--- title: pipeflow: v0.4.0 on CRAN | daily.dev description: Pipeflow 0.4.0 is now on CRAN, introducing pipeline views that let developers work on a subset of pipeline steps without copying data, plus new extract/replace... canonical: https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: pipeflow: v0.4.0 on CRAN | daily.dev og:description: Pipeflow 0.4.0 is now on CRAN, introducing pipeline views that let developers work on a subset of pipeline steps without copying data, plus new extract/replace... og:url: https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex og:image: https://api.daily.dev/og/posts/jHOzfEhEx.png og:image:alt: pipeflow: v0.4.0 on CRAN og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # pipeflow: v0.4.0 on CRAN **[R-bloggers](https://daily.dev/sources/rbloggers)** · 8 min read · 1 upvotes · 0 comments ## Summary Pipeflow 0.4.0 is now on CRAN, introducing pipeline views that let developers work on a subset of pipeline steps without copying data, plus new extract/replace operators ([ and [[) for reading and editing steps data.table-style. The release also brings a functional and method-style API, output collection and grouping by tags, pipeline combination and modification utilities, split/map/reduce execution modes, nested pipelines, and self-modifying pipelines. Performance was improved by moving the dependency graph to C++ (since v0.3.0) and dropping the lgr and jsonlite dependencies, leaving only data.table and Rcpp. The post also compares pipeflow to the {targets} package, positioning pipeflow as optimized for low-latency, interactive use cases like Shiny app backends, while targets remains better suited for large, reproducible batch jobs with disk persistence and distributed execution. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What new features were added in pipeflow 0.4.0 for R? Pipeflow 0.4.0 adds pipeline views, which let you work on a subset of pipeline steps without copying the underlying data, and new data.table-style extract and replace operators ([ and [[) for reading and editing steps. It also adds grouped output collection via pip_collect(), split/map/reduce execution modes, nested pipelines, and self-modifying pipelines with restart(). _Developers tracking R package releases can follow pipeflow's evolving feature set on daily.dev._ ### How does the pipeflow R package compare to the targets package for pipelines? Targets remains the standard for heavy-duty, reproducible pipelines that persist results to disk, record provenance, and scale via distributed infrastructure like crew. Pipeflow instead targets interactive sessions, such as Shiny app backends, where a pipeline is built and modified on the fly and must respond quickly; benchmarks show pipeflow consistently faster for re-running pipelines after a parameter change. _Choosing between pipeline tools for R projects gets easier when comparisons like pipeflow versus targets surface on daily.dev._ ### What performance changes were made under the hood in pipeflow since version 0.3.0? Since version 0.3.0, pipeflow's dependency graph has been implemented in C++ for significant performance gains, and step and parameter bookkeeping was improved using data.table. In version 0.4.0, external dependencies were also reduced by dropping the lgr and jsonlite packages, leaving only data.table and Rcpp as dependencies. _Developers weighing package dependencies and performance can keep tabs on changes like this via daily.dev._ ## Similar posts on daily.dev - [logrittr: A Verbose Pipe Operator for Logging dplyr Pipelines](https://daily.dev/posts/logrittr-a-verbose-pipe-operator-for-logging-dplyr-pipelines-ev8sjqhmt) · R-bloggers · 0 upvotes · 0 comments - [Pipelined SQL in ClickHouse 26.8](https://daily.dev/posts/pipelined-sql-in-clickhouse-26-8-dvtuimznh) · ClickHouse · 2 upvotes · 0 comments - [Drag, drop, done: a visual composer for Redpanda Connect](https://daily.dev/posts/drag-drop-done-a-visual-composer-for-redpanda-connect-u31jrwdnd) · Redpanda · 13 upvotes · 1 comments - [Pipeline Flow Monitoring](https://daily.dev/posts/pipeline-flow-monitoring-rfvhlotmc) · databricks · 1 upvotes · 0 comments - [Write Pandas Like a Pro With Method Chaining Pipelines](https://daily.dev/posts/write-pandas-like-a-pro-with-method-chaining-pipelines-ok6d61mik) · Towards Data Science · 1 upvotes · 0 comments --- Tags: [#devops](https://daily.dev/tags/devops), [#r](https://daily.dev/tags/r) [View this post on daily.dev](https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"pipeflow: v0.4.0 on CRAN","url":"https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex"},"datePublished":"2026-10-03T11:54:07.566Z","dateModified":"2026-10-03T11:54:30.429Z","description":"Pipeflow 0.4.0 is now on CRAN, introducing pipeline views that let developers work on a subset of pipeline steps without copying data, plus new extract/replace...","image":"https://media.daily.dev/image/upload/s--0_ODbtD2--/f_auto/v1722860399/public/Placeholder%2008","thumbnailUrl":"https://media.daily.dev/image/upload/s--0_ODbtD2--/f_auto/v1722860399/public/Placeholder%2008","isAccessibleForFree":true,"articleSection":"R-bloggers","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"R-bloggers","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/98bcbbdf72774292a55ceda8f2277f1e","url":"https://daily.dev/sources/rbloggers"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"devops,r","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"R-bloggers","item":"https://daily.dev/sources/rbloggers"},{"@type":"ListItem","position":3,"name":"pipeflow: v0.4.0 on CRAN"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/pipeflow-v0-4-0-on-cran-jhozfehex#faq","mainEntity":[{"@type":"Question","name":"What new features were added in pipeflow 0.4.0 for R?","acceptedAnswer":{"@type":"Answer","text":"Pipeflow 0.4.0 adds pipeline views, which let you work on a subset of pipeline steps without copying the underlying data, and new data.table-style extract and replace operators ([ and [[) for reading and editing steps. 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