tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
chattr vs mirai
A side-by-side editorial comparison of chattr and mirai — release velocity, themes, recent moves, and the top alternatives to consider.
chattr vs mirai: at a glance
What is chattr?
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
What is mirai?
mirai removed its dispatcher process and added memory backpressure to the queue.
The async evaluation framework releases roughly monthly and moves fast at the architecture level. In 2.7.0 the dispatcher stopped being a separate process and became a thread, after its loop had already been rewritten in C inside nanonext one release earlier. The same release added an opt-in memory budget for queued task payloads and try_mirai(), which returns NULL immediately rather than blocking when that budget is exhausted.
chattr vs mirai: editorial side-by-side
chattr
0.0ANALYTICS
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
◆ Current state
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
◆ Where it's heading
The first two releases show why that happened. Each provider brought its own error formats, token discovery and response handling, and 0.2.0 is largely a list of per-provider repairs — OpenAI error parsing, Copilot token discovery and model defaults, a new Databricks foundation model backend. Maintaining that surface scales linearly with the number of providers, and the pivot to ellmer trades it for a single dependency. The cost shows up immediately in 0.3.1, which exists solely to absorb a change in ellmer's token object.
◆ Prediction
Expect chattr's releases to now track ellmer's, as 0.3.1 already does, with the package's own work concentrating on the IDE experience rather than model connectivity. New provider support will arrive without a chattr release at all.
mirai
2.5ANALYTICS
mirai removed its dispatcher process and added memory backpressure to the queue.
◆ Current state
The async evaluation framework releases roughly monthly and moves fast at the architecture level. In 2.7.0 the dispatcher stopped being a separate process and became a thread, after its loop had already been rewritten in C inside nanonext one release earlier. The same release added an opt-in memory budget for queued task payloads and try_mirai(), which returns NULL immediately rather than blocking when that budget is exhausted.
◆ Where it's heading
Two threads of work run together: cutting overhead out of the task path — thread-based dispatcher, in-process transport for synchronous daemons, lower per-element dispatch cost in mirai_map() — and making the framework safe to embed in an event loop, where blocking the host R thread is not acceptable. Deployment reach is growing too, with http_config() launching remote daemons over HTTP APIs and auto-configuring for Posit Workbench. Each release pins a minimum nanonext version, so the two packages advance as one unit.
◆ Prediction
With backpressure in place but opt-in, the open question these notes leave is whether a default memory budget arrives; continued overhead reduction and Shiny-facing non-blocking paths are the safer bet.
Alternatives to chattr and mirai
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 chattr or mirai.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all chattr alternatives → · See all mirai alternatives →
Recent activity from chattr and mirai
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 25d agomiraiMap collection and daemon lifecycle fixes
- 2mo agomiraiAgent skill ships in-package; HTTP headers take over auth
- 3mo agomiraiDispatcher becomes a thread, and the queue gains a memory budget ⚡
- 5mo agomiraiParallel RNG seeding leaves experimental status
- 6mo agomiraiRemote daemons over HTTP, and a C dispatcher loop
- 8mo agomiraiTelemetry span timing and daemon-switch fix
- 0y agochattrAdapts to ellmer's token object change
- 1y agochattrAll model integration moves to ellmer, direct backends removed ⚡
- 2y agochattrDatabricks foundation models added; per-provider error handling fixed
- 2y agochattrFirst release: LLM chat in the RStudio console and app
Frequently asked questions
What is the difference between chattr and mirai?
They serve adjacent needs but don't currently overlap on shipped themes. mirai is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is chattr better than mirai?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mirai is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to chattr?
Top chattr alternatives in Analytics are ranked by recent ship velocity. Browse the "chattr alternatives" section above for the current picks, or visit /alternatives/chattr for the full list with editorial commentary on each.
What are the best alternatives to mirai?
Top mirai alternatives in Analytics are ranked by recent ship velocity. Browse the "mirai alternatives" section above for the current picks, or visit /alternatives/mirai for the full list with editorial commentary on each.