3 years and 1.0 pre release

content/blog/2020-05-04-dvc-3-years-and-1-0-release.md

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+---
+title: DVC 3 years anniversary and 1.0 pre-release
+date: 2020-05-04
+description: |
+  Today, we’ve got three big things to announce: 🎉 3rd-year anniversary of DVC,
+  🚀 DVC 1.0 pre-release is ready and ⭐ 5000 GitHub starts.
+descriptionLong: |
+  Today, we’ve got three big things to announce.
+    - 🎉 3rd-year anniversary of DVC
+    - 🚀 DVC 1.0 pre-release is ready
+    - ⭐ DVC has reached 5K GitHub starts (coincidently on the same day)
+picture: static/uploads/images/2020-05-04/5k_stars.png
+pictureComment:
+author: ../authors/dmitry_petrov.md
+commentsUrl: https://discuss.dvc.org/t/dvc-3-years-and-1-0-release/
+tags:
+  - birthday
+  - users
+  - MLOps
+  - CI/CD
+---
+
+## 3 years anniversary!
+
+3 years ago on **May 4th, 2017** the first DVC blog post was published
+[Data Version Control beta release: iterative machine learning](https://blog.dataversioncontrol.com/data-version-control-beta-release-iterative-machine-learning-a7faf7c8be67).
+It was the first DVC tutorial and now we make the redirect to the new tutorial
+page to not to confuse users.
+
+[The first DVC discussion on Reddit](https://www.reddit.com/r/Python/comments/698ian/dvc_data_scientists_collaboration_and_iterative/)
+A few days later it was
+[republished on other sources](https://www.kdnuggets.com/2017/05/data-version-control-iterative-machine-learning.html)
+
+Today, DVC gets recognized at professional conferences: people spot our logo,
+and sometimes even our faces, and want to chat. There's much more content about
+DVC coming from bloggers than from inside our organization. We're seeing more
+and more job postings that list DVC as a requirement, and we're showing up in
+[data science textbooks](https://www.amazon.com/Learn-Python-Building-Science-Applications/dp/1789535360).
+When we find a new place DVC is mentioned, we celebrate in our Slack - we've
+come a long way!
+
+The data science and ML space is fast-paced and vibrant, and we're proud that
+DVC is making an impact on discussions about best practices for healthy,
+sustainable ML. Every week, we chat with companies and research groups using DVC
+to make their teams more productive. We're proud to be part of the growing MLOps
+movement: so far, a majority of CI/CD for ML projects are implemented with DVC
+under the hood.
+
+I can confidently say that DVC wouldn't have been possible without a lot of help
+from our community. Thank you to everyone who has supported us:
+
+**DVC core team.** The core team of the project takes the majority of the
+development activities, constantly brings new ideas, documents the product and
+always on the first line of user's support. Many users knows that great user
+support if one of the "killing features" of DVC. Today the core team consists of
+6 brave engineers.
+
+**DVC contributors.** As of today, the DVC code base has
+[126 individual contributors](https://github.com/iterative/dvc/graphs/contributors).
+Many of these folks put hours into their PRs. We're grateful for their tenacity
+and generosity.
+
+**Documentation contributors.** Another
+[124 people contributed](https://github.com/iterative/dvc.org/graphs/contributors)
+to the DVC documentation and website https://dvc.org/doc. Every time a new
+person tries out DVC, they benefit from the hard work that's gone into our docs.
+
+**Active community members.** Active DVC users help our team understand and
+better anticipate their needs and identify priorities for development. They
+share bright ideas for new features, locate and investigate bugs in code, and
+welcome and support new users.
+
+**People who give DVC a shot.** Today, there are thousands of data scientists,
+ML engineers, and developers using DVC on a regular basis. The number of users
+is growing every week. Our [Discord channel](http://dvc.org/chat) has almost two
+thousand users. Hundreds more connect with us through email and Twitter. To
+everyone willing to try out DVC, thank you for the opportunity.
+
+## DVC 1.0. is the result of 3 years of learning
+
+All these contributions, big and small, have a collective impact on DVC's
+development. I'm happy (and a bit nervous) to announce that a pre-release of a
+brand new DVC 1.0 is ready for public beta testing.
+
+The new DVC is inspired by discussions and contributions from our community -
+both fresh ideas and bug reports 😅.
+
+Here are some of the features we’re excited to be rolling out soon:
+
+[**Run-cache (a.k.a. build-cache)**](https://github.com/iterative/dvc/issues/1234)
+(the issue was created 1.5 years ago). DVC 1.0 has a "long memory" of DVC
+commands runs. This means it can identify if a `dvc repro` has already been run
+and save compute time by returning the cached result - even if you didn't Git
+commit that past run. We added the run-cache with CI/CD systems and other MLOps
+automation tools in mind. No more auto-commits needed after `dvc repro` in the
+CI/CD system side.
+
+[\*\*Multi-stage DVC files.](https://github.com/iterative/dvc/issues/1871)
+(created a year ago). We redesigned the DVC-metafile format to make saved
+pipelines more interpretable and editable. Pipeline stages are now saved in a
+single metafile, with all stages stored together instead of in separate files.
+We removed checksums from the pipeline metafile, which improves its
+human-readability.
+
+[**Plots.**](https://github.com/iterative/dvc/issues/3409) Countless users asked
+us when we'd support metrics visualizations. Now it's here: DVC 1.0 introduces a
+metrics file visualization command, `dvc metrics diff`. DVC plots are powered by
+the [Vega-Lite](https://vega.github.io/vega-lite/) graphic library. This
+function is designed not only for showing visualizations based on the current
+state of your project, but it can also combine multiple plots from your Git
+history in a single chart so you can compare results across commits. Users can
+visualize how, for example, their model accuracy in the latest commit differs
+from another commit (or even multiple commits).
+
+```
+$ dvc plot diff -d logs.csv HEAD HEAD^ d1e4d848 baseline-march
+file:///Users/dmitry/src/plot/logs.html
+$ open logs.html
+```
+
+![](/static/uploads/images/2020-05-04/dvc-plot.png)
+
+```
+$ dvc plot diff -d logs.csv HEAD HEAD^ d1e4d848 baseline-march \
+        -x loss --template scatter
+file:///Users/dmitry/src/plot/logs.html
+$ open logs.html
+```
+
+![](/static/uploads/images/2020-05-04/dvc-plot-scatter.png)
+
+**Data transfer optimizations.** We've done substantial work on optimizing data
+management commands, such as `dvc pull \ push \ status -c \ gc -c`. Now, based
+on the amount of data, DVC can choose an optimal data remote traversing
+strategy. We've introduced mini-indexes to help DVC instantly check data
+directories instead of iterating over millions of files. This also speeds up
+file adding\removing to large directories. More optimizations are included in
+the release based on performance bottlenecks we profiled.
+
+[**Hyperparameter tracking.**(https://github.com/iterative/dvc/issues/3393) This
+feature was actually released in the last DVC 0.93 version (see
+[params docs](https://dvc.org/doc/command-reference/params). However, it is an
+important step to support configuration files and ML experiments in a more
+holistic way.
+
+I hope our the most active users will find time to check the DVC pre release
+version and provide their feeback. The installation instruction is
+[on our website](https://dvc.org/doc/install/pre-release).
+
+## 5000 GitHub stars
+
+Activity on our GitHub page has grown organically since the DVC repo went public
+on May 4th, 2017. Coincidently, today, in the 3rd year anniversary we have
+reached 5000 starts:
+
+![](/static/uploads/images/2020-05-04/5k_github.png)
+
+## Thank you!
+
+Thank you again for all DVC contributions, community members, and users. Every
+piece of your help is highly appreciated and will bring huge benefits to the
+entire ecosystem of data and ML projects.