Going from data science development to production is full of friction. Data engineering is a manual and time-consuming process. Data teams spend countless hours managing infrastructure and repeating tasks, which reduces the team’s ability to deliver actionable insights in real-time.
LineaPy creates a frictionless path for taking data science workflows from development to production with just two lines of code.
Cleaning Messy Notebooks
Data science is an experimental process that typically involves using interactive tools such as notebooks. Notebooks can include messy code, out of order cell execution, and iterative refinements, until a good result is achieved. LineaPy relieves scientists from the manual effort of cleaning notebooks and automates the process of generating clean code for any given result.Learn more
Revisiting Previous Work
Data science is often a team effort where one person’s work uses results from another’s. Revisiting earlier development work that led to a given result can be challenging. For example, the developer might not remember how they arrived at these results or may no longer be in the organization, rendering the results unreliable and even unusable. LineaPy tracks results automatically and records the lineage associated with their creation and modification to support downstream artifacts that use them.Learn more.
Fully developed notebooks are sometimes used like pipelines running periodically to process the latest data and update dashboards. Running a notebook is a manual, brittle process, prone to errors, and requires the knowledge of orchestration tools that might be outside data scientists domain knowledge. LineaPy automatically generates production pipelines, greatly reducing the time to yield results.Learn More
The Magic of LineaPy
LineaPy is backed by a decade of research and industry expertise tackling hyperscale data challenges.
Manage the data lifecycle
LineaPy captures lineage to enable a comprehensive view of dependencies in your environment. Automatically generated Linea Graphs retrace lineage at any point in history, making it easy to update artifacts and increase trust.
Deliver production-grade code
LineaPy applies compiler research to analyze development code and automatically refactors it to be production-grade, enabling reproducibility for future artifacts.