Best Package Managers for Spark NLP

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Compare the Top Package Managers that integrate with Spark NLP as of December 2025

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This a list of Package Managers that integrate with Spark NLP. Use the filters on the left to add additional filters for products that have integrations with Spark NLP. View the products that work with Spark NLP in the table below.

What are Package Managers for Spark NLP?

Package managers are software tools that automate the process of installing, upgrading, configuring, and removing software packages. They simplify dependency management by ensuring that required libraries and modules are downloaded and updated correctly. Many package managers connect to online repositories, allowing developers and system administrators to access large ecosystems of software quickly. By standardizing installations and updates, they reduce errors, improve consistency, and save time in both development and production environments. Package managers are widely used across programming languages, operating systems, and frameworks to streamline software distribution and maintenance. Compare and read user reviews of the best Package Managers for Spark NLP currently available using the table below. This list is updated regularly.

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    Conda

    Conda

    Conda

    Package, dependency, and environment management for any language, Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, Fortran, and more. Conda is an open-source package management system and environment management system that runs on Windows, macOS, Linux, and z/OS. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs, but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a different version of Python, you do not need to switch to a different environment manager, because conda is also an environment manager. With just a few commands, you can set up a totally separate environment to run that different version of Python, while continuing to run your usual version of Python in your normal environment.
    Starting Price: Free
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