tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
charlatan vs chattr
A side-by-side editorial comparison of charlatan and chattr — release velocity, themes, recent moves, and the top alternatives to consider.
charlatan vs chattr: at a glance
What is charlatan?
R's fake-data generator rebuilt its provider hierarchy so contributors can add one locale without touching the rest.
charlatan generates realistic fake data — names, addresses, phone numbers, jobs, internet artefacts — across many locales, following the same model as faker in Python and Perl. The 0.6.1 release reworked the provider class hierarchy so locale-specific providers inherit from a parent, and 0.6.2 since has been a documentation rebuild that happened to surface a duplicate Norwegian phone number pattern. Activity is sparse and bursty.
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.
charlatan vs chattr: editorial side-by-side
charlatan
0.0ANALYTICS
R's fake-data generator rebuilt its provider hierarchy so contributors can add one locale without touching the rest.
◆ Current state
charlatan generates realistic fake data — names, addresses, phone numbers, jobs, internet artefacts — across many locales, following the same model as faker in Python and Perl. The 0.6.1 release reworked the provider class hierarchy so locale-specific providers inherit from a parent, and 0.6.2 since has been a documentation rebuild that happened to surface a duplicate Norwegian phone number pattern. Activity is sparse and bursty.
◆ Where it's heading
The package's value scales with locale coverage, and its releases track that: early versions added data-type providers, middle versions added locales one contributor at a time, and 0.6.1 attacked the bottleneck by restructuring the class hierarchy so a locale can override a single function. Development has effectively been handed to contributors, with maintainer releases reduced to docs rebuilds and CRAN compliance.
◆ Prediction
Expect the next substantive release to be an accumulation of contributed locales and providers arriving through the new parent-provider structure, rather than maintainer-driven feature work.
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.
Alternatives to charlatan and chattr
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 charlatan or chattr.
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 charlatan alternatives → · See all chattr alternatives →
Recent activity from charlatan and chattr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agocharlatanDocs rebuild surfaces a duplicate Norwegian phone pattern
- 0y agochattrAdapts to ellmer's token object change
- 1y agochattrAll model integration moves to ellmer, direct backends removed ⚡
- 1y agocharlatanProvider classes restructured so locales can override single functions ⚡
- 2y agochattrDatabricks foundation models added; per-provider error handling fixed
- 2y agochattrFirst release: LLM chat in the RStudio console and app
- 6y agocharlatanNew locales and providers; allowed_locales() added
- 7y agocharlatanLocale naming standardised; French and Danish data corrected
- 8y agocharlatancharlatan v0.2.2
- 8y agocharlatanSix new providers broaden charlatan beyond names and addresses
Frequently asked questions
What is the difference between charlatan and chattr?
They serve adjacent needs but don't currently overlap on shipped themes. charlatan and chattr 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 charlatan better than chattr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. charlatan and chattr 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 charlatan?
Top charlatan alternatives in Analytics are ranked by recent ship velocity. Browse the "charlatan alternatives" section above for the current picks, or visit /alternatives/charlatan for the full list with editorial commentary on each.
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.