See Assets list at the bottom of this page: https://github.com/ipfs/go-ipfs/releases/tag/v0.7.0 Download the build appropriate for your machine, or just download the source tar if you're not sure.
Unzip the file that you downloaded.
tar xvfz {filename}.tar.gz
Move the binary into your path. sudo may be required for this.
mv go-ipfs/ipfs /usr/local/bin/ipfs
Initialize a ~/.ipfs directory. This is where your files and config will be saved.
ipfs init
Remove default peers for performance.
ipfs bootstrap rm --all
Add the dWeather server as a peer.
ipfs bootstrap add "/ip4/198.211.104.50/tcp/4001/p2p/QmWsAFSDajELyneR7LkMsgfaRk2ib1y3SEU7nQuXSNPsQV"
Start the IPFS daemon. You will need to have the daemon running to use some functionality of the dWeather client.
ipfs daemon
In a new window, confirm that you can pull content.
ipfs cat QmVsy2HZCi39ePJRpNqXEJvHgRMqjcyu1FLqgiFkPTMknq/USW00014704.csv.gz
Confirm that the dWeather server is a peer.
ipfs swarm peers
Install dweather_client:
pip3 install dweather_client
Get valid dataset names and associated hashes:
http_queries.get_heads()
Get the metadata for a given dataset name:
http_queries.get_metadata(http_queries.get_heads()['cpcc_temp_max-daily'])
Get a rainfall dict for a gridded dataset:
client.get_gridcell_history(41.175, -75.125, 'cpcc_temp_max-daily') # with ipfs daemon running
Get a station variable:
client.get_station_history('USW00024285', "SNOW") # with ipfs daemon running
See further examples in tests
cd dweather-python-client
python3 -m venv .
bin/pip3 install -r requirements.txt
bin/python3 -m pytest dweather_client/tests
Some dweather_client features require an ipfs daemon to work.
Some gridded dataset tests run from local pickles of the dataset for speed. To generate one of these pickles from a dataset that exists in gridded_datasets.py, simply run the below from command line whilst at the top level (dweather-python-client) of the project. The example shown assumes a dataset name of "era5_precip-hourly".
python3 dweather_client/tools/create_pickle.py era5_precip-hourly
Create an isolated Python installation and install the dependencies.
git clone https://github.com/Arbol-Project/dWeather-Python-Client.git
cd dWeather-Python-Client
python3 -m venv .
bin/pip3 install -r requirements.txt
Run the tests, if you want.
bin/python3 -m pytest -s --log-cli-level=20 dweather_client/tests
Certain dweather functions will try to save query results locally to disk for faster performance on subsequent loads. This can be overridden by passing pin=False in these function calls.
Load the ipfs UI to browse what files are stored locally. Paste the following into a web browser. http://127.0.0.1:5001/webui
Navigate to Files, then click "pins." Content can be unpinned via the UI.
If you just want to remove everything, delete ~/.ipfs and rerun the installation and configuration from ipfs init.
rm -rf ~/.ipfs
See tests directory for example usage. Documented examples of usage should appear in a docs repository or in product-dev-notebook.