# Mr. Graph
[](https://mr-graph.readthedocs.io/en/latest/?badge=latest)
Welcome to Mr. Graph!
Mr. Graph is a python library designed to make composing graphs of sync and async functions easy! Use google style docstrings to automagically create dataclasses and chain together function calls into graphs.
## Features
- Use with either async or sync functions
- Uses google style doc strings to name return values.
- Creates dataclasses for each function's output.
- Can infer pipelines from input and output signatures
- All directed acyclic graph layouts supported. linear, fan-in, fan-out.
## Example Usage
Building graphs can be as easy as:
```python
from mr_graph import Graph
def return_one():
"""
return 1
return one with no inputs
Returns
-------
m : float
equal to 1
"""
return 1
async def add_1(m: float):
"""
add 1 to a number
add 1 to the input value n.
Parameters
----------
n : float
number to add 1 to.
Returns
-------
n : float
equal to n + 1
"""
return n + 1
async def build_implicit_linear_graph():
"""
Return 2
Simple example linear graph. Wired up automagically using the input and output variable names.
Parameters
----------
Returns
-------
two : float
always equal to 2
"""
g = Graph(nodes=[return_one, add_1])
return await g()
```
More information can be found on read the docs!
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"description": "# Mr. Graph\n\n[](https://mr-graph.readthedocs.io/en/latest/?badge=latest)\n\nWelcome to Mr. Graph!\n\nMr. Graph is a python library designed to make composing graphs of sync and async functions easy! Use google style docstrings to automagically create dataclasses and chain together function calls into graphs.\n\n## Features\n\n- Use with either async or sync functions\n- Uses google style doc strings to name return values.\n- Creates dataclasses for each function's output.\n- Can infer pipelines from input and output signatures\n- All directed acyclic graph layouts supported. linear, fan-in, fan-out.\n\n\n## Example Usage\n\nBuilding graphs can be as easy as:\n\n```python\nfrom mr_graph import Graph\n\ndef return_one():\n \"\"\"\n return 1\n\n return one with no inputs\n\n Returns\n -------\n m : float\n equal to 1\n \"\"\"\n return 1\n \nasync def add_1(m: float):\n \"\"\"\n add 1 to a number\n\n add 1 to the input value n.\n\n Parameters\n ----------\n n : float\n number to add 1 to.\n\n Returns\n -------\n n : float\n equal to n + 1\n \"\"\"\n return n + 1\n\nasync def build_implicit_linear_graph():\n \"\"\"\n Return 2\n\n Simple example linear graph. Wired up automagically using the input and output variable names.\n\n Parameters\n ----------\n \n Returns\n -------\n two : float\n always equal to 2\n \"\"\"\n\n g = Graph(nodes=[return_one, add_1])\n return await g()\n```\n\nMore information can be found on read the docs!\n",
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