![]() ![]() Parallel extraction can approximately double the speed of extracting. In addition to increasing conda’s solving speeds, we have also greatly increased the speed of downloading and extracting conda packages. Install conda Packages Faster With Parallelized Downloads More about the plugin architecture below. This was made possible by a new plugin architecture. TL DR: The conda-libmamba-solver is now available as a fully supported solver option. If you are unsure whether you should use the new solver, you may refer to “ Should I use conda-libmamba-solver?,” where we have detailed the differences between the classic and libmamba solvers. So, instead of doing that, we decided to develop a plugin architecture proof-of-concept with Quansight to empower users with the choice of an alternate solver. Conda is used by over 30 million users around the world, and it didn’t have the underlying infrastructure to support experimental tools.ĭirectly updating the default solver itself without causing disruptions to existing workflows would require a high dose of optimistic hope. Implementing a new solver for conda while prioritizing maximized backwards compatibility was a non-trivial challenge. The exact speed improvements of the new solver will vary based on the environment and packages users are installing, but you can expect to see improvements in the 50-80% range across use cases. In that performance test, the classic solver downloaded the two large libraries in 91 seconds, whereas libmamba, the libsolv-based solver, took only 15 seconds-an ~80% speed improvement. In our experimental release announcement, we compared the performance of the solvers by installing popular Python packages SciPy and TensorFlow on the same Windows machine. The conda-libmamba-solver greatly increases the speed with which conda solves an environment when installing packages. You may also refer to this comprehensive Getting Started guide. To install and set the new solver, run the following commands:Ĭonda install -n base conda-libmamba-solver Speed improvement has been one of conda’s most highly requested updates, and after almost a year of joint development work, we are incredibly excited to share that the conda-libmamba-solver has now joined the default solver club. Back in March of this year, the conda team introduced a new experimental solver, conda-libmamba-solver, as part of our collaborative effort with Quansight to make conda faster. ![]()
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