# Parslet: Your Pocket-Sized Workflow Assistant
**A tiny tool for running automated to-do lists (we call them workflows) on your Python projects. It's built to work anywhere, especially on your phone.**
### So, What is Parslet?
Parslet is a tiny workflow engine built in Python. That means it's a tool that helps you automate a bunch of tasks in a specific order, especially on phones and devices that can’t run heavy-duty software. Think of it like a smart to-do list for your computer or phone, but instead of reminding you to do things, **it actually does them for you in the right order, automatically.**
Imagine this real-world example:
You run a small juice business with your besty. Every morning you:
1. Wash the fruits
2. Peel them
3. Blend them
4. Pour into bottles
5. Label and store
Now imagine you could automate this entire process using a small robot. You just tell it the steps once, and it does them every morning, in order. You get to spend quality time with your besty.
**That’s what Parslet does, but for software tasks.**
---
### What Kinds of Tasks Can It Handle?
In a real-world tech setting, you could use Parslet to:
1. Run a script to **collect data** from a website.
2. Then, **clean up** that messy data.
3. Then, **save** the clean data to a file.
4. Then, **back up** that file to a server.
5. Finally, **send you an email** confirming the job is done.
All of this, in the right order, without you needing to babysit it.
---
### Why is Parslet Special?
Most tools like this are built for powerful servers in a data center. Parslet is different. It’s designed from the ground up to:
- **Be Super Lightweight:** It works on a Raspberry Pi or even an Android phone.
- **Run in Termux:** It’s built and tested to work perfectly inside [Termux](https://termux.dev/en/), the command-line tool for Android.
- **Work Offline:** No internet? No problem. Your workflows will still run.
- **Empower Everyone:** It’s for students, creators, and developers in Africa and beyond who might not have a laptop but have a brilliant idea.
---
### How Does It Work?
It uses something called a **DAG** (Directed Acyclic Graph), which is just a fancy way of saying:
> “Step B only runs after Step A is done.”
You define these steps (we call them **Tasks**) in a simple Python file. Parslet reads your file, understands the order, and handles the rest. It manages failures and runs everything as efficiently as possible.
---
## Get Started
Ready to try it? You can be up and running in less than a minute.
1. **Get the Code:**
First, you'll need to copy the project files to your device using a CLI.
```bash
git clone https://github.com/Kanegraffiti/Parslet.git
cd Parslet
```
2. **Install It:**
Now, have Python install Parslet so you can use it from anywhere.
```bash
pip install .
```
3. **Create Your First "Recipe"**
Create a new file called `my_first_workflow.py` and paste this in. This is your recipe, telling Parslet what to do.
```python
from parslet import parslet_task, ParsletFuture
from typing import List
# This is a "task." It's just a normal Python function
# with a special @parslet_task note for Parslet.
@parslet_task
def say_hello(name: str) -> str:
print(f"Task 1: Saying hello to {name}")
return f"Hello, {name}!"
# Here's a second task.
@parslet_task
def make_it_loud(text: str) -> str:
print("Task 2: Making the text loud!")
return f"{text.upper()}!"
# This is the main "recipe" function.
# Parslet looks for this to know how your tasks connect.
def main() -> List[ParsletFuture]:
# First, we tell Parslet to run the say_hello task.
# It doesn't run yet! It just gives us an "IOU" for the result.
greeting_iou = say_hello("Parslet")
# Next, we give the "IOU" from the first task to the second task.
# This tells Parslet: "Wait for task 1 to finish before starting task 2."
loud_greeting_iou = make_it_loud(greeting_iou)
# We return the very last IOU. This tells Parslet, "We're done when this is done."
return [loud_greeting_iou]
```
4. **Run It**
Now for the fun part. Tell Parslet to run your new recipe.
```bash
parslet run my_first_workflow.py
```
You'll see the `print` statements from your tasks as they run, in the correct order!
---
## What Else Can It Do?
Parslet is small, but it's packed with neat features for real-world use.
- **Works Offline:** Your automated recipes run even without an internet connection.
- **Saves Battery:** Use the special `--battery-mode` to tell Parslet to take it easy and conserve power.
- **Smart About Resources:** It automatically checks your device's CPU and memory to run smoothly without crashing.
- **DEFCON:** A multi-layered defense system in Parslet that proactively blocks zero-day exploits and malicious DAG behavior using offline rules.
- **Plays Well with Others:** If you ever move to a big server, Parslet has tools to convert your recipes to run on powerful systems like Parsl or Dask.
- **Made for Termux:** We use it and test it on Android phones, so you know it'll work.
Want to see more? Check out the `use_cases/` and `examples/` folders for more advanced recipes!
---
## Visualizing Your Workflows
Parslet can generate a picture of your workflow (a "DAG") to help you see how your tasks are connected. This is great for debugging and documentation.
To use this feature, you need to have **Graphviz** installed on your system.
- **On Linux (Debian/Ubuntu):** `sudo apt install graphviz`
- **On Linux (Fedora):** `sudo dnf install graphviz`
- **On Android (Termux):** `pkg install graphviz`
- **On Windows:** Download and run the installer from the [official Graphviz website](https://graphviz.org/download/) and make sure to add it to your system's PATH.
You will also need the `pydot` Python package, which is included in `requirements.txt`.
Once Graphviz is installed, you can use the `--export-png` flag with the `run` command:
```bash
parslet run my_first_workflow.py --export-png my_workflow.png
```
This will create an image file named `my_workflow.png` showing your workflow.
---
## Want to Learn More? (Documentation)
We've written down everything you need to know in a simple, friendly way.
- [**See All Features (Full Documentation)**](https://parslet.readthedocs.io/en/latest/)
- [**How It Really Works (Architecture)**](https://parslet.readthedocs.io/en/latest/architecture.html)
- [**The Remote Control (CLI Commands)**](https://parslet.readthedocs.io/en/latest/usage.html)
---
## Contributing
We'd love your help making Parslet even better. It's easy to get started. Check out our [Contributing Guide](./CONTRIBUTING.md).
---
## License
This project is licensed under the MIT License. See [LICENSE](./LICENSE) for the full text.
## Acknowledgements
Built by [Kelechi Nwankwo](https://github.com/Kanegraffiti) for the **Africa Deep Tech Challenge 2025**.
Inspired by the powerful [Parsl](https://github.com/Parsl/parsl) project.
A big thank you to the Outreachy community and the Parsl maintainers.
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"description": "# Parslet: Your Pocket-Sized Workflow Assistant\n**A tiny tool for running automated to-do lists (we call them workflows) on your Python projects. It's built to work anywhere, especially on your phone.**\n\n\n\n\n\n### So, What is Parslet?\n\nParslet is a tiny workflow engine built in Python. That means it's a tool that helps you automate a bunch of tasks in a specific order, especially on phones and devices that can\u2019t run heavy-duty software. Think of it like a smart to-do list for your computer or phone, but instead of reminding you to do things, **it actually does them for you in the right order, automatically.**\n\nImagine this real-world example:\n\nYou run a small juice business with your besty. Every morning you:\n\n1. Wash the fruits\n2. Peel them\n3. Blend them\n4. Pour into bottles\n5. Label and store\n\nNow imagine you could automate this entire process using a small robot. You just tell it the steps once, and it does them every morning, in order. You get to spend quality time with your besty.\n\n**That\u2019s what Parslet does, but for software tasks.**\n\n---\n\n### What Kinds of Tasks Can It Handle?\n\nIn a real-world tech setting, you could use Parslet to:\n\n1. Run a script to **collect data** from a website.\n2. Then, **clean up** that messy data.\n3. Then, **save** the clean data to a file.\n4. Then, **back up** that file to a server.\n5. Finally, **send you an email** confirming the job is done.\n\nAll of this, in the right order, without you needing to babysit it.\n\n---\n\n### Why is Parslet Special?\n\nMost tools like this are built for powerful servers in a data center. Parslet is different. It\u2019s designed from the ground up to:\n\n- **Be Super Lightweight:** It works on a Raspberry Pi or even an Android phone.\n- **Run in Termux:** It\u2019s built and tested to work perfectly inside [Termux](https://termux.dev/en/), the command-line tool for Android.\n- **Work Offline:** No internet? No problem. Your workflows will still run.\n- **Empower Everyone:** It\u2019s for students, creators, and developers in Africa and beyond who might not have a laptop but have a brilliant idea.\n\n---\n\n### How Does It Work?\n\nIt uses something called a **DAG** (Directed Acyclic Graph), which is just a fancy way of saying:\n\n> \u201cStep B only runs after Step A is done.\u201d\n\nYou define these steps (we call them **Tasks**) in a simple Python file. Parslet reads your file, understands the order, and handles the rest. It manages failures and runs everything as efficiently as possible.\n\n---\n\n## Get Started\n\nReady to try it? You can be up and running in less than a minute.\n\n1. **Get the Code:**\n\n First, you'll need to copy the project files to your device using a CLI.\n\n ```bash\n git clone https://github.com/Kanegraffiti/Parslet.git\n cd Parslet\n ```\n\n2. **Install It:**\n\n Now, have Python install Parslet so you can use it from anywhere.\n\n ```bash\n pip install .\n ```\n\n3. **Create Your First \"Recipe\"**\n\n Create a new file called `my_first_workflow.py` and paste this in. This is your recipe, telling Parslet what to do.\n\n ```python\n from parslet import parslet_task, ParsletFuture\n from typing import List\n\n # This is a \"task.\" It's just a normal Python function\n # with a special @parslet_task note for Parslet.\n @parslet_task\n def say_hello(name: str) -> str:\n print(f\"Task 1: Saying hello to {name}\")\n return f\"Hello, {name}!\"\n\n # Here's a second task.\n @parslet_task\n def make_it_loud(text: str) -> str:\n print(\"Task 2: Making the text loud!\")\n return f\"{text.upper()}!\"\n\n # This is the main \"recipe\" function.\n # Parslet looks for this to know how your tasks connect.\n def main() -> List[ParsletFuture]:\n # First, we tell Parslet to run the say_hello task.\n # It doesn't run yet! It just gives us an \"IOU\" for the result.\n greeting_iou = say_hello(\"Parslet\")\n \n # Next, we give the \"IOU\" from the first task to the second task.\n # This tells Parslet: \"Wait for task 1 to finish before starting task 2.\"\n loud_greeting_iou = make_it_loud(greeting_iou)\n\n # We return the very last IOU. This tells Parslet, \"We're done when this is done.\"\n return [loud_greeting_iou]\n ```\n\n4. **Run It**\n\n Now for the fun part. Tell Parslet to run your new recipe.\n\n ```bash\n parslet run my_first_workflow.py\n ```\n\nYou'll see the `print` statements from your tasks as they run, in the correct order!\n\n---\n\n## What Else Can It Do? \n\nParslet is small, but it's packed with neat features for real-world use.\n\n- **Works Offline:** Your automated recipes run even without an internet connection.\n- **Saves Battery:** Use the special `--battery-mode` to tell Parslet to take it easy and conserve power.\n- **Smart About Resources:** It automatically checks your device's CPU and memory to run smoothly without crashing.\n- **DEFCON:** A multi-layered defense system in Parslet that proactively blocks zero-day exploits and malicious DAG behavior using offline rules.\n- **Plays Well with Others:** If you ever move to a big server, Parslet has tools to convert your recipes to run on powerful systems like Parsl or Dask.\n- **Made for Termux:** We use it and test it on Android phones, so you know it'll work.\n\nWant to see more? Check out the `use_cases/` and `examples/` folders for more advanced recipes!\n\n---\n\n## Visualizing Your Workflows\n\nParslet can generate a picture of your workflow (a \"DAG\") to help you see how your tasks are connected. This is great for debugging and documentation.\n\nTo use this feature, you need to have **Graphviz** installed on your system.\n\n- **On Linux (Debian/Ubuntu):** `sudo apt install graphviz`\n- **On Linux (Fedora):** `sudo dnf install graphviz`\n- **On Android (Termux):** `pkg install graphviz`\n- **On Windows:** Download and run the installer from the [official Graphviz website](https://graphviz.org/download/) and make sure to add it to your system's PATH.\n\nYou will also need the `pydot` Python package, which is included in `requirements.txt`.\n\nOnce Graphviz is installed, you can use the `--export-png` flag with the `run` command:\n\n```bash\nparslet run my_first_workflow.py --export-png my_workflow.png\n```\n\nThis will create an image file named `my_workflow.png` showing your workflow.\n\n---\n\n## Want to Learn More? (Documentation)\n\nWe've written down everything you need to know in a simple, friendly way.\n\n- [**See All Features (Full Documentation)**](https://parslet.readthedocs.io/en/latest/)\n- [**How It Really Works (Architecture)**](https://parslet.readthedocs.io/en/latest/architecture.html)\n- [**The Remote Control (CLI Commands)**](https://parslet.readthedocs.io/en/latest/usage.html)\n\n---\n\n## Contributing\n\nWe'd love your help making Parslet even better. It's easy to get started. Check out our [Contributing Guide](./CONTRIBUTING.md).\n\n---\n\n## License\n\nThis project is licensed under the MIT License. See [LICENSE](./LICENSE) for the full text.\n\n## Acknowledgements\n\nBuilt by [Kelechi Nwankwo](https://github.com/Kanegraffiti) for the **Africa Deep Tech Challenge 2025**. \nInspired by the powerful [Parsl](https://github.com/Parsl/parsl) project. \nA big thank you to the Outreachy community and the Parsl maintainers.\n",
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