Smart Citizen Data
Welcome to SmartCitizen Data. This is a data analysis framework for working with sensor data in different ways:
- Interacting with several sensors APIs
- Clean data, export and calculate metrics
- Model sensor data and calibrate sensors
- Generate data visualisations - matplotlib,
plotlyor uplot - Generate analysis reports in html or pdf and upload them to Zenodo
Installation
You can check it out in the Python 3.* (tested between 3.9 and 3.11).
You can just run:
pip install scdata
Plots (device.ts_plot(), maps, panels...) need the plotting libraries, an optional extra. Without them scdata loads and processes data, and plotting raises an error that says how to install them:
pip install "scdata[plot]"
Parquet needs the storage extra: the backups (local or S3: device.load_from_storage(), device.backup_to_storage()) and exports in parquet (device.export(..., file_format='parquet')):
pip install "scdata[storage]"
Examples (scripts and notebooks) are in examples.
Work on the source code
Simply clone the repository with:
git clone https://github.com/fablabbcn/smartcitizen-data.git
cd smartcitizen-data
Install scdata package with requirements:
python setup.py install
Or if you want to edit:
pip install --editable ".[dev]"
Tokens and config
Blueprints, calibrations and sensor names are read from BASE_POSTPROCESSING_URL, the same variable as smartcitizen-connector. By default it is this repository on GitHub; set it to https://flows.smartcitizen.me/api/v1/ to use the metadata served by Smart Citizen Flows.
Settings can be changed in ~/.config/scdata/config.yaml. The file only keeps what differs from the defaults (the defaults of new versions apply after upgrading), for instance:
data:
reload_metadata: false
paths:
export: /home/me/exports
The data folder is ~/.cache/scdata by default ($XDG_CACHE_HOME/scdata if it is set), with the raw, processed, export... folders inside. Each folder of paths is changed on its own, and only to a folder that exists: changing data does not move the others. To move them all, set XDG_CACHE_HOME.
Also, .env files will be picked from ~/.cache/scdata. An env.example is provided. If you want to upload data to Zenodo, you will need to fill set an environment variable called ZENODO_TOKEN in your environment. The .env file is not mandatory for scdata to work. It only serves for authentication if you want to POST or GET data without throttling. You can still do GET requests but they will be throttled if not authenticated/authorized by the platform. See user roles for more info.
Using with jupyter lab (optional)
It can also be used with jupyter lab or jupyter. For this install juypterlab.
Contribute
Issues and PR more than welcome!
Funding
This work has received funding from the European Union's Horizon 2020 research and innovation program under the grant agreement No. 689954
1 maintainer
Metadata
1 maintainer
Release files for scdata 1.6.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scdata-1.6.4.tar.gz | 339.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scdata-1.6.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 705.6 kB
Release files / scdata-1.6.4.tar.gz
| Download URL | scdata-1.6.4.tar.gz |
|---|---|
| Size | 339.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Release files / scdata-1.6.4-py3-none-any.whl
| Download URL | scdata-1.6.4-py3-none-any.whl |
|---|---|
| Size | 366.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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