https://github.com/ssenart/PyGazpar

Python library to download gas consumption from a Grdf account
https://github.com/ssenart/PyGazpar

consumption gas gazpar grdf meter python

Last synced: about 1 month ago
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Python library to download gas consumption from a Grdf account

• Host: GitHub
• URL: https://github.com/ssenart/PyGazpar
• Owner: ssenart
• License: mit
• Created: 2019-08-13T12:42:11.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-10-09T19:50:27.000Z (2 months ago)
• Last Synced: 2024-11-17T00:38:56.477Z (about 1 month ago)
• Topics: consumption, gas, gazpar, grdf, meter, python
• Language: Python
• Size: 4.23 MB
• Stars: 30
• Watchers: 7
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.md

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README

        
# PyGazpar

## $\text{\color{green}{!!! This library is working again. CAPTCHA has been removed !!!}}$

PyGazpar is a Python library for getting natural gas consumption from GrDF French provider.

Their natural gas meter is called Gazpar. It is wireless and transmit the gas consumption once per day.

All consumption data is available on the client account at GrDF Web Site (https://monespace.grdf.fr).

PyGazpar automatically goes through the Web Site and download the consumption data, and make it available in a Python structure.

## Installation

### Requirements

PyGazpar does not require Selenium and corresponding geckodriver to work.

With the new GrDF web site, it is possible to load the consumption data far easily than before.

### Create your virtual environment

```bash

$ cd /path/to/my_project_folder/

$ python -m venv .venv

```

### PyGazpar installation

Activate your virtual environment.

```bash

source .venv/bin/activate

```

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install PyGazpar.

```bash

pip install pygazpar

```

You can also download the source code and install it manually.

```bash

cd /path/to/pygazpar/

python setup.py install

```

## Usage

#### Command line:

1. Standard usage (using Json GrDF API).

```bash

$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' --datasource 'json'

```

2. Alternate usage (using Excel GrDF document).

```bash

$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' -t 'temporary directory where to store Excel file (ex: /tmp)' --datasource 'excel'

```

3. Test usage (using local static data files, do not connect to GrDF site).

```bash

$ pygazpar -u 'your login' -p 'your password' -c 'your PCE identifier' --datasource 'test'

```

#### Library:

1. Standard usage (using Json GrDF API).

```python

import pygazpar

client = pygazpar.Client(pygazpar.JsonWebDataSource(

    username='your login',

    password='your password')

)

data = client.loadSince(pceIdentifier='your PCE identifier',

                        lastNDays=60,

                        frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY])

```

See [samples/jsonSample.py](samples/jsonSample.py) file for the full example.

2. Alternate usage (using Excel GrDF document).

```python

import pygazpar

client = pygazpar.Client(pygazpar.ExcelWebDataSource(

    username='your login',

    password='your password')

)

data = client.loadSince(pceIdentifier='your PCE identifier',

                        lastNDays=60,

                        frequencies=[pygazpar.Frequency.DAILY, pygazpar.Frequency.MONTHLY])

```

See [samples/excelSample.py](samples/jsonSample.py) file for the full example.

3. Test usage (using local static data files, do not connect to GrDF site).

```python

import pygazpar

client = pygazpar.Client(pygazpar.TestDataSource())

data = client.loadSince(pceIdentifier='your PCE identifier',

                        lastNDays=10,

                        frequencies=[pygazpar.Frequency.DAILY, Frequency.MONTHLY])

```

See [samples/testSample.py](samples/jsonSample.py) file for the full example.

#### Output:

```json

data =>

{

  "daily": [

    {

      "time_period": "13/10/2022",

      "start_index_m3": 15724,

      "end_index_m3": 15725,

      "volume_m3": 2,

      "energy_kwh": 17,

      "converter_factor_kwh/m3": 11.16,

      "temperature_degC": null,

      "type": "Mesur\u00e9",

      "timestamp": "2022-12-13T23:58:35.606763"

    },

    ...

    {

      "time_period": "11/12/2022",

      "start_index_m3": 16081,

      "end_index_m3": 16098,

      "volume_m3": 18,

      "energy_kwh": 201,

      "converter_factor_kwh/m3": 11.27,

      "temperature_degC": -1.47,

      "type": "Mesur\u00e9",

      "timestamp": "2022-12-13T23:58:35.606763"

    }

  ],

  "monthly": [

    {

      "time_period": "Novembre 2022",

      "start_index_m3": 15750,

      "end_index_m3": 15950,

      "volume_m3": 204,

      "energy_kwh": 2227,

      "timestamp": "2022-12-13T23:58:35.606763"

    },

    {

      "time_period": "D\u00e9cembre 2022",

      "start_index_m3": 15950,

      "end_index_m3": 16098,

      "volume_m3": 148,

      "energy_kwh": 1664,

      "timestamp": "2022-12-13T23:58:35.606763"

    }

  ]

}

```

## Limitation

PyGazpar relies on how GrDF Web Site is built.

Any change in the Web site may break this library.

We expect in close Future that GrDF makes available an open API from which we can get safely their data.

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://choosealicense.com/licenses/mit/)

## Project status

PyGazpar has been initiated for integration with [Home Assistant](https://www.home-assistant.io/).

Corresponding Home Assistant integration custom component is available [here](https://github.com/ssenart/home-assistant-gazpar).