# MCH-Extract: MeteoSwiss OpenData Extraction Tool
> **⚠️ DISCLAIMER**: This tool is **NOT official** and is **NOT affiliated** with MeteoSwiss. It is an independent project that provides a convenient access to publicly available MeteoSwiss measurement data through the Open Government Data initiative.
A simple Python tool for downloading weather data from Switzerland's automatic ground-based weather stations. Designed for scientists and researchers who need easy access to publicly available [MeteoSwiss data](https://opendatadocs.meteoswiss.ch/) without dealing with the complexities of the FSDI REST API.
## What Does This Tool Do?
- **Download weather data** from Swiss weather stations with simple commands
- **Get data in different time intervals**: daily, hourly, monthly, or 10-minutes measurements
- **Save data** in Excel-friendly CSV or efficient Parquet formats
- **Access data programmatically** in Python for analysis using [Polars](https://docs.pola.rs/) or Pandas
- **Handle data validation** automatically - just specify what you want
## Installation
Install using pip (requires Python 3.10 or newer):
```bash
pip install mch-extract
```
Verify the tool is installed and working:
```bash
mch-extract --help
```
## Quick Examples
### Command Line (Terminal)
Get daily temperature and precipitation data for two stations:
```bash
mch-extract --from 2024-06-01 --to 2024-06-07 \
--stations PAY VIT \
--variables temperature precipitation \
--daily \
--output my_weather_data.csv
```
Get hourly temperature data with detailed output:
```bash
mch-extract --from 2024-06-01 \
--stations PAY \
--variables temperature \
--hourly \
--output hourly_temp.csv \
--verbose
```
### In Python Scripts
```python
from datetime import date
from mchextract import get_data
# Download weather data as a Polars DataFrame
data = get_data(
stations=['PAY', 'VIT'], # Payerne and Villars-Tiercelin stations
variables=['temperature', 'precipitation'],
start_date=date(2024, 6, 1),
end_date=date(2024, 6, 7),
timescale='daily'
)
# If you prefer working with Pandas, you can convert the Polars DataFrame:
# data = data.to_pandas()
# (requires `pandas` package to be installed separately)
print(f"Downloaded {len(data)} rows of data")
print(data.head())
# Save to file
data.write_csv("my_data.csv")
```
## How to Use
### Command Line Options
**Required:**
- `--from DATE`: Start date (YYYY-MM-DD format, e.g., 2024-06-01)
- `--stations CODES`: Weather station codes (e.g., PAY VIT ROM)
- **Time resolution**: Choose one of `--monthly`, `--daily`, `--hourly`, or `--10min`
**Optional:**
- `--to DATE`: End date (defaults to most recent valid date)
- `--variables VARS`: What to measure (e.g., temperature precipitation). If not set, will return all available parameters for the stations
- `--dwh PARAMS`: Additional MeteoSwiss DWH parameters shortnames to include. See below on how to find them.
- `--output FILE`: Where to save data. Supported format are: `.csv`, `.json`, `.parquet`. If not set, will print CSV data to STDOUT
- `--verbose`: Show detailed progress information
- `--no-cache`: Disable caching (useful for testing or debugging)
### Available Weather Variables
As a convenience, some "easy to use" variables are provided. These will be automatically converted to DWH parameters for you.
- `temperature`: Air temperature
- `precipitation`: Rainfall and snow
- `pressure`: Atmospheric pressure
- `humidity`: Relative humidity
- `sunshine`: Sunshine duration
- `evaporation`: Evaporation measurements
### Time Intervals
- `--monthly`: Monthly averages
- `--daily`: One measurement per day
- `--hourly`: One measurement per hour
- `--10min`: Real-time measurements every 10 minutes
### Station Codes
Weather stations use 3-letter codes:
- `PAY`: Payerne
- `VIT`: Villars-Tiercelin
- `KLO`: Zurich/Kloten
- `GVE`: Geneva
- And many more...
If you use an invalid code, the tool will show you all available stations.
### References
STAC browser: https://data.geo.admin.ch/browser/index.html#/collections/ch.meteoschweiz.ogd-smn?.language=en
For the list of available stations and parameters, consult the following CSV files:
- Stations list
- regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_stations.csv
- precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_stations.csv
- Parameters list:
- regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_parameters.csv
- precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_parameters.csv
- Inventory (which station has which parameters):
- regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_datainventory.csv
- precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_datainventory.csv
## More Examples
### Command Line Examples
```bash
# Download precipitation data for multiple stations
mch-extract --from 2024-01-01 --to 2024-01-31 --stations PAY VIT ROM \
--variables precipitation --hourly --output rain_data.csv
# Get temperature and humidity for Zurich area
mch-extract --from 2024-12-01 --to 2024-12-31 --stations KLO \
--variables temperature humidity --daily --output zurich_weather.csv
# Monthly climate summary for Geneva
mch-extract --from 2024-01-01 --to 2025-01-01 --stations GVE \
--variables temperature precipitation pressure \
--monthly --output geneva_climate.csv
```
### Python Examples
```python
from datetime import date
from mchextract import get_data
# Get recent weather for analysis
data = get_data(
stations=['PAY', 'VIT'],
variables=['temperature', 'precipitation'],
start_date=date(2024, 6, 1),
end_date=date(2024, 6, 7),
timescale='daily'
)
# Basic data exploration
print(f"Data shape: {data.shape}")
print(f"Average temperature: {data['temperature'].mean():.1f}°C")
print(f"Total precipitation: {data['precipitation'].sum():.1f}mm")
# Save for Excel
data.write_csv("weather_analysis.csv")
```
## About the Data
### Swiss Weather Network
This tool accesses data from Switzerland's official weather monitoring network:
- **~160 complete weather stations**: Measure temperature, precipitation, wind, sunshine, humidity, radiation, and pressure
- **~100 precipitation stations**: Focus on rainfall and snow measurements
### Data Types Available
- **10-minutes data**: Real-time measurements (updated every 20 minutes)
- **Hourly data**: Hourly summaries
- **Daily data**: Daily summaries (most common for research)
- **Monthly data**: Monthly climate summaries
### Data Coverage
- **Historical**: From when each station started until end of last year
- **Recent**: From January 1st of current year until yesterday
- **Real-time**: Current data (only for hourly and 10-minutes intervals)
### Data Quality
- All data comes pre-processed from MeteoSwiss
- Quality control and validation already applied
- Follows international meteorological standards
- Some stations have data going back to 1981 or earlier
## Troubleshooting
### Common Problems
**"Invalid station code"**
- Check your 3-letter station codes (e.g., PAY, KLO, GVE)
- The tool will show available stations if you use an invalid code
**"No data available for date range"**
- Make sure your dates are in YYYY-MM-DD format
- Check that the date range is reasonable (not too far in the future)
- Some stations may not have all variables available
**"Network error" or "Download failed"**
- Check your internet connection
- MeteoSwiss servers might be temporarily unavailable
**Need more help?**
- Use `--verbose` to see detailed information about what's happening
- Check that your dates and station codes are correct
### Getting Detailed Output
Add `--verbose` to any command to see what the tool is doing:
```bash
mch-extract --from 2024-01-01 --stations PAY --variables temperature \
--daily --output debug.csv --verbose
```
## Important Notes
### Attribution
If using this data in publications or research, please consult MeteoSwiss guidelines on how to cite them. Data is provided under [Creative Commons Licence CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). See [Terms of use](https://opendatadocs.meteoswiss.ch/general/terms-of-use).
### Disclaimer
- This tool is **NOT official** and **NOT affiliated** with MeteoSwiss
- It provides convenient access to publicly available MeteoSwiss OpenData
- For climate analyses, consider MeteoSwiss' [official climate data products](https://opendatadocs.meteoswiss.ch/c-climate-data)
### Data Usage
- All data comes from MeteoSwiss OpenData and can be used freely
- Please respect MeteoSwiss servers - don't make excessive requests
- For large-scale or commercial usage, consider contacting MeteoSwiss directly
- This tool is not meant to be integrated into any automated solutions
## Development and Contributing
This project is open source. For developers interested in:
- Setting up a development environment
- Running tests
- Contributing code
- Building from source
Please see [DEVELOPMENT.md](DEVELOPMENT.md) for detailed technical documentation.
## Learn More
- [MeteoSwiss OpenData Documentation](https://opendatadocs.meteoswiss.ch/)
- [Weather Station Network Information](https://opendatadocs.meteoswiss.ch/a-data-groundbased/a1-automatic-weather-stations)
- [Interactive Station Map](https://www.meteoswiss.admin.ch/services-and-publications/applications/measurement-values-and-measuring-networks.html#param=messnetz-automatisch&lang=en)
- [MeteoSwiss Open Data Explorer](https://www.meteoswiss.admin.ch/services-and-publications/applications/ext/download-data-without-coding-skills.html)
#### Keywords
MeteoSwiss, MeteoSchweiz, MétéoSuisse, data extraction, OpenData, wrapper, Python API, Python package
Raw data
{
"_id": null,
"home_page": null,
"name": "mch-extract",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "data, meteorology, meteoswiss, ogd, switzerland, weather",
"author": null,
"author_email": "Martin Spoto <martin.spoto98@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/76/93/bc9c3684a65626ac17af1c2d36f3b3acbf25a5ad69201ce1313b27e14482/mch_extract-0.2.1.tar.gz",
"platform": null,
"description": "# MCH-Extract: MeteoSwiss OpenData Extraction Tool\n\n> **\u26a0\ufe0f DISCLAIMER**: This tool is **NOT official** and is **NOT affiliated** with MeteoSwiss. It is an independent project that provides a convenient access to publicly available MeteoSwiss measurement data through the Open Government Data initiative.\n\nA simple Python tool for downloading weather data from Switzerland's automatic ground-based weather stations. Designed for scientists and researchers who need easy access to publicly available [MeteoSwiss data](https://opendatadocs.meteoswiss.ch/) without dealing with the complexities of the FSDI REST API.\n\n## What Does This Tool Do?\n\n- **Download weather data** from Swiss weather stations with simple commands\n- **Get data in different time intervals**: daily, hourly, monthly, or 10-minutes measurements\n- **Save data** in Excel-friendly CSV or efficient Parquet formats\n- **Access data programmatically** in Python for analysis using [Polars](https://docs.pola.rs/) or Pandas\n- **Handle data validation** automatically - just specify what you want\n\n## Installation\n\nInstall using pip (requires Python 3.10 or newer):\n\n```bash\npip install mch-extract\n```\n\nVerify the tool is installed and working:\n\n```bash\nmch-extract --help\n```\n\n## Quick Examples\n\n### Command Line (Terminal)\n\nGet daily temperature and precipitation data for two stations:\n\n```bash\nmch-extract --from 2024-06-01 --to 2024-06-07 \\\n --stations PAY VIT \\\n --variables temperature precipitation \\\n --daily \\\n --output my_weather_data.csv\n```\n\nGet hourly temperature data with detailed output:\n\n```bash\nmch-extract --from 2024-06-01 \\\n --stations PAY \\\n --variables temperature \\\n --hourly \\\n --output hourly_temp.csv \\\n --verbose\n```\n\n### In Python Scripts\n\n```python\nfrom datetime import date\nfrom mchextract import get_data\n\n# Download weather data as a Polars DataFrame\ndata = get_data(\n stations=['PAY', 'VIT'], # Payerne and Villars-Tiercelin stations\n variables=['temperature', 'precipitation'],\n start_date=date(2024, 6, 1),\n end_date=date(2024, 6, 7),\n timescale='daily'\n)\n\n# If you prefer working with Pandas, you can convert the Polars DataFrame:\n# data = data.to_pandas()\n# (requires `pandas` package to be installed separately)\n\nprint(f\"Downloaded {len(data)} rows of data\")\nprint(data.head())\n\n# Save to file\ndata.write_csv(\"my_data.csv\")\n```\n\n## How to Use\n\n### Command Line Options\n\n**Required:**\n\n- `--from DATE`: Start date (YYYY-MM-DD format, e.g., 2024-06-01)\n- `--stations CODES`: Weather station codes (e.g., PAY VIT ROM)\n- **Time resolution**: Choose one of `--monthly`, `--daily`, `--hourly`, or `--10min`\n\n**Optional:**\n\n- `--to DATE`: End date (defaults to most recent valid date)\n- `--variables VARS`: What to measure (e.g., temperature precipitation). If not set, will return all available parameters for the stations\n- `--dwh PARAMS`: Additional MeteoSwiss DWH parameters shortnames to include. See below on how to find them.\n- `--output FILE`: Where to save data. Supported format are: `.csv`, `.json`, `.parquet`. If not set, will print CSV data to STDOUT\n- `--verbose`: Show detailed progress information\n- `--no-cache`: Disable caching (useful for testing or debugging)\n\n### Available Weather Variables\n\nAs a convenience, some \"easy to use\" variables are provided. These will be automatically converted to DWH parameters for you.\n\n- `temperature`: Air temperature\n- `precipitation`: Rainfall and snow\n- `pressure`: Atmospheric pressure\n- `humidity`: Relative humidity\n- `sunshine`: Sunshine duration\n- `evaporation`: Evaporation measurements\n\n### Time Intervals\n\n- `--monthly`: Monthly averages\n- `--daily`: One measurement per day\n- `--hourly`: One measurement per hour\n- `--10min`: Real-time measurements every 10 minutes\n\n### Station Codes\n\nWeather stations use 3-letter codes:\n\n- `PAY`: Payerne\n- `VIT`: Villars-Tiercelin\n- `KLO`: Zurich/Kloten\n- `GVE`: Geneva\n- And many more...\n\nIf you use an invalid code, the tool will show you all available stations.\n\n### References\n\nSTAC browser: https://data.geo.admin.ch/browser/index.html#/collections/ch.meteoschweiz.ogd-smn?.language=en\n\nFor the list of available stations and parameters, consult the following CSV files:\n\n- Stations list\n - regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_stations.csv\n - precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_stations.csv\n- Parameters list:\n - regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_parameters.csv\n - precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_parameters.csv\n- Inventory (which station has which parameters):\n - regular: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn/ogd-smn_meta_datainventory.csv\n - precip: https://data.geo.admin.ch/ch.meteoschweiz.ogd-smn-precip/ogd-smn-precip_meta_datainventory.csv\n\n## More Examples\n\n### Command Line Examples\n\n```bash\n# Download precipitation data for multiple stations\nmch-extract --from 2024-01-01 --to 2024-01-31 --stations PAY VIT ROM \\\n --variables precipitation --hourly --output rain_data.csv\n\n# Get temperature and humidity for Zurich area\nmch-extract --from 2024-12-01 --to 2024-12-31 --stations KLO \\\n --variables temperature humidity --daily --output zurich_weather.csv\n\n# Monthly climate summary for Geneva\nmch-extract --from 2024-01-01 --to 2025-01-01 --stations GVE \\\n --variables temperature precipitation pressure \\\n --monthly --output geneva_climate.csv\n```\n\n### Python Examples\n\n```python\nfrom datetime import date\nfrom mchextract import get_data\n\n# Get recent weather for analysis\ndata = get_data(\n stations=['PAY', 'VIT'],\n variables=['temperature', 'precipitation'],\n start_date=date(2024, 6, 1),\n end_date=date(2024, 6, 7),\n timescale='daily'\n)\n\n# Basic data exploration\nprint(f\"Data shape: {data.shape}\")\nprint(f\"Average temperature: {data['temperature'].mean():.1f}\u00b0C\")\nprint(f\"Total precipitation: {data['precipitation'].sum():.1f}mm\")\n\n# Save for Excel\ndata.write_csv(\"weather_analysis.csv\")\n```\n\n## About the Data\n\n### Swiss Weather Network\n\nThis tool accesses data from Switzerland's official weather monitoring network:\n\n- **~160 complete weather stations**: Measure temperature, precipitation, wind, sunshine, humidity, radiation, and pressure\n- **~100 precipitation stations**: Focus on rainfall and snow measurements\n\n### Data Types Available\n\n- **10-minutes data**: Real-time measurements (updated every 20 minutes)\n- **Hourly data**: Hourly summaries\n- **Daily data**: Daily summaries (most common for research)\n- **Monthly data**: Monthly climate summaries\n\n### Data Coverage\n\n- **Historical**: From when each station started until end of last year\n- **Recent**: From January 1st of current year until yesterday\n- **Real-time**: Current data (only for hourly and 10-minutes intervals)\n\n### Data Quality\n\n- All data comes pre-processed from MeteoSwiss\n- Quality control and validation already applied\n- Follows international meteorological standards\n- Some stations have data going back to 1981 or earlier\n\n## Troubleshooting\n\n### Common Problems\n\n**\"Invalid station code\"**\n\n- Check your 3-letter station codes (e.g., PAY, KLO, GVE)\n- The tool will show available stations if you use an invalid code\n\n**\"No data available for date range\"**\n\n- Make sure your dates are in YYYY-MM-DD format\n- Check that the date range is reasonable (not too far in the future)\n- Some stations may not have all variables available\n\n**\"Network error\" or \"Download failed\"**\n\n- Check your internet connection\n- MeteoSwiss servers might be temporarily unavailable\n\n**Need more help?**\n\n- Use `--verbose` to see detailed information about what's happening\n- Check that your dates and station codes are correct\n\n### Getting Detailed Output\n\nAdd `--verbose` to any command to see what the tool is doing:\n\n```bash\nmch-extract --from 2024-01-01 --stations PAY --variables temperature \\\n --daily --output debug.csv --verbose\n```\n\n## Important Notes\n\n### Attribution\n\nIf using this data in publications or research, please consult MeteoSwiss guidelines on how to cite them. Data is provided under [Creative Commons Licence CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). See [Terms of use](https://opendatadocs.meteoswiss.ch/general/terms-of-use).\n\n### Disclaimer\n\n- This tool is **NOT official** and **NOT affiliated** with MeteoSwiss\n- It provides convenient access to publicly available MeteoSwiss OpenData\n- For climate analyses, consider MeteoSwiss' [official climate data products](https://opendatadocs.meteoswiss.ch/c-climate-data)\n\n### Data Usage\n\n- All data comes from MeteoSwiss OpenData and can be used freely\n- Please respect MeteoSwiss servers - don't make excessive requests\n- For large-scale or commercial usage, consider contacting MeteoSwiss directly\n- This tool is not meant to be integrated into any automated solutions\n\n## Development and Contributing\n\nThis project is open source. For developers interested in:\n\n- Setting up a development environment\n- Running tests\n- Contributing code\n- Building from source\n\nPlease see [DEVELOPMENT.md](DEVELOPMENT.md) for detailed technical documentation.\n\n## Learn More\n\n- [MeteoSwiss OpenData Documentation](https://opendatadocs.meteoswiss.ch/)\n- [Weather Station Network Information](https://opendatadocs.meteoswiss.ch/a-data-groundbased/a1-automatic-weather-stations)\n- [Interactive Station Map](https://www.meteoswiss.admin.ch/services-and-publications/applications/measurement-values-and-measuring-networks.html#param=messnetz-automatisch&lang=en)\n- [MeteoSwiss Open Data Explorer](https://www.meteoswiss.admin.ch/services-and-publications/applications/ext/download-data-without-coding-skills.html)\n\n#### Keywords\nMeteoSwiss, MeteoSchweiz, M\u00e9t\u00e9oSuisse, data extraction, OpenData, wrapper, Python API, Python package",
"bugtrack_url": null,
"license": null,
"summary": "A Python package for extracting meteorological data from MeteoSwiss OpenData API",
"version": "0.2.1",
"project_urls": {
"Documentation": "https://github.com/martintops/mch-extract#readme",
"Homepage": "https://github.com/martintops/mch-extract",
"Issues": "https://github.com/martintops/mch-extract/issues",
"Repository": "https://github.com/martintops/mch-extract"
},
"split_keywords": [
"data",
" meteorology",
" meteoswiss",
" ogd",
" switzerland",
" weather"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "cec02e9debc014c25e2df4db9988722cec28531b6651e1a90b06e8e9194024b0",
"md5": "9421740df5bfe88a55b2b3b7f75c1f5b",
"sha256": "8da87b027936fd74f7a3050f453632cffb66a9d96d2636ef90db7864fe24ad41"
},
"downloads": -1,
"filename": "mch_extract-0.2.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "9421740df5bfe88a55b2b3b7f75c1f5b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 25113,
"upload_time": "2025-07-16T20:17:00",
"upload_time_iso_8601": "2025-07-16T20:17:00.615307Z",
"url": "https://files.pythonhosted.org/packages/ce/c0/2e9debc014c25e2df4db9988722cec28531b6651e1a90b06e8e9194024b0/mch_extract-0.2.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "7693bc9c3684a65626ac17af1c2d36f3b3acbf25a5ad69201ce1313b27e14482",
"md5": "289e463898a7fc9a76de35897067236a",
"sha256": "66d1323ab310b6aff2609ebfc05a59418b23190bd4f30ff69a2624b8b7a35361"
},
"downloads": -1,
"filename": "mch_extract-0.2.1.tar.gz",
"has_sig": false,
"md5_digest": "289e463898a7fc9a76de35897067236a",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 57945,
"upload_time": "2025-07-16T20:17:01",
"upload_time_iso_8601": "2025-07-16T20:17:01.739944Z",
"url": "https://files.pythonhosted.org/packages/76/93/bc9c3684a65626ac17af1c2d36f3b3acbf25a5ad69201ce1313b27e14482/mch_extract-0.2.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-07-16 20:17:01",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "martintops",
"github_project": "mch-extract#readme",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "mch-extract"
}
JSON
