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Modify for local pytest run in CONTRIBUTING #122

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Dec 17, 2024
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Modify for local pytest run in CONTRIBUTING #122

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0c45528
run pytest locally in CONTRIBUTING
AdrienWehrle Dec 17, 2024
2ea332e
fix a typo in README en passsant
AdrienWehrle Dec 17, 2024
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8 changes: 5 additions & 3 deletions CONTRIBUTING.md
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Expand Up @@ -65,14 +65,16 @@ pip install -e .
If your PR targets the implementation of a new feature or the
improvement of existing ones, please add at least one test per feature
(in the associated
[`tests/test_earthspy.py`](https://github.com/AdrienWehrle/earthspy/blob/main/LICENSE)
[`tests/test_earthspy.py`](https://github.com/AdrienWehrle/earthspy/blob/main/tests/test_earthspy.py)
file) and include them in your PR, using `pytest` (see existing tests
for examples).

To run the entire test suite, run pytest in the current directory:
To run the entire test suite locally, run pytest in the current
directory by passing the full path to your Sentinel Hub credential
file:

```bash
pytest
pytest --authfile=/path/to/auth.txt
```


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6 changes: 0 additions & 6 deletions README.md
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Expand Up @@ -12,12 +12,6 @@

`earthspy` is a wrapper around methods for the download of satellite data offered in the [sentinelhub-py Python package](https://github.com/sentinel-hub/sentinelhub-py). This tool makes the monitoring and study of any place on Earth simple, ready to use and easily deployable for operational purposes and automated Near-Real Time (NRT) applications.

Some useful capabilities:
- Data download in multiprocessing
- Data download at optimized resolutions with the Direct (D) download mode
- Data download at native resolutions with the Split and Merge (SM) downlodad mode
- Data storage with efficient structure and file naming

As `earthspy` is built on top of the [Sentinel Hub services](https://www.sentinel-hub.com/), it includes e.g. the data pre-processing through [custom scripts](https://docs.sentinel-hub.com/api/latest/evalscript/) allowing the user to process and download only the products needed (such as high-level indices) therefore optimizing download time and local storage.

# Table of Contents
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