NDFF Client api

This project packages a module which you can use to interact with the NDFF

Learn more <https://ndff.nl>_.

Release notes: <https://ndff.atlassian.net/wiki/spaces/KT/pages/3591831556/NDFF+connector+releases>_

Data

A lot of test data is provided in this project. All data AND settings examples for that data are in the tests directory.

There is also a QGIS project file available (on request) which has most of the data loaded as layers and can be used for testing. This project file should be put in the tests/qgis directory because all data paths are relative to that.

QuickStart

Use ...

Linux::

best to use a Virtual Environment, (for R in de R directory?):

create a virtual env

python -m venv venv

activate venv

source venv/bin/activate

'pip install ndff' in venv R only? install dependencies from pypi (NOT testpypi):

• psycopg2
• click
• requests
• shapely

dependencies are handled, for test version

pip install -i https://testpypi.python.org/pypi ndff

or

pip install --upgrade -i https://testpypi.python.org/pypi ndff pip install .

make sure you have the right configurations:

cd demo mkdir -p settings_user/ndff_settings cp global_settings/data_source.csv settings_user/ndff_settings cp global_settings/ndff_api.csv settings_user/ndff_settings

you now have one global settings directory (containing some convenient mappings)

AND

a settings_user directory, in which you have to update the following files with YOUR information:

- a datasource.csv (pointing to a dataset and type, the copy is OK: it points to the demo csv)
- a ndff_api.csv (with all the right credentials to connect to the NDFF api in your domain; YOU HAVE TO UPDATE THIS ONE)

to let the client script pick up the two configuration directories, export the directories to your environment

from the demo project make sure you can call the ndff script

ndff --help

to see help of the subcommands, for example

ndff sample --help

or

ndff

the last one should show a warning that you are missing a (actually 2) environment variable(s)

set these

export NDFF_GLOBAL_SETTINGS_DIR=./global_settings export NDFF_USER_SETTINGS_DIR=./settings_user

NOTE: use -v or -vv or -vvv to see (debug) information

show 1 sample from the demo csv (mapped according to the demo field_mappings.csv)

ndff -v sample

or 10 records

ndff sample -n 10

validate the dataset (NOTE: as this is a valid dataset, without -vv it shows NOTHING !!!)

ndff -vv validate

sent ONE record to ndff:

ndff -vv sent -n 1

this either returns a 201 (success) OR a 409 (already there)

if you want to do this again / overwrite, use the -o (overwrite) flag

ndff -vv sent -n 1 -o

OR just sent the full dataset, overwriting the earlier versions

ndff -vv sent -o

JSON mapping and API ...........

When you have set the above mentioned NDFF_GLOBAL_SETTINGS_DIR and NDFF_USER_SETTINGS_DIR values you've set all the values of the datasource, the API credentials and the field mappings.

So when you use for example the command::

ndff -vv sent -n 1

It has all the information to create the mapping and directly sends it to the API.

CLI ...

https://davidfischer.name/2017/01/python-command-line-apps/

https://codeburst.io/building-beautiful-command-line-interfaces-with-python-26c7e1bb54df

R

The demo folder contains a sample R-scrip for inspiration.