Installation

Let’s start with the installation of Sparksee graph database. Sparksee only needs to be downloaded and unpacked. Depending on which language you prefer, a few settings or considerations may need to be taken into account too.

By downloading Sparksee you should have received a free personal evaluation license. Learn more about it in the last section of this chapter.

Download

Sparksee is available for several programming languages, so the first thing you should do is download the right package for your development platform.

All the packages can be downloaded here.

Available platforms:

• Java: This is the package for all new Sparksee Java projects.
• Microsoft .NET: Sparksee is natively available for .NET developers.
• C++: A C++ interface is also available. Sparksee core is C++, so we punch it another level to the API.
• Python: Sparksee is available for Python 3 developers.
• Objective-C An Objective-C api is provided for iOS and MacOS developers. The C++ interface can still be used in Objective-C projects.

Java developers can also get Sparksee through Apache Maven instead of manually downloading the packages. More information in Sparksee maven project.

Unpacking

Once you have downloaded Sparksee and unpacked it, the content of most packages should look like this:

• doc: This is the directory that contains Sparksee API reference documentation in html or another specific format for each platform.
• lib: A directory with Sparksee libraries. It may have subdirectories when different files are required regarding each operating system.
• ReleaseNotes.txt: This is a text file with basic information on the latest release changes.
• LICENSE.txt: Contains Sparksee licensing information.

According to the programming language particularities, some packages may include additional contents.

Unpack the downloaded Sparksee package and it’s ready to be used. No further installation is required, with the exception of Objective-C on MacOS, where an installer is provided to easily copy the framework to the right standard directory.

However, some additional steps can be taken to make Sparksee usage easier for your platform.

Java

All the libraries required to develop a java application with Sparksee are contained in a jar file located at the lib directory (sparkseejava.jar).

If you are not using Maven, you may want to add the path to this file into the CLASSPATH environment variable. However, to avoid any misunderstandings, in this document we will explicitly use the file to compile the examples.

.NET

The .NET package contains two subdirectories in the lib directory (windows32 and windows64) for 32 or 64 bit systems. In each one the main library included is sparkseenet.dll. This is the library that you will need to include in your .NET projects.

All the other available libraries in the package are native dlls that sparkseenet.dll must be able to find at run time. Although it is not required, you may want to copy all these libraries to your system folder.

C++

The C++ lib folder contains native libraries for each available platform (Windows 32/64 bits, Linux 32/64 bits, MacOS 64 bits,…).

In Linux and MacOS, you may want to add the path to the correct subdirectory to your LD_LIBRARY_PATH (linux) or DYLD_LIBRARY_PATH(MacOS) environment variables.

In Windows you can copy the libraries to the system folders or just be sure to always include them in your projects.

The rest of files included in this package, like the ones in the includes directory, will be needed at compilation time. See Chapter 4.

For iOS you have to uncompress the “.dmg” file to get the Sparksee.framework directory. This directory contains the include files, the static library and the documentation. More information on how to use it can be found on Chapter 4. Please consider using the Objective-C version of Sparksee instead.

Python

Sparksee Python installation is now easier than ever, since we provide a wheel file for each specific platform and Python version (for example, sparksee-6.1.0-cp314-cp314-manylinux_2_39_x86_64.whl).

Just pick the wheel file that matches your platform and Python version, and install it with pip:

pip install the_sparksee_file.whl

This will take care of installing both the Python module and the native libraries it depends on, so no additional configuration is required.

You can verify that the module was installed correctly with the following command:

python -c "import sparksee; sparksee.Sparksee(sparksee.SparkseeConfig()); print('Sparksee module OK')"

If it prints Sparksee module OK without errors, the Python module and its native library dependency are correctly installed.

Objective-C

For Objective-C, Sparksee is distributed as a zip file containing a single Sparksee.xcframework, instead of the usual lib and doc directories. This xcframework bundles the binaries for all supported MacOS and iOS builds (device and simulator), so the same package works for both platforms. The documentation is also included, directly under the framework’s Documentation subdirectory.

To use it, unzip the package and add Sparksee.xcframework to your Xcode project (drag it into the project navigator, or add it under Frameworks, Libraries, and Embedded Content in your target settings). Xcode will automatically select the right binary slice for the platform and architecture you are building for, so no separate installer or manual library placement is required.

License

Every Sparksee download comes with a mail containing a limited personal evaluation license, that must be configured using the provided client identifier and license identifier. The personal evaluation license allows the construction of graphs with up to 1M objects, which is more than enough to construct the example explained in this guide.

If you have commercial interest or need to deal with larger databases, check Sparksee’s website license section for licenses quotation on the latest release of Sparksee.

If you hold a license identifiers, later in this document you will learn how to use your license for a project.