# Ingredient Parser
The Ingredient Parser package is a Python package for parsing structured information out of recipe ingredient sentences.
## Documentation
Documentation on using the package and training the model can be found at https://ingredient-parser.readthedocs.io/.
## Quick Start
Install the package using pip
```bash
$ python -m pip install ingredient-parser-nlp
```
Import the ```parse_ingredient``` function and pass it an ingredient sentence.
```python
>>> from ingredient_parser import parse_ingredient
>>> parse_ingredient("3 pounds pork shoulder, cut into 2-inch chunks")
ParsedIngredient(
name=[IngredientText(text='pork shoulder', confidence=0.999193)],
size=None,
amount=[IngredientAmount(quantity='3',
unit=<Unit('pound')>,
text='3 pounds',
confidence=0.999906,,
APPROXIMATE=False,
SINGULAR=False)],
preparation=IngredientText(text='cut into 2 inch chunks', confidence=0.999193),
comment=None,
purpose=None,
foundation_foods=[],
sentence='3 pounds pork shoulder, cut into 2-inch chunks'
)
```
Refer to the documentation [here](https://ingredient-parser.readthedocs.io/en/latest/start/index.html#optional-parameters) for the optional parameters that can be used with `parse_ingredient` .
## Model
The core of the library is a sequence labelling model that is used to label each token in the sentence with the part of the sentence it belongs to. A data set of 81,000 example sentences is used to train and evaluate the model. See the [Model Guide](https://ingredient-parser.readthedocs.io/en/latest/guide/index.html) in the documentation for mode details.
The model has the following accuracy on a test data set of 20% of the total data used:
```
Sentence-level results:
Accuracy: 94.94%
Word-level results:
Accuracy 97.90%
Precision (micro) 97.88%
Recall (micro) 97.90%
F1 score (micro) 97.88%
```
## Development
The development dependencies are in the ```requirements-dev.txt``` file. Details on the training process can be found in the [Model Guide](https://ingredient-parser.readthedocs.io/en/latest/guide/index.html) documentation.
Before committing anything, install [pre-commit](https://pre-commit.com/) and run
```
pre-commit install
```
to install the pre-commit hooks.
Please target the **develop** branch for pull requests. The main branch is used for stable releases and hotfixes only.
There is a simple web app for testing the parser with ingredient sentences and showing the parsed output. To run the web app, run the command
```bash
$ flask --app webapp run
```
This requires the development dependencies to be installed.
The dependencies for building the documentation are in the ```requirements-doc.txt``` file.
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