This repository contains a collection of Python scripts that can be used in conjunction with Bash scripts to aid in various tasks, such as studying, productivity, and automation.
The pomodoro script is a Python script that implements the Pomodoro Technique, a time management method that uses a timer to break down work into intervals, traditionally 25 minutes in length, separated by short breaks. The script allows you to specify the number of Pomodoro cycles to run and the end timer sound file to play.
To use the pomodoro script, you can run the pomodoro.sh Bash script provided in the repository:
./pomodoro.sh
This will start a Pomodoro timer with 4 cycles and play the crowd.mp3 sound file at the end of each cycle and break. You can adjust the number of cycles and the end timer sound file by editing the pomodoro.sh script or by passing command-line arguments to the pomodoro.py script directly.
pomodoro.py: The Python script that implements the Pomodoro timer logic.pomodoro.sh: A Bash script that runs thepomodoro.pyscript with default options.sounds/: A directory containing sound files that can be played at the end of each Pomodoro cycle and break.
The Lofi script is a Python script that will play the Lofi music for you in the background!
To use the lofi-music.py script, you can run it like this:
python study_music.py --option
Options:
- --play
- --stop
This is a Python script that runs SEO, performance, best practices, and accessibility tests on a website. It uses the lighthouse cli to perform these tests.
Install the lighthouse CLI
npm install -g lighthouse
Install Chrome Browser
To run the tests, use the following command:
python site-lighthouse.py <website-url> -p
Replace <website-url> with the URL of the website you want to test.
The script will then perform SEO, performance, best practices, and accessibility tests on the website, and print the results to the console.
This is a command-line interface (CLI) written in Python that uses the OpenAI API to generate answers to technical and code-related questions. The CLI takes a prompt text as input, along with optional arguments for the OpenAI model to use and the temperature to use for generating the answer.
To use the OpenAI Question Answering CLI, you'll need to have Python 3 installed on your machine, along with the OpenAI Python module. You can install the OpenAI module using pip:
pip install openai
Once you have Python and the OpenAI module installed, you can download the openai_qa.py script from this repository and save it to your computer.
To use the OpenAI Question Answering CLI, simply run the openai_qa.py script from the command line, passing in the prompt text as a required argument:
python openai_qa.py "What is a Python decorator and how does it work?"
This will generate an answer to the specified question using the text-davinci-002 model and a temperature of 0.5, and print the answer to the console.
You can also specify the OpenAI model to use and the temperature by passing in optional arguments:
python openai_qa.py "What is a Python decorator and how does it work?" --model text-curie-001 --temperature 0.3
This will generate an answer to the specified question using the text-curie-001 model and a temperature of 0.3, and print the answer to the console.
The following command-line options are available for the OpenAI Question Answering CLI:
prompt_text(required): The prompt text for the question to generate an answer for.--model(optional): The name of the OpenAI API model to use (default: text-davinci-002).--temperature(optional): The temperature to use for generating the answer (default: 0.5).
The generate_transcript.py script is a Python script that uses the SpeechRecognition module to generate a transcript from a video. It supports various video formats and uses the Google Speech Recognition API to recognize the speech in the audio.
To use the generate_transcript.py script, you can run it like this:
python generate_transcript.py path/to/video.mp4
This command will generate a transcript from the audio in the video file at the specified path and print the transcript to the console. You can also specify the path to save the transcript file using the --output argument, like this:
python generate_transcript.py path/to/video.mp4 --output path/to/transcript.txt
This command will generate the transcript and save it to the specified file path.
generate_transcript.py: The Python script that generates a transcript from a video file.
The aliases.sh script is a Bash script that defines a set of useful aliases for common Bash commands and scripts. The aliases include commands to navigate the file system, search for files, and run Python scripts.
To use the aliases.sh script, you can run it in your Bash terminal:
source aliases.sh
Or
./aliases.sh
This will define the aliases for the current terminal session. You can also add this command to your .bashrc file to make the aliases available every time you open a new terminal.
aliases.sh: A Bash script that defines a set of useful aliases.
Feel free to contribute to this repository by adding new Python scripts or improving the existing ones. Please submit a pull request with your changes, and make sure to include documentation and usage instructions for any new scripts.