Visualize and profile your python code with FlowVisor.


Keywords
python, flow, visualize, code, flowvisor, profiling, profile, decorator
License
MIT
Install
pip install FlowVisor==0.1.4

Documentation


FlowVisor

Visualize the flow of your python code.


FlowVisor-Example



Installation

pip install FlowVisor

Usage

from FlowVisor import FlowVisor, vis

@vis # This will visualize the function in the flow
def my_function():
    print("Hello World")

@vis
def my_other_function():
    my_function()

my_other_function()
FlowVisor.CONFIG.output_file = "example_graph" # You can add some configureation with the CONFIG object
FlowVisor.graph() # Generate the graph
FlowVisor.export("example_flow", "json") # Save the flow as json

CLI

add-vis

Adds the vis decorator to all functions in all python files in a directory.

add-vis -p <path-to-dir>

remove-vis

Removes the vis decorator from all functions in all python files in a directory.

remove-vis -p <path-to-dir>

vis-file

Generate a graph from a exported flow file.

vis-file -f <path-to-flow-file>

Overhead

The overhead of the FlowVisor is tried to be kept as low as possible. The overhead is mainly caused by the decorator. Therefore the time for running the logic of the Flowvisor is excluded from the profiling.

You can even descrease the overhead by the advanced_ovhead_reduction:

FlowVisor.enable_advanced_overhead_reduction()

Development

git clone https://github.com/cophilot/FlowVisor
cd FlowVisor
pip install -r requirements.txt

Example

Run the example:

pip install -r requirements.txt
python example.py

by Philipp B.