chattr
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
Comparison · Analytics
tensorflow vs ymlthis
A side-by-side editorial comparison of tensorflow and ymlthis — release velocity, themes, recent moves, and the top alternatives to consider.
tensorflow vs ymlthis: at a glance
What is tensorflow?
The R binding to TensorFlow now spends nearly every release on install plumbing.
The R tensorflow package is a thin binding whose release notes have, for several years, been dominated by one problem: getting a working Python TensorFlow onto the user's machine. Recent releases hand that job progressively to reticulate — 2.20.0 adds py_require_tensorflow(), which makes the long-standing install_tensorflow() call unnecessary in most cases. The remaining content is version-default bumps, GPU detection fixes, and compatibility work against NumPy 2.0 and R-devel.
What is ymlthis?
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
ymlthis built R Markdown YAML front matter programmatically — a fluent `yml_*()` interface plus RStudio add-ins, so users did not have to hand-write metadata blocks whose valid fields were scattered across output-format documentation. Version 1.0.0 declares the package retired, with only CRAN-preserving changes to follow, and states the reason plainly: Quarto now provides good YAML support.
tensorflow vs ymlthis: editorial side-by-side
tensorflow
0.0ANALYTICS
The R binding to TensorFlow now spends nearly every release on install plumbing.
◆ Current state
The R tensorflow package is a thin binding whose release notes have, for several years, been dominated by one problem: getting a working Python TensorFlow onto the user's machine. Recent releases hand that job progressively to reticulate — 2.20.0 adds py_require_tensorflow(), which makes the long-standing install_tensorflow() call unnecessary in most cases. The remaining content is version-default bumps, GPU detection fixes, and compatibility work against NumPy 2.0 and R-devel.
◆ Where it's heading
Two arcs run through these entries. The first is dependency resolution moving from imperative (call install_tensorflow(), which builds a venv and pip-installs CUDA) to declarative (declare the requirement, let reticulate resolve it). The second is the quiet handover of the modelling layer: 2.16.0 switched the suggested high-level package from keras to keras3, leaving this package as the low-level tensor and installer surface rather than the place users spend their time.
◆ Prediction
The next release will most likely track a TensorFlow version bump plus whatever reticulate's requirement-resolution API changes, and continue trimming install_tensorflow()'s responsibilities. The entries give no indication of new modelling capability landing here rather than in keras3.
ymlthis
0.0ANALYTICS
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
◆ Current state
ymlthis built R Markdown YAML front matter programmatically — a fluent `yml_*()` interface plus RStudio add-ins, so users did not have to hand-write metadata blocks whose valid fields were scattered across output-format documentation. Version 1.0.0 declares the package retired, with only CRAN-preserving changes to follow, and states the reason plainly: Quarto now provides good YAML support.
◆ Where it's heading
The retirement is the endpoint of a long drift. Between 2020 and 2022 every release was reactive — patching around a crayon update that mangled rendered YAML, tracking shiny 1.6, following roxygen2 7.0.0, fixing a typo in an add-in. No new capability has landed in six years, and the four-year gap before 1.0.0 had already answered the question the release note finally makes explicit.
◆ Prediction
Nothing further of substance is expected — the stated policy is changes only where CRAN requires them, so the next release, if any, will be a compatibility patch.
Alternatives to tensorflow and ymlthis
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either tensorflow or ymlthis.
cloudml
Six years since the last functional change, and Google renamed the service it wraps in the release before that
tidymodels
The meta-package ships almost nothing, which is exactly what a version-pinning shim should do
datapack
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
USAboundaries
Seven years dormant, then two releases dragging every census boundary from 2020 to 2024
slider
Feature-complete since 2021, and every release since has been paying CRAN's C API bill
See all tensorflow alternatives → · See all ymlthis alternatives →
Recent activity from tensorflow and ymlthis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agoymlthisymlthis retired; Quarto covers the need ⚡
- 11mo agotensorflowpy_require_tensorflow() replaces manual install_tensorflow()
- 2y agotensorflowSuggests keras3 over keras; auto-installs CUDA on Linux
- 2y agotensorflowTracks TensorFlow 2.15 and newer reticulate
- 2y agotensorflowInstalls the CUDA runtime itself; only the driver is manual
- 3y agotensorflowInstalls into a dedicated r-tensorflow environment by default
- 3y agotensorflowR doubles now convert to float64 tensors, not float32
- 4y agoymlthisTypo fixed in the miniUI add-in check
- 4y agoymlthisyml_author() accepts yml_blank(); shiny fixes
- 4y agoymlthisciteproc handling moved to newer rmarkdown functions
- 5y agoymlthisPatched a crayon update that mangled rendered YAML
- 5y agoymlthisAdjustments for shiny 1.6
Frequently asked questions
What is the difference between tensorflow and ymlthis?
They serve adjacent needs but don't currently overlap on shipped themes. tensorflow and ymlthis are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is tensorflow better than ymlthis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tensorflow and ymlthis are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to tensorflow?
Top tensorflow alternatives in Analytics are ranked by recent ship velocity. Browse the "tensorflow alternatives" section above for the current picks, or visit /alternatives/tensorflow for the full list with editorial commentary on each.
What are the best alternatives to ymlthis?
Top ymlthis alternatives in Analytics are ranked by recent ship velocity. Browse the "ymlthis alternatives" section above for the current picks, or visit /alternatives/ymlthis for the full list with editorial commentary on each.