HERE Data SDK for Python - Analytics

The Data SDK for Python - Analytics enables exploration, analysis and visualization of HERE platform data in your own environment using Jupyter, Python and Spark. Use this SDK to experiment and design data processes and AI before going to production in HERE platform.

Caution

Due to the lack of Python support in production pipelines, Python logic must be re-implemented in Spark/Flink for production.

We're delivering our Data SDK for Python using Conda, a package management service that makes it easy to find, access, store and share public notebooks, environments, and conda and PyPI packages. Conda is a popular tool among Python data workers because it makes it easy for them to stay current with updates made to their various environments and packages. It also allows users to switch between environments without affecting the delicate compatibility of each environment's dependencies.

Prerequisites

Note

After installing conda for the first time, please restart your terminal before executing any conda command. This is to avoid a common issue where conda command is not recognized the first time.

To begin, sign into the HERE platform. This will renew your browser token so you can access the HERE platform repository. Next, download the installation script.

Environment Validation

To ensure your credentials are properly placed, use the following command to ensure the environment is ready for the SDK.

python sdk_setup.py -v

Installation

Note (Only For Windows)

  • Please start the terminal as an administrator to avoid errors related to insufficient rights or privileges.

To install the SDK, use the following commands:

This command will install the latest version of the SDK in the default environment.

python sdk_setup.py -i

To install a specific version of the SDK in the default environment, use the following command below.

python sdk_setup.py -i <sdk_version>

Note

  • The default environment name is olp-sdk-for-python-1.8-env, if you want to change it, specify the name in the command

To install the latest version of the SDK in specified environment:

 python sdk_setup.py -i -n <yourenvname>

To install the specific version of the SDK in specified environment:

python sdk_setup.py -i <sdk_version> -n <yourenvname>
  • If you have errors related with python-geohash dependency when creating the conda environment, please follow these steps.

Activate the conda environment:

conda activate olp-sdk-for-python-1.8-env

Go to home directory and proceed to start Jupyter:

For Linux/MacOS:

cd ~/
jupyter notebook --NotebookApp.iopub_data_rate_limit=1000000000 --ip=0.0.0.0

For Windows:

cd %USERPROFILE%
jupyter notebook --NotebookApp.iopub_data_rate_limit=1000000000

Note

  • The "go to home directory" command is optional: cd ~/. It is for you to be able to access all the files located in your home folder when Jupyter starts.
  • You can stop the Jupyter server by typing CTRL + C in the same console you started it.

JupyterLab

If you work with the JupyterLab "desktop" instead of the "classic" Jupyter notebooks, use this command to start Jupyter:

For Linux/MacOS:

cd ~/
jupyter lab --NotebookApp.iopub_data_rate_limit=1000000000 --ip=0.0.0.0

For Windows:

cd %USERPROFILE%
jupyter lab --NotebookApp.iopub_data_rate_limit=1000000000

With JupyterLab you will benefit from installing a few additional JupyterLab extensions. These will either render files in some frequently used formats (e.g. HTML or GeoJSON) or some computed output (like Leaflet map cells) directly inside JupyterLab:

jupyter labextension install @mflevine/jupyterlab_html
jupyter labextension install @jupyterlab/geojson-extension
jupyter labextension install jupyter-leaflet
jupyter labextension install @jupyter-widgets/jupyterlab-manager

You might also be able to install these inside JupyterLab using its interactive Extension Manager.

API Reference

Explore the Data SDK for Python API reference by opening the html docs located at the links below:

For Linux/MacOS: $HOME/olp-sdk-for-python-1.8/documentation/Data SDK for Python API Reference.html.

For Windows: %USERPROFILE%\olp-sdk-for-python-1.8\documentation\Data SDK for Python API Reference.html.

Note

We recommend opening this documentation directly in Chrome and Firefox browsers instead of Jupyter or Internet Explorer.

Tutorial Notebooks

The tutorial notebooks included with the SDK are located in the folder:

For Linux/MacOS: $HOME/olp-sdk-for-python-1.8/tutorial-notebooks/python.

For Windows: %USERPROFILE%\olp-sdk-for-python-1.8\tutorial-notebooks\python.

We recommend reading the Getting Started notebook to get an overview of all of the tutorial notebooks:

For Linux/MacOS: $HOME/olp-sdk-for-python-1.8/tutorial-notebooks/GettingStarted.ipynb

For Windows: %USERPROFILE%\olp-sdk-for-python-1.8\tutorial-notebooks\GettingStarted.ipynb


Help us improve our setup experience, please fill out this short 1-minute survey after you are finished setting up the SDK. Complete survey


results matching ""

    No results matching ""