# GTPyhop
GTPyhop is a task-planning system based on [Pyhop](https://bitbucket.org/dananau/pyhop/src/master/), but generalized to plan for both goals and tasks.
[Dana Nau](https://www.cs.umd.edu/~nau/) is the original developper of GTPyhop.
## The pip Branch
[This pip branch](https://github.com/PCfVW/GTPyhop/tree/pip) is forked from [Dana Nau's GTPyhop main branch](https://github.com/dananau/GTPyhop) and refactored for PyPI distribution.
The file tree structure of [this pip branch](https://github.com/PCfVW/GTPyhop/tree/pip), produced with the help of [_GithubTree](https://github.com/mgks/GitHubTree), is the following:
```
📄 LICENSE.txt
📄 pyproject.toml
📄 README.md
📁 src/
└── 📁 gtpyhop/
├── 📄 __init__.py
├── 📁 examples/
├── 📄 __init__.py
├── 📁backtracking_htn.py
├── 📁blocks_goal_splitting/
├── 📄 __init__.py
├── 📄 actions.py
├── 📄 examples.py
├── 📄 methods.py
└── 📄 README.txt
├── 📁 blocks_gtn/
├── 📄 __init__.py
├── 📄 actions.py
├── 📄 examples.py
├── 📄 methods.py
└── 📄 README.txt
├── 📁 blocks_hgn/
├── 📄 __init__.py
├── 📄 actions.py
├── 📄 examples.py
└── 📄 methods.py
├── 📁 blocks_htn/
├── 📄 __init__.py
├── 📄 actions.py
├── 📄 examples.py
└── 📄 methods.py
├── 📄 logistics_hgn.py
├── 📄 pyhop_simple_travel_example.py
├── 📄 regression_tests.py
├── 📄 simple_hgn.py
├── 📄 simple_htn_acting_error.py
└── 📄 simple_htn.py
├── 📄 main.py
└── 📁 test_harness/
├── 📄 __init__.py
└── 📄 test_harness.py
```
## Installation from PyPI (soon available)
Open a terminal and type the following:
```bash
pip install gtpyhop
```
[uv](https://docs.astral.sh/uv/) can of course be used if you prefer:
```bash
uv pip install gtpyhop
```
## Installation from github
Alternatively, you can directly install from github:
```bash
git clone -b pip https://github.com/PCfVW/GTPyhop.git
cd GTPyhop
pip install .
```
## Testing your installation
We suggest you give gtpyhop a try straight away; start an interactive python session:
```bash
python
```
.. and import gtpyhop to run the regression tests:
```python
# Import the main GTPyhop planning system
import gtpyhop
```
The following should be printed in your terminal:
```code
Imported GTPyhop version 1.2.0
Messages from find_plan will be prefaced with 'FP>'.
Messages from run_lazy_lookahead will be prefaced with 'RLL>'.
Using iterative seek_plan.
```
Now import the regression tests module:
```python
from gtpyhop.examples import regression_tests
```
Be prepared to see a lot of information on the screen about the examples and how to solve them, with different levels of verbosity; with this in mind, run the regression tests:
```python
regression_tests.main()
```
The last lines printed in your terminal should be:
```code
-----------------------------------------------------------------------
Created the domain 'gtpyhop.examples.simple_htn_acting_error'. To run the examples, type this:
gtpyhop.examples.simple_htn_acting_error.main()
Finished without error.
```
Happy Planning!
## Usage
You have successfully installed and tested gtpyhop; it's time to declare your own planning problems in gtpyhop.
Please read [Dana's additional information](https://github.com/dananau/GTPyhop/blob/main/additional_information.md) of how to implement:
- [States](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#states)
- [Actions](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#actions)
- [Tasks and task methods](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#3-tasks-and-task-methods)
- [Goals and goal methods](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#4-goals-and-goal-methods)
- ...and much more about GTPyhop!
## New Features
### Iterative Planning Strategy
[This pip branch](https://github.com/PCfVW/GTPyhop/tree/pip) introduces a new iterative planning strategy that enhances the planner's capabilities for large planning scenarios; it is the default strategy.
Once gtpyhop is imported, Dana Nau's original recursive strategy can be set calling:
```python
set_recursive_strategy(True) # Planning strategy now is recursive
```
### New Functions
The following functions have been added to Dana's original code:
- `print_domain_names`
- `find_domain_by_name`, `is_domain_created`
- `set_current_domain`, `get_current_domain`
- `set_recursive_planning`, `get_recursive_planning`, `reset_planning_strategy`
- `set_verbose_level`, `get_verbose_level`
- `seek_plan_iterative`,
- `refine_multigoal_and_continue_iterative`
- `refine_unigoal_and_continue_iterative`
- `refine_task_and_continue_iterative`
- `apply_action_and_continue_iterative`
### Renaming
`_recursive` has been added at the end of the identifiers of the original functions involved in seeking for a plan:
- seek_plan → `seek_plan_recursive`
- _apply_action_and_continue → `apply_action_and_continue_recursive`
- _refine_multigoal_and_continue → `refine_multigoal_and_continue_recursive`
- _refine_unigoal_and_continue → `refine_unigoal_and_continue_recursive`
- _refine_task_and_continue → `refine_task_and_continue_recursive`
## Version History
> **1.2.0** -- Uploaded to PyPI: https://pypi.org/project/gtpyhop/
> 1.2.0rc1 -- Uploaded to Test PyPI: https://test.pypi.org/project/gtpyhop/1.2.0rc1/
> 1.2.0b2 -- This tested refactored version will soon be ready to be indexed on TestPyPI as 1.2.0rc1
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"description": "# GTPyhop\n\nGTPyhop is a task-planning system based on [Pyhop](https://bitbucket.org/dananau/pyhop/src/master/), but generalized to plan for both goals and tasks.\n\n[Dana Nau](https://www.cs.umd.edu/~nau/) is the original developper of GTPyhop.\n\n## The pip Branch\n\n[This pip branch](https://github.com/PCfVW/GTPyhop/tree/pip) is forked from [Dana Nau's GTPyhop main branch](https://github.com/dananau/GTPyhop) and refactored for PyPI distribution.\n\nThe file tree structure of [this pip branch](https://github.com/PCfVW/GTPyhop/tree/pip), produced with the help of [_GithubTree](https://github.com/mgks/GitHubTree), is the following:\n\n```\n\ud83d\udcc4 LICENSE.txt\n\ud83d\udcc4 pyproject.toml\n\ud83d\udcc4 README.md\n\ud83d\udcc1 src/\n \u2514\u2500\u2500 \ud83d\udcc1 gtpyhop/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc1 examples/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc1backtracking_htn.py\n \u251c\u2500\u2500 \ud83d\udcc1blocks_goal_splitting/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc4 actions.py\n \u251c\u2500\u2500 \ud83d\udcc4 examples.py\n \u251c\u2500\u2500 \ud83d\udcc4 methods.py\n \u2514\u2500\u2500 \ud83d\udcc4 README.txt\n \u251c\u2500\u2500 \ud83d\udcc1 blocks_gtn/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc4 actions.py\n \u251c\u2500\u2500 \ud83d\udcc4 examples.py\n \u251c\u2500\u2500 \ud83d\udcc4 methods.py\n \u2514\u2500\u2500 \ud83d\udcc4 README.txt\n \u251c\u2500\u2500 \ud83d\udcc1 blocks_hgn/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc4 actions.py\n \u251c\u2500\u2500 \ud83d\udcc4 examples.py\n \u2514\u2500\u2500 \ud83d\udcc4 methods.py\n \u251c\u2500\u2500 \ud83d\udcc1 blocks_htn/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u251c\u2500\u2500 \ud83d\udcc4 actions.py\n \u251c\u2500\u2500 \ud83d\udcc4 examples.py\n \u2514\u2500\u2500 \ud83d\udcc4 methods.py\n \u251c\u2500\u2500 \ud83d\udcc4 logistics_hgn.py\n \u251c\u2500\u2500 \ud83d\udcc4 pyhop_simple_travel_example.py\n \u251c\u2500\u2500 \ud83d\udcc4 regression_tests.py\n \u251c\u2500\u2500 \ud83d\udcc4 simple_hgn.py\n \u251c\u2500\u2500 \ud83d\udcc4 simple_htn_acting_error.py\n \u2514\u2500\u2500 \ud83d\udcc4 simple_htn.py\n \u251c\u2500\u2500 \ud83d\udcc4 main.py\n \u2514\u2500\u2500 \ud83d\udcc1 test_harness/\n \u251c\u2500\u2500 \ud83d\udcc4 __init__.py\n \u2514\u2500\u2500 \ud83d\udcc4 test_harness.py\n```\n\n## Installation from PyPI (soon available)\n\nOpen a terminal and type the following:\n\n```bash\npip install gtpyhop\n```\n\n[uv](https://docs.astral.sh/uv/) can of course be used if you prefer:\n\n```bash\nuv pip install gtpyhop\n```\n\n## Installation from github\n\nAlternatively, you can directly install from github:\n\n```bash\ngit clone -b pip https://github.com/PCfVW/GTPyhop.git\ncd GTPyhop\npip install .\n```\n\n## Testing your installation\n\nWe suggest you give gtpyhop a try straight away; start an interactive python session:\n```bash\npython\n```\n\n.. and import gtpyhop to run the regression tests:\n\n```python\n# Import the main GTPyhop planning system\nimport gtpyhop\n```\n\nThe following should be printed in your terminal:\n\n```code\nImported GTPyhop version 1.2.0\nMessages from find_plan will be prefaced with 'FP>'.\nMessages from run_lazy_lookahead will be prefaced with 'RLL>'.\nUsing iterative seek_plan.\n```\n\nNow import the regression tests module:\n\n```python\nfrom gtpyhop.examples import regression_tests\n```\n\nBe prepared to see a lot of information on the screen about the examples and how to solve them, with different levels of verbosity; with this in mind, run the regression tests:\n\n```python\nregression_tests.main()\n```\n\nThe last lines printed in your terminal should be:\n\n```code\n-----------------------------------------------------------------------\nCreated the domain 'gtpyhop.examples.simple_htn_acting_error'. To run the examples, type this:\ngtpyhop.examples.simple_htn_acting_error.main()\n\nFinished without error.\n```\n\nHappy Planning!\n\n## Usage\n\nYou have successfully installed and tested gtpyhop; it's time to declare your own planning problems in gtpyhop.\n\nPlease read [Dana's additional information](https://github.com/dananau/GTPyhop/blob/main/additional_information.md) of how to implement:\n- [States](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#states)\n- [Actions](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#actions)\n- [Tasks and task methods](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#3-tasks-and-task-methods)\n- [Goals and goal methods](https://github.com/dananau/GTPyhop/blob/main/additional_information.md#4-goals-and-goal-methods)\n- ...and much more about GTPyhop!\n\n## New Features\n\n### Iterative Planning Strategy\n\n[This pip branch](https://github.com/PCfVW/GTPyhop/tree/pip) introduces a new iterative planning strategy that enhances the planner's capabilities for large planning scenarios; it is the default strategy.\n\nOnce gtpyhop is imported, Dana Nau's original recursive strategy can be set calling:\n\n```python\nset_recursive_strategy(True) # Planning strategy now is recursive\n```\n\n### New Functions\n\nThe following functions have been added to Dana's original code:\n\n- `print_domain_names`\n- `find_domain_by_name`, `is_domain_created`\n- `set_current_domain`, `get_current_domain`\n- `set_recursive_planning`, `get_recursive_planning`, `reset_planning_strategy`\n- `set_verbose_level`, `get_verbose_level`\n- `seek_plan_iterative`,\n - `refine_multigoal_and_continue_iterative`\n - `refine_unigoal_and_continue_iterative`\n - `refine_task_and_continue_iterative`\n - `apply_action_and_continue_iterative`\n\n### Renaming\n\n`_recursive` has been added at the end of the identifiers of the original functions involved in seeking for a plan: \n\n- seek_plan → `seek_plan_recursive`\n- _apply_action_and_continue → `apply_action_and_continue_recursive`\n- _refine_multigoal_and_continue → `refine_multigoal_and_continue_recursive`\n- _refine_unigoal_and_continue → `refine_unigoal_and_continue_recursive`\n- _refine_task_and_continue → `refine_task_and_continue_recursive`\n\n\n## Version History\n\n> **1.2.0** -- Uploaded to PyPI: https://pypi.org/project/gtpyhop/\n\n> 1.2.0rc1 -- Uploaded to Test PyPI: https://test.pypi.org/project/gtpyhop/1.2.0rc1/\n\n> 1.2.0b2 -- This tested refactored version will soon be ready to be indexed on TestPyPI as 1.2.0rc1\n",
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