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Creating a custom directory tree is an efficient method for visually organizing your project's directory structure, complete with detailed information. It provides a clear model of your project layout for easy reference and management.
This project directory is organized using a hierarchical structure to efficiently manage and navigate through various files and directories. Below is a breakdown of the directory tree along with explanations for each directory and file.
pip install custom-tree
then run:
custom-tree
you will see your current directory tree in the console.
Saving Directory Tree: If you want to save the results of your current directory tree Run this
custom-tree --output OR -o file_name.txt
it will generate the results in the current directory file_name.txt
.
Installation Path: Ensure that the installation path for Python packages is included in your system's PATH environment variable. This path typically includes the Scripts directory inside the Python installation directory.
Shell Restart: If you're using a shell (like Bash), you might need to restart it to pick up the changes to the PATH environment variable.
Installation Location: Double-check the installation location of the package. If it's not installed in the expected location, you might need to investigate why the installation path is different.
Executable Name: Ensure that the name specified in the console_scripts
entry point in your setup.py
matches the
command you're trying to run. In this case, it should be custom-tree
.
Permissions: Make sure that you have the necessary permissions to execute commands from the installed package.
Virtual Environment: If you're using a virtual environment, ensure that it is activated when you try to run the command.
project_directory/
📂 src/
│ 📂 main/
│ │ 📂 java/
│ │ │ 📂 com/
│ │ │ 📄 Main.java
│ │ 📂 resources/
│ │ │ 📂 config/
│ │ │ 📄 application.properties
│ │ 📂 webapp/
│ │ 📄 index.html
│ 📂 test/
│ │ 📂 java/
│ │ │ 📂 com/
│ │ │ 📄 MainTest.java
│ │ │ 📂 example/
│ │ │ 📄 MainTest.java
│ │ 📂 resources/
│ │ 📂 test_config/
│ │ 📄 test.properties
📂 docs/
│ 📄 documentation.md
📄 README.md
📄 LICENSE
The custom-tree
tool now supports including hidden directories in the directory tree structure. Hidden directories are
those whose names begin with a dot (.
), such as .git
or .config
. By default, hidden directories are excluded from
the tree structure.
To include hidden directories in the tree structure, use the --hidden
flag when running the custom-tree
command:
custom-tree --hidden
Example: Consider the following directory structure:
📁 my_project/
| 📁 .git/
| | 📄 config
| | \--- ...
| 📁 src/
| | 📄 main.py
| | \--- ...
| 📁 tests/
| | 📄 test.py
| | 📁 test_directory/
| | | 📄 test_file.txt
| | \--- ...
| 📄 README.md
Without the --hidden flag, running dir-tree would output:
📁 my_project/
| 📄 src/
| | 📄 main.py
| | \--- ...
| 📄 tests/
| | 📄 test.py
| | \--- ...
| 📄 README.md
With the --hidden
flag, hidden directories are included:
📁 my_project/
| 📁 .git/
| | 📄 config
| | \--- ...
| 📁 src/
| | 📄 main.py
| | \--- ...
| 📁 tests/
| | 📄 test.py
| | 📁 test_directory/
| | | 📄 test_file.txt
| | \--- ...
| 📄 README.md
Note: Including hidden directories can be useful for inspecting the entire directory structure, including version control files (e.g., .git) or configuration directories (e.g., .config). However, be cautious when sharing or distributing directory tree structures that include hidden directories, as they may contain sensitive information.
If you have any issue please submit it here. https://github.com/dragon-devs/custom-tree
FAQs
Creating a custom directory tree is an efficient method for visually organizing your project's directory structure, complete with detailed information. It provides a clear model of your project layout for easy reference and management.
We found that custom-tree demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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