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LineaPy Profile
LineaPy

@lineapy_oss

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165

Move fast from data science prototype to pipeline💡 Learn how @ https://t.co/D58h0bRxjF

Distributed, everywhere 🌎
Joined April 2022
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@lineapy_oss
LineaPy
4 years
Data scientists, meet LineaPy! Just two lines of #opensource code captures, analyzes, and transforms messy #datascience development code to extract production data pipelines in minutes. No refactoring or new tools needed.
lineapy.org
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@lineapy_oss
LineaPy
3 years
What's LineaPy’s secret sauce that lets LineaPy auto-generate Airflow/Kubeflow/Argo/Ray/DVC pipelines from spaghetti DS development code with a couple of simple APIs? Check out our latest blog post, where we take a peek behind the curtains 😉
lineapy.org
When it comes to data science development, a Jupyter Notebook is often the easiest way to go. When the time comes to convert development code into […]
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@DataTalksClub
DataTalksClub
3 years
In this Open Source Spotlight, we talked about @lineapy_oss. LineaPy helps to capture, analyze, and transform messy notebooks into data pipelines with just two lines of code. Here is a full demo on how you can use it https://t.co/aWLRR0ckgu
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@lineapy_oss
LineaPy
3 years
We are excited to see what you can do with #LineaPy, come connect with us on our community Slack https://t.co/bapv3atGxR with any questions, comments, or if you just want to share something awesome! #oss
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@lineapy_oss
LineaPy
3 years
@raydistributed Check our updated documentation ( https://t.co/0YRtSN4QhU) for examples of how to configure pipelines for each of these frameworks and how to set up and run some demos. Also, check out our demo youtube video ( https://t.co/o0DC0nZYrR) for the frameworks you are most interested in.
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@lineapy_oss
LineaPy
3 years
@raydistributed Workflows #LineaPy now supports using the new Ray Workflows as an orchestration engine! Users can now leverage the scalability of Ray to run their toughest and computationally heaviest DAG workflows.
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@lineapy_oss
LineaPy
3 years
@kubeflow Pipelines Using Kubeflow's Pipeline Python SDK, #LineaPy users can now create DAG files that can be submitted to an existing Kubeflow cluster. We are excited by the additional opportunities this will provide #Kubernetes shops already using Kubeflow.
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@lineapy_oss
LineaPy
3 years
@argoproj @DVCorg Data Pipelines DVC now supports Stage per Artifact flavor, allowing a finer granularity breakdown of the DAG into stages. This not only improves the debuggability and flexibility of the data pipeline but allows DVC users to leverage DVCs stage caching functionality.
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@lineapy_oss
LineaPy
3 years
@argoproj Workflows Through Hera, the Argo Workflows Python SDK, users can now use Lineapy to generate pipeline files that can be submitted to Argo Workflows. This gives Lineapy the ability to create and submit pipelines to one of the leading Kubernetes Workflow Engines.
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@lineapy_oss
LineaPy
3 years
#LineaPy now integrates with @argoproj , @kubeflow , and @raydistributed , @DVCorg ! With the generous help of our #OSS contributors, we now have additional integrations with multiple frameworks, including Argo, Kubeflow, and Ray, DVC.
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@FeatureformML
FeatureformML
3 years
It's Day 5 of the #12DaysOfPodcasts! 🎉 Today @lineapy_oss CEO @me_dorx shares the ideal workflow for getting data science notebooks into production 😄
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@lineapy_oss
LineaPy
3 years
🎙Podcast drop: our founder and CEO Doris Xin joins O'Reilly author Noah Gift on his podcast to talk about how LineaPy helps get #Jupyter notebooks to production and captures lineage across the #datascience lifecycle. Don't miss this one! 👇 https://t.co/bEhv8JuiCc
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@lineapy_oss
LineaPy
3 years
🤝 If you love both MLflow and LineaPy and want to leverage the best of both libraries, we break down how you can do it with minimal effort or code change. Follow us for other exciting integrations in the works. #mlflow #datascience #lineapy https://t.co/CiagjsXSqt
lineapy.org
MLflow is a great tool for managing the entire ML lifecycle. We often use MLflow for the following purposes: Compared to MLflow, which focuses on ML […]
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@lineapy_oss
LineaPy
3 years
💡 LineaPy eschews this messy process for a simple solution. ➕ Get to production in minutes, not days. Try our demo using standard iris data here:
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@lineapy_oss
LineaPy
3 years
📙 Data scientists working on Jupyter notebooks day-to-day often have non-linear workflows. They jump between cells, delete cells, edit cells, and re-execute them until a "good" table, model, or chart (an "artifact") is produced. LineaPy gets rid of the messy process...
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@lineapy_oss
LineaPy
3 years
✓ Monday fun fact: 80% of data science is engineering. The bottleneck isn't the science; it's the engineering behind getting to production.
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@lineapy_oss
LineaPy
3 years
Happy Thanksgiving to the LineaPy community! We're grateful for your support, feedback, and hope you enjoy your time with friends and family today 🦃 🥧 🍂
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@lineapy_oss
LineaPy
3 years
⚡️ Automate data engineering with LineaPy and unlock the power of your data. We're #opensource and super easy to set up. Here's how to get started👇 Step 1: Go to → https://t.co/4zMDDTB4Mx Step 2: Install the Python package Step 3: Try out one of our notebooks!
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github.com
Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code. - LineaLabs/lineapy
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@FeatureformML
FeatureformML
3 years
🤔 How do you scale machine learning across many teams? @lineapy_oss CEO @me_dorx shares her thoughts in the clip below 👇🏽 Check out her full episode on the #MLOpsWeeklyPodcast here: https://t.co/BIuFeJGXDw
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@lineapy_oss
LineaPy
3 years
📱Based on a recently published gas forecast by @seanjtaylor, our team created a FastAPI app that forecasts #gasprices and shows you whether the price will go up or down this week, so you can decide the best time to pump gas based on your region.
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