squares
is a Python-based command-line application that finds the two closest square numbers to a given input number.
To install squares
, use pip
:
pip install squares-cli
This will install the squares
command, allowing you to find the closest square numbers directly from the command line.
The squares
command can find the two closest square numbers (one above and one below) to a given input number. You can use it in various ways, specifying options to control the output.
squares [OPTIONS] <number>
If no options are specified, squares
will output both the closest square number below and the closest square number above the given input, separated by a comma.
--below
- Outputs only the closest square below the input number.--above
- Outputs only the closest square above the input number.--both
- Outputs both the closest squares (this is the default behavior if no option is specified).-h
or--help
- Displays the help message.
Here are some example commands and their expected outputs:
squares 12
Output:
9, 16
In this example, squares 12
finds the closest squares around 12, returning both the closest square below (9) and the closest square above (16).
squares --below 12
Output:
9
This example uses --below
to return only the closest square below 12, which is 9.
squares --above 12
Output:
16
Here, --above
is used to return only the closest square above 12, which is 16.
squares --both 12
Output:
9, 16
Using --both
explicitly returns both closest squares around 12. This produces the same result as the default behavior.
A man page is also included in the installation. You can access it by typing:
man squares
This will display comprehensive information about the command, options, and examples, similar to what is provided in this README.
- Operating System Compatibility:
squares
is compatible with UNIX-like systems (Linux and macOS) and Windows, though the man page installation may vary depending on the OS. - Python Version: This package requires Python 3.6 or higher.[
This project is licensed under the MIT License.
This README.md
provides a clear description of what the package does, how to install and use it, and includes examples and notes for further clarification. Let me know if there’s anything else you’d like added or modified!]