https://twitter.com/hamilton_os/status/1623701290839842817 (3) takes advantage of the new plugin framework -- just install geopandas and you can use it as you would pandas. Twitter

https://twitter.com/hamilton_os/status/1623701292215599109 As always, thanks to our wonderful community for so many wonderful ideas and contributions. See full update with credit here: https://t.co/8TIEaPjl96. Twitter

https://twitter.com/hamilton_os/status/1623701289657073666 (2) enables you two express powerful parameterizations -- you can generate multiple dataframes in one function and extract columns from them. Let's say you're generating test/training sets -- you can now do that all in a function! Docs for more details: https://t.co/GV6WV5ybHU Twitter

https://twitter.com/hamilton_os/status/1623701293780070400 And finally, if you want to help out or get started with Hamilton, reach out! Happy to point you in the right direction -- just join our slack community https://t.co/HjwqlUGKe0. Twitter

https://twitter.com/KishManani/status/1624434166531076098 Streamline your dataframe transformations with the @hamilton_os's Hamilton package! By combining smaller, testable functions, you can easily build a DAG of operations on your dataframe. https://t.co/ibAgvWs391 Twitter

https://twitter.com/hamilton_os/status/1624474149187129347 Thanks for the shout out @KishManani ! Twitter Streamline your dataframe transformations with the @hamilton_os's Hamilton package! By combining smaller, testable… https://twitter.com/i/web/status/1624434166531076098 Twitter

https://twitter.com/hamilton_os/status/1625634399638396929 Happy Tuesday! 📢 New user provided example - thanks Thierry Jean! TL;DR: * it shows an example Hamilton Transformer for use within a @scikit_learn pipeline! * ✂️📋 to use it * would ❤️ feedback! https://t.co/DQEb6F4kD2 #python #MachineLearning #featureengineering Twitter

https://twitter.com/hamilton_os/status/1627753580655685632 🚨 Happy Monday: big release today 1.17.0🚨 TL;DR: (1) +

target_

parameter for some decorators to help "target" what they apply to. (2) +

subdag

decorator to enable first class chaining. (3) + dataframe flattening. Upgrade: pip install sf-hamilton==1.17.0 #OpenSource 1/6 Twitter

https://twitter.com/hamilton_os/status/1627753582283083776 (1) Using target_ : E.g. use it to "target"

check_output

@ extract_columns(*cols_to_expose) @ check_output(schema=a_schema, target_="source_data") def source_data(path: str) -> pd.DataFrame: _df = https://t.co/jI2qY1lTky_csv(path) # other logic return _df 2/6 Twitter

https://twitter.com/hamilton_os/status/1627753583868547072 (2) Instead of using Hamilton within itself: def source_2_data(path: str) -> pd.DataFrame: from hamilton import driver dr = driver.Driver({"loader": "source_2"}, transforms) df = dr.execute(["combined_data"], inputs={"source_2_path": path}) return df 3/6 Twitter

https://twitter.com/hamilton_os/status/1627753585378471936 (2 cont.) You can now do: @ subdag( transforms, inputs={"path": source("path")}, config={"loader": "source_2"}, ) def source_2_data(combined_data: pd.DataFrame) -> pd.DataFrame: return combined_data To have 💯% visibility into it! 4/6 Twitter

https://twitter.com/hamilton_os/status/1627753586846490624 (3) Requesting dataframes in the output to create a single dataframe: * Previous behavior did not allow you to do this. * Can now directly request the function that outputs the dataframe and it'll be flattened. * Use this when you can't be verbose! 5/6 Twitter

https://twitter.com/hamilton_os/status/1627753588402569216 Thanks to all the users that raised issues and asked questions - that helped shaped these API improvements! Join Slack if you have questions - https://t.co/HjwqlUGKe0 Or create issues/discussions on github - https://t.co/IUmQKGuV69 #pydata #python #opensource 6/6 Twitter

https://twitter.com/stefkrawczyk/status/1627812079884443649 @Ubunta @databricks @SnowflakeDB @getdbt @DataPolars @duckdb @IbisData Take @hamilton_os for a spin. It'll help structure your code to stitch together all of work that is required. Twitter

https://twitter.com/stefkrawczyk/status/1627812137740677121 @Ubunta @databricks @SnowflakeDB @getdbt @DataPolars @duckdb @IbisData @hamilton_os more than happy to do a personal walkthrough if useful ;) Twitter

https://twitter.com/stefkrawczyk/status/1628837145577422851 @mitchpatin At @DagWorks we're enabling Data Science teams to build, and own ML ETLs in a sustainable and maintainable way, built on @hamilton_os. Say bye to 🍝code, $$$ maintenance, knowledge silos, and instead spend more time building features and models. Sign up for early access! Twitter

https://twitter.com/stefkrawczyk/status/1629365320942231552 @bernhardsson I consider @hamilton_os to be on that spectrum 😎. Twitter

https://twitter.com/elijahbenizzy/status/1630276088919375873 Hamilton retweeted: Two exciting pieces of #hamilton news: 1. We have forked Hamilton under the DAGWorks org: please give us a ⭐ so w… https://twitter.com/i/web/status/1630276088919375873 Twitter

https://twitter.com/hamilton_os/status/1630279274690392065 🚨 Big news today 🚨 (1) The Hamilton repository has moved to https://github.com/DAGWorks-Inc/hamilton please ⭐ it! We're trying to rebuild the stars we lost with the move. (2) The docs have moved to https://t.co/0eFZJl9FZB (3) Never tried Hamilton? 👀 at https://t.co/mwmdtkS2kS 😉 Twitter

https://twitter.com/hamilton_os/status/1630279276183588865 Thanks to @SarahHaskins, @CharityKith for helping with the docs, & @elilambnz for building https://github.com/elilambnz/react-py that we leveraged for https://t.co/zh6Ij6kIYy. Twitter

https://twitter.com/DagWorks/status/1630282092914569218 📣Yep, it's official📣: @hamilton_os is now under https://github.com/dagworks-inc/hamilton We're excited to be able to invest into the project and work on our goal of helping #datateams own #machinelearning #ETL without the maintenance burden that comes with them. 🤔->👀 https://t.co/1L6TS163Bm Twitter 🚨 Big news today 🚨 (1) The Hamilton repository has moved to https://github.com/DAGWorks-Inc/hamilton please ⭐ it! We're trying to… https://twitter.com/i/web/status/1630279274690392065 Twitter

https://twitter.com/hamilton_os/status/1632813442834010113 🎆 Happy Monday, excited to announce our 1.19.0 release. What’s new: 1) @ApacheSpark (#PySpark) UDF Map support! 2) New example and docs on feature engineering with Hamilton. pip install sf-hamilton==1.19.0 to get it. More info follows: 1/5 #opensource #Python #DataScience Twitter

https://twitter.com/hamilton_os/status/1632813444432003074 1) Native #PySpark UDF support: Write any chain of “map” operations as Hamilton funcs & execute them as UDFs on a pyspark DF. We think this is 🆒: (a) removes UDF boilerplate, (b) makes it easier to reuse & forces naming alignment See https://t.co/fwFVWktVTo for details. 2/5 Twitter

https://twitter.com/hamilton_os/status/1632813445811933184 1*) Native #PySpark UDF support caveats: * Current support is for primitives & pandas series * it could have some rough edges, so it’s in the experimental sub-package; which is another way to say, #contributors/#ideas/#issues welcome! 3/5 Twitter

https://twitter.com/hamilton_os/status/1632813447342886912 (2) We give 2 ideas on how you might leverage Hamilton to run the same #featureengineering code for offline batch & online web contexts. The examples don’t cover all possibilities - but we’re pretty sure Hamilton will cover you! So let us know your 🤔https://t.co/nreoQCWkF0 4/5 Twitter

https://twitter.com/hamilton_os/status/1632813448794112002 That’s it for now. * Thanks for all the fresh ⭐❤️‍🔥 - we’re just about at 200 ⭐, trying to get back all the way to 893 -- please ⭐ us - https://t.co/EytwlJYaKH * Otherwise do you have questions/issues/need help? Join our slack https://t.co/HjwqlUGKe0 we'll help you out! Twitter

https://twitter.com/hamilton_os/status/1632830640793206784 Excited to be called out as a 💎! Thanks Avi Chawla! 35 Hidden Python Libraries That Are Absolute Gems https://open.substack.com/pub/avichawla/p/35-gem-py-libs?r=17gs0j&utm_campaign=post&utm_medium=web Twitter

https://twitter.com/stefkrawczyk/status/1632825350668562435 Hamilton retweeted: Thanks @ycombinator ! Excited to be part of the program and excited to share more details about what we're building… https://twitter.com/i/web/status/1632825350668562435 Twitter Welcome to YC, @elijahbenizzy, @stefkrawczyk, and @DagWorks! DAGWorks helps data science teams avoid machine learn… https://twitter.com/i/web/status/1632818328359292928 Twitter

https://twitter.com/elijahbenizzy/status/1633510588419817474 Hamilton retweeted: @ergestx Hamilton is aiming to be something like that. While its more focused on the ML side its super general purp… https://twitter.com/i/web/status/1633510588419817474 Twitter

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