I think you could simply copying the visualize.py into the same directory as the script you are running.
If you wanted it in your lib/site-packages directory so you could import it with the neat module:
copy visualize.py into lib/site-packages/neat/ and modify __init__.py to add the line import neat.visualize as visualize. Delete the __pycache__ directory. Make sure you have modules installed: Numpy, GraphViz, and Matplotlib. When you've done the above, you should be able to import neat and access neat.visualize.
I don't recommend doing this though for several reasons:
- Say you wanted to update your neat module. Your visualize.py file is technically not part of the module. So it wouldn't be updated along with your neat module.
- the visualize.py file seems to be written in the context of the examples as opposed to being for general use with the module, so contextually, it doesn't belong there.
- At some point in the future, you might also forget that this wasn't a part of the module, but your code acts as if it was part of the API. So your code will break in some other neat installation.
GitHub
github.com › nicolashahn › import-visualizer
GitHub - nicolashahn/import-visualizer: Visualize the import relationships between all files in a python codebase
Visualize the import relationships between all modules in a python codebase.
Author nicolashahn
Ludochaordic
chezsoi.org › lucas › blog › python-modules-imports-visualization.html
Python module imports visualization - Ludochaordic
It is relatively straightforward, with a single notable trick: the conversion from a Python module path to a hue color value on a 360 degrees scale.
importerror - NEAT-Python not finding Visualize.py - Stack Overflow
So recently I have found about a NEAT algorithm and wanted to give it a try using NEAT-Python(not sure if this is even the correct source :| ). So I created my virtual environment activated it and More on stackoverflow.com
Visualizing Python Project Import Graphs
From the Readme examples it is not clear what is the point. The import graph is shown, but only as points. Is there any more data, like names of imports? More on reddit.com
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June 29, 2016python - Importing visualization function from .py file to use in .ipynb file - Stack Overflow
I am new to python and have some problems importing functions from a .py file to use in a .ipynb file.. I am trying to call the following function from my visualization_tb.py file: def treemap_show... More on stackoverflow.com
Visualize the structure of a Python module - Stack Overflow
Is there tool out there which can be used to graphically represent the structure of a python module? I'm thinking that a graph of sub-modules and classes connected by arrows representing imports. More on stackoverflow.com
Videos
PyPI
pypi.org › project › visualizer
visualizer · PyPI
March 19, 2020 - To use the second type Automatic ... the library from visualizer import Visualizer autoVis = Visualizer(df=df, # df: (dataframe) num_cols=num_cols, # num_cols: (list) of numerical columns....
» pip install visualizer
PyPI
pypi.org › project › visualize
visualize · PyPI
git clone https://github.com/rentainhe/visualization.git python example.py · results will be saved to ./test_grid_attention and ./test_region_attention ... import numpy as np from visualize import visualize_region_attention img_path="path/to/example.jpg" save_path="example" attention_retio=1.0 boxes = np.array([[14, 25, 100, 200], [56, 75, 245, 300]], dtype='int') boxes_attention = [0.36, 0.64] visualize_region_attention(img_path, save_path=save_path, boxes=boxes, box_attentions=boxes_attention, attention_ratio=attention_retio, save_image=True, save_origin_image=True, quality=100)
» pip install visualize
GitHub
github.com › CodeReclaimers › neat-python › blob › master › examples › xor › visualize.py
neat-python/examples/xor/visualize.py at master · CodeReclaimers/neat-python
Python implementation of the NEAT neuroevolution algorithm - neat-python/examples/xor/visualize.py at master · CodeReclaimers/neat-python
Author CodeReclaimers
Matplotlib
matplotlib.org
Matplotlib — Visualization with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
Databricks
docs.databricks.com › aws › en › notebooks › source › getting-started › import-visualize-data-python.html
import-visualize-data-python - Databricks
Databricks notebooks are collaborative, multi-language documents for data science and machine learning, with real-time coauthoring and built-in visualizations.
LinkedIn
linkedin.com › all › engineering › data visualization
What is the best way to import Python libraries for data visualization?
December 31, 2023 - O pypi é o oficial pra elas :) Aí meu caro, é instalar a lib usando pip install e depois realizar o import dela usando import. Qualquer questão que precisar responder num detalhe maior que esse vai encontrar na documentação da biblioteca. :) …see more ... Python offers a variety of libraries for data visualization, each with their own unique advantages and disadvantages.
Reddit
reddit.com › r/python › visualizing python project import graphs
r/Python on Reddit: Visualizing Python Project Import Graphs
June 29, 2016 - --- If you have questions or are new to Python use r/LearnPython ... Archived post. New comments cannot be posted and votes cannot be cast. Share ... From the Readme examples it is not clear what is the point. The import graph is shown, but only as points. Is there any more data, like names of imports? ... Once the visualization is displayed, you can inspect file names by hovering over a node.
Stack Overflow
stackoverflow.com › questions › 63395327 › importing-visualization-function-from-py-file-to-use-in-ipynb-file
python - Importing visualization function from .py file to use in .ipynb file - Stack Overflow
But importing functions from the .py file works good. I have tried to import a simple test function from .py and that one imports and works perfectely in the .ipynb file. Therefor I think there might be a problem with calling on functions to show plots and other visualization tools.
Medium
medium.com › @jrmandal2025 › importing-data-and-performing-data-visualization-in-python-3d92568898c2
Importing Data and Performing Data Visualization in Python | by Mithlesh Mandal | Dec, 2025 | Medium
December 1, 2025 - Before you can import data or visualize it, you need to bring in the right Python libraries. Libraries are pre-written collections of functions and tools that make working with data easier and faster.
GitHub
github.com › thebjorn › pydeps
GitHub - thebjorn/pydeps: Python Module Dependency graphs · GitHub
Python module dependency visualization. This package is primarily intended to be used from the command line through the pydeps command. Contents · How to install · Usage · Example · Notes · Configuration files · Bacon (Scoring) Import cycles · Clustering ·
Starred by 2.1K users
Forked by 134 users
Languages Python 97.8% | Dockerfile 2.2%
Gauge
gauge.sh › blog › how-to-visualize-your-python-projects-dependency-graph
How to Visualize your Python Project’s Dependency Graph - Gauge - Solving the monolith/microservices dilemma
In order to correctly visualize your existing dependencies, Tach will crawl the Python AST to figure out which modules import from each other.
Medium
medium.com › illumination › visualize-dependencies-between-python-modules-d6e8e9a92c50
Visualize dependencies between Python Modules | by Sambasivarao. K | ILLUMINATION | Medium
May 12, 2021 - --include-missing argument includes the python imports from other scripts as well. ... As you can see from above, It shows dependencies up to level-2. If you want to visualize only up to level-1 dependencies, use “--max-bacon 1”.
Top answer 1 of 4
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I think you want the Python library snakefood
sfood: Given a set of input files or root directories, generate a list of dependencies between the files;
sfood-graph: Read a list of dependencies and produce a Graphviz dot file. (This file can be run through the Graphviz dot tool to produce a viewable/printable PDF file);
2 of 4
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I know this question is very old. If someone is searching a tool for visualising the structure of a Python module, you can try Sourcetrail.
This tool helps you to visualise big source codes such as PyTorch or TensorFlow.
It starts with a nice overview of the project.
If you go inside the Classes button and select any class, it will show you the connection of a specific class with other classes and functions.
All the buttons are clickable and gives you a nice overview. This gives you a kickstart to understand the structure of unknown source code very easily.
Sisense
sisense.com › home › blog › data visualizations in python and r
Guide to Data Visualizations in Python and R - Sisense
March 17, 2026 - Here “Species” is target variable ... and “Petal Width.” · First import basic libraries like numpy and pandas and Python data visualization libraries like matplotlib and seaborn....
Dataquest
dataquest.io › blog › python-data-visualization-libraries
Python Data Visualization Libraries – Dataquest
January 26, 2026 - Before we get into visualizing the data, let's take a quick look at the dataset we'll be working with. We'll be using data from openflights. We'll be using route, airport, and airline data. Each row in the route data corresponds to an airline route between two airports. Each row in the airport data corresponds to an airport in the world, and has information about it. Each row in the airline data represents a single airline. We first read in the data: # Import the pandas library.
Hex
hex.tech › home › templates › data visualization › python data visualization
Python Data Visualization Libraries and Examples | Hex
To begin with, we will need the Python libraries matplotlib, seaborn, plotly, and altair. These libraries come preinstalled in the Hex environment but in case they are not present you can install them using PIP as follows: ... Once the libraries are installed, you can load them into the Hex environment with the help of the following lines of code: ... import matplotlib.pyplot as plt import seaborn as sns import plotly.express as px import altair as alt
Berkeleyautomation
berkeleyautomation.github.io › visualization › install › install.html
Python Installation — visualization 1.0.0 documentation
Python Installation · View page source · This package is installable via pip · $ pip install visualization · Building visualization’s documentation requires a few extra dependencies – specifically, sphinx and a few plugins. To install the dependencies required, simply change directories ...