在R中安装包时出现‘i386加载失败’错误，该如何解决？
Hey there, let's sort out that frustrating ERROR: loading failed for 'i386' issue you're facing while installing the ffanalytics package from GitHub. This is a common hiccup on Windows systems, and here's how to fix it:
What's Causing This?
This error pops up because your Windows R installation includes both 32-bit (i386) and 64-bit (x64) architectures, and the package fails to compile properly for the 32-bit version. It could be due to incompatible 32-bit dependencies, missing compile tools, or your system not needing 32-bit R at all.
Step-by-Step Solutions
1. Force Install Only the 64-Bit Version
Most modern Windows systems are 64-bit, so you can skip compiling the 32-bit version entirely. Run this command in your R console:
devtools::install_github("isaactpetersen/ffanalytics", args = "--no-multiarch")
The --no-multiarch flag tells R to only build and install the package for your current system architecture (64-bit), avoiding the problematic 32-bit compilation step.
2. Verify Your R Architecture
If the first method doesn't work, check which version of R you're running:
Sys.getenv("R_ARCH")
- If the output is
/i386, you're using the 32-bit R executable. Close R, open the 64-bit version (usually labeled "R x64" in your start menu), and try the installation again. - If it shows
/x64, you're already on 64-bit, so stick with the command from step 1.
3. Install Required Compilation Tools
Sometimes this error stems from missing Rtools, the set of tools needed to compile packages on Windows:
- Download the version of Rtools that matches your R release (check your R version with
version$version.string). - During installation, make sure to check the box that says "Add Rtools to system PATH".
- Restart R, then try installing
ffanalyticsagain.
4. Pre-Install Dependencies
If the package is failing because of missing dependencies, manually install the required packages first:
install.packages(c("dplyr", "tidyr", "purrr", "xml2", "rvest"))
Once these are installed, re-run the install_github command from step 1.
内容的提问来源于stack exchange，提问作者Luke
