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toadharvard authored and chernishev committed Jun 26, 2024
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## Table of Contents

- [Main Features](#main-features)
- [Usage Examples](#usage-examples)
- [Installation](#installation)
- [Usage Examples](#usage-examples)
- [Contacts and Q&A](#contacts-and-qa)

# Main Features
Expand Down Expand Up @@ -45,13 +45,30 @@ The currently supported data patterns are:

For more information about the supported patterns check the main [repo](https://github.com/Desbordante/desbordante-core).

## Installation

**Requrements**:
* Python 3.11+
* pipx
* [`desbordante` package](https://pypi.org/project/desbordante/) requirements

### PyPI
Run the following command:
```sh
pipx install desbordante-cli
```
### Git
```sh
pipx install git+https://github.com/desbordante/desbordante-cli
```

## Usage examples
Example datasets can be found at main [repo](https://github.com/Desbordante/desbordante-core)

Usage examples:
1) Discover all exact functional dependencies in a table stored in a comma-separated file with a header row. In this example the default FD discovery algorithm (HyFD) is used.

```sh
python3 cli.py --task=fd --table=../examples/datasets/university_fd.csv , True
desbordante --task=fd --table=../examples/datasets/university_fd.csv , True
```

```text
Expand All @@ -67,7 +84,7 @@ python3 cli.py --task=fd --table=../examples/datasets/university_fd.csv , True
2) Discover all approximate functional dependencies with error less than or equal to 0.1 in a table represented by a .csv file that uses a comma as the separator and has a header row. In this example the default AFD discovery algorithm (Pyro) is used.

```sh
python3 cli.py --task=afd --table=../examples/datasets/inventory_afd.csv , True --error=0.1
desbordante --task=afd --table=../examples/datasets/inventory_afd.csv , True --error=0.1
```

```text
Expand All @@ -79,28 +96,18 @@ python3 cli.py --task=afd --table=../examples/datasets/inventory_afd.csv , True
3) Check whether metric functional dependency “Title -> Duration” with radius 5 (using the Euclidean metric) holds in a table represented by a .csv file that uses a comma as the separator and has a header row. In this example the default MFD validation algorithm (BRUTE) is used.

```sh
python3 cli.py --task=mfd_verification --table=../examples/datasets/theatres_mfd.csv , True --lhs_indices=0 --rhs_indices=2 --metric=euclidean --parameter=5
desbordante --task=mfd_verification --table=../examples/datasets/theatres_mfd.csv , True --lhs_indices=0 --rhs_indices=2 --metric=euclidean --parameter=5
```

```text
True
```

For more information check the --help option:

```sh
desbordante --help
```

## Installation

The source code is currently hosted on GitHub at https://github.com/Desbordante/desbordante-console. In order for this to run, first you have to have install the latest version of the main Desbordante [package](https://pypi.org/project/desbordante/).
# Contacts and Q&A

**NOTE**: Only Python 3.11+ is supported for CLI

Run the following commands:

```sh
pip install -r cli/requirements.txt
python3 cli/cli.py --help
```
If you have any questions regarding the tool you can create an [issue](https://github.com/Desbordante/desbordante-cli/issues) at GitHub.

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