update from CRAN submission

Author: jasdumas

.DS_Store

@@ -9,3 +9,4 @@
 ^pkgdown$
 ^\.github$
 ^CODE_OF_CONDUCT\.md$
+^CRAN-SUBMISSION$

.Rbuildignore

@@ -0,0 +1,3 @@
+Version: 0.0.1
+Date: 2025-11-05 15:49:44 UTC
+SHA: 63261b92bdb71d892b8aab684cfa73e4d8b146cd

CRAN-SUBMISSION

@@ -1,14 +1,14 @@
 Package: shinyfa
-Title: Analyze the File Contents of Shiny Directories
-Version: 0.0.0.9000
+Title: Analyze the File Contents of 'shiny' Directories
+Version: 0.0.1
 Authors@R: person("Jasmine", "Daly",  email = "jasmine.dumas@gmail.com", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0001-8006-2428"))
 Description: Provides tools for analyzing and understanding the file contents of 
-    large Shiny application directories. The package extracts key information about 
-    render functions, reactive functions, and their inputs from Shiny app files, 
+    large 'shiny' application directories. The package extracts key information about 
+    render functions, reactive functions, and their inputs from app files, 
     organizing them into structured data frames for easy reference. This streamlines 
     the onboarding process for new contributors and helps identify areas for 
-    optimization in complex Shiny codebases with multiple files and sourcing chains.
+    optimization in complex 'shiny' codebases with multiple files and sourcing chains.
 URL: https://github.com/dalyanalytics/shinyfa, https://dalyanalytics.github.io/shinyfa/
 BugReports: https://github.com/dalyanalytics/shinyfa/issues
 License: MIT + file LICENSE

DESCRIPTION

@@ -1,4 +1,5 @@
-# shinyfa (development version)
+# shinyfa 0.0.1 (development version)
 
 * 2025-02-17: Initial development on GitHub.
-* 2025-06-14: Prepping for CRAN submission
+* 2025-06-14: Prepping for CRAN submission.
+* 2025-10-31: submitting to CRAN after community testing.

NEWS.md

@@ -1,10 +1,10 @@
-# shinyfa 
+# shinyfa
 
 <img src="https://media.githubusercontent.com/media/dalyanalytics/shinyfa/refs/heads/main/man/figures/shinyfa-logo.png" align="right" alt="shinyfa logo" width="200" />
 
 
 <!-- badges: start -->
-[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
+[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
 [![R-CMD-check](https://github.com/dalyanalytics/shinyfa/actions/workflows/pkgdown.yaml/badge.svg)](https://github.com/dalyanalytics/shinyfa/actions/workflows/pkgdown.yaml)
 <!-- badges: end -->
 
@@ -13,45 +13,109 @@ The `{shinyfa}` package is designed to help Shiny developers analyze and underst
 
 Large Shiny applications often contain numerous files that define both dynamic UI and server components, sometimes linked together in complex sourcing chains (though this is less common in Shiny apps structured with modules). For new contributors—such as consultants joining a project—it can take considerable time to onboard, navigate the codebase, and identify areas for optimization.  
 
-This in-progress package aims to streamline that process by extracting key information from a Shiny app directory. It identifies specific render functions, reactive functions, and their inputs, organizing them into a structured `data.frame` for easy reference.  
+This package aims to streamline that process by extracting key information from a Shiny app directory. It identifies specific render functions, reactive functions, and their inputs, organizing them into a structured `data.frame` for easy reference.  
 
 The *fa* in *shinyfa* stands for *file analysis*.
 
-## Installation
+## 🎯 Why use shinyfa?
 
-You can install the development version of {shinyfa} from [GitHub](https://github.com/) with:
+- **📊 Audit reactive dependencies**: Quickly understand which inputs affect which outputs across your entire app
+- **🔍 Identify unused code**: Find reactive expressions and render functions that may no longer be used
+- **🗺️ Map data flow**: Visualize how data flows through complex Shiny applications with multiple modules
+- **📚 Generate documentation**: Create instant reference guides for new team members joining the project
+- **⚡ Optimize performance**: Identify potential bottlenecks by understanding reactive chains
+
+## 📦 Installation
+
+Install from CRAN:
+
+``` r
+install.packages("shinyfa")
+```
+
+Or install the development version from GitHub:
 
 ``` r
-# install.packages("pak")
+# Install from GitHub
+devtools::install_github("dalyanalytics/shinyfa")
+
+# Or using pak
 pak::pak("dalyanalytics/shinyfa")
 ```
 
-## Example
+## 🚀 Usage
+
+### Basic Example
 
-This is a basic example which shows you how to solve a common problem for looping through a directory that contains server files:
+Analyze a typical Shiny app structure:
 
 ``` r
 library(shinyfa)
-library(dplyr)  
+library(dplyr)
 
-file_path_df <- list.files("SHINY-SERVER-DIRECTORY", 
-                           pattern = "\\.R$", full.names = TRUE)
+# Analyze server files in your Shiny app
+server_files <- list.files("my_shiny_app/server", 
+                          pattern = "\\.R$", 
+                          full.names = TRUE, 
+                          recursive = TRUE)
 
-file_analysis <- data.frame()  # Initialize an empty dataframe
+file_analysis <- data.frame()
 
-for (file in file_path_df) {
+for (file in server_files) {
   shiny_analysis <- analyze_shiny_reactivity(file_path = file)
 
-  # Skip if NULL (empty file or only `source()` calls)
   if (is.null(shiny_analysis)) next
 
-  # Add filename column
   shiny_analysis$file_name <- basename(file)
-  
-  # Bind results
   file_analysis <- bind_rows(file_analysis, shiny_analysis)
 }
 
+# View the analysis results
 print(file_analysis)
 ```
 
+### Example Output
+
+```
+#>   type         name              inputs        output          file_name
+#> 1 render       plotSales        c("dateRange", "product")  plotOutput     sales_module.R
+#> 2 reactive     filteredData     c("selectedRegion")         NULL           data_processing.R  
+#> 3 observe      updateFilters    c("input$reset")            NULL           ui_helpers.R
+#> 4 render       tableSummary     c("filteredData")           tableOutput    summary_module.R
+#> 5 observeEvent downloadHandler  c("input$download")         NULL           download_handlers.R
+```
+
+### Analyzing Specific Patterns
+
+``` r
+# Find all reactive expressions that depend on a specific input
+file_analysis %>%
+  filter(type == "reactive", 
+         grepl("dateRange", inputs)) %>%
+  select(name, file_name)
+
+# Identify potentially unused render functions
+file_analysis %>%
+  filter(type == "render",
+         is.na(output) | output == "")
+```
+
+## 🔍 Scope & Limitations
+
+- **File types**: Supports `.R` files 
+- **Module support**: Works with both traditional Shiny apps and modularized applications
+- **Static analysis**: Performs static code analysis without running the app
+- **Pattern detection**: May not catch all edge cases or dynamically generated reactives
+
+## 🤝 Contributing
+
+Contributions are welcomed! 
+
+- Submit bug reports and feature requests via [GitHub Issues](https://github.com/dalyanalytics/shinyfa/issues)
+- Fork the repository and submit pull requests for improvements
+- Help us improve documentation and add more examples
+
+## 📄 License
+
+MIT © Jasmine Daly / shinyfa authors
+

README.md

@@ -1,10 +1,14 @@
-# shinyfa 0.0.0.9000
+# shinyfa 0.0.1
 
 ## R CMD check results
 
-Duration: 19.7s
+Duration: 18.5s
 
 0 errors ✔ | 0 warnings ✔ | 0 notes ✔
 
 R CMD check succeeded
 
+* This is a new release.
+* The words 'onboarding' and 'codebases' are not misspellings in the description file.
+* Updated Shiny to 'shiny' in Title and Description fields.
+