivalent to your_function(**{\"x\": 1, \"y\": 2})\n```\n\n### `unpacking(func) -> callable`\n\nAutomatically detects whether to use `*args` or `**kwargs` unpacking based on the argument type.\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks arguments appropriately\n\n**Behavior:**\n\n- For sequences (list, tuple): uses `*args` unpacking\n- For mappings (dict): uses `**kwargs` unpacking\n\n**Example:**\n\n```python\nunpacking_func = unpacking(your_function)\nresult1 = unpacking_func([1, 2, 3]) # Uses *args\nresult2 = unpacking_func({\"x\": 1, \"y\": 2}) # Uses **kwargs\n```\n\n### `starredpart(func) -> callable`\n\nLike `starred()`, but only passes as many positional arguments as the function accepts.\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks only the needed positional arguments\n\n### `doublestarredpart(func) -> callable`\n\nLike `doublestarred()`, but only passes keyword arguments that the function accepts.\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks only the needed keyword arguments\n\n### `unpackingpart(func) -> callable`\n\nLike `unpacking()`, but only passes as many arguments as the function needs (works with both positional and keyword arguments).\n\n**Parameters:**\n\n- `func`: The function to wrap\n\n**Returns:** A new function that unpacks only the needed arguments\n",
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"license": "Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n \n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n \n 1. Definitions.\n \n \"License\" shall mean the terms and conditions for use, reproduction,\n and distribution as defined by Sections 1 through 9 of this document.\n \n \"Licensor\" shall mean the copyright owner or entity authorized by\n the copyright owner that is granting the License.\n \n \"Legal Entity\" shall mean the union of the acting entity and all\n other entities that control, are controlled by, or are under common\n control with that entity. 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