When You install Synapser, You may encounter a similar error:
$ R CMD BUILD .
Execution halted
ERROR: configuration failed for package ‘synapser’
* removing ‘/private/var/folders/2n/xwh21m9s3sq_mhnkbc6n6z_c0000gn/T/RtmpZ47UPP/Rinstf55478c3f09/synapser’For this error, You can try first remove $HOME.virtualenvs then run the build command again.
When you build synapser, you may encounter the following error:
$ R CMD BUILD .
Error: processing vignette 'upload.Rmd' failed with diagnostics:
No credentials provided.
--- failed re-building ‘upload.Rmd’First, create a file named .synapseConfig in your home
directory. Then add the following lines to the file:
[authentication]
authtoken = <authtoken>Now, you should be able to build Synapser.
If you encounter errors related to rjson version conflicts during installation, such as:
Error in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]) :
namespace 'rjson' 0.2.23 is being loaded, but <= 0.2.21 is required
Calls: <Anonymous> ... namespaceImportFrom -> asNamespace -> loadNamespace
Execution halted
ERROR: lazy loading failed for package 'synapser'This occurs when you have a newer version of rjson installed that is incompatible with synapser. The best solution is to use the recommended installation method:
Recommended Solution:
For the latest version:
# Install remotes if not already installed
if (!require("remotes", quietly = TRUE)) {
install.packages("remotes")
}
# Install the latest version of synapser (this automatically handles dependency versions)
remotes::install_cran("synapser", repos = c("http://ran.synapse.org", "https://cloud.r-project.org"))For a specific version:
# Install remotes if not already installed
if (!require("remotes", quietly = TRUE)) {
install.packages("remotes")
}
# Install a specific version of synapser (e.g., version 2.1.1.259 - major.minor.patch.build)
remotes::install_version("synapser", version = "X.Y.Z.AAA", repos = c("http://ran.synapse.org", "https://cloud.r-project.org"))Manual Resolution (if you prefer to manage dependencies yourself):
Remove the conflicting package:
remove.packages("rjson")Install the compatible version using remotes:
if (!require("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_version("rjson", "0.2.21")Also ensure you have the correct reticulate version:
remotes::install_version("reticulate", "1.28")Re-install synapser:
install.packages("synapser", repos=c("http://ran.synapse.org", "https://cloud.r-project.org"))Synapser is only compatible with Python versions 3.8 to 3.11. If you’re using Python 3.12 or later, you may encounter installation or runtime errors. We recommend using Python 3.10 for optimal compatibility.
To check your Python version in R:
reticulate::py_config()Important: synapser versions 2.1.0+ require R versions 4.1.3 ≤ R < 4.5. If you are using R ≥ 4.5, the installation will automatically fall back to synapser 2.0.0 instead of the latest version.
Check your R version:
R.version.stringIf you have R ≥ 4.5: - You must downgrade to R 4.4.x or earlier to install synapser 2.1.1+ - Otherwise, installation will automatically select synapser 2.0.0 - This happens because R’s package installer respects dependency constraints
If installation selects 2.0.0 when you expect 2.1.1: - Verify your R version is between 4.1.3 and 4.4.x - Check that your reticulate version is ≤ 1.28 (required for synapser 2.1.x) - Consider using the recommended installation method with version specification
Windows: 1. Download R 4.4.2 from CRAN Windows archives 2. Uninstall your current R version from Control Panel 3. Install the downloaded R 4.4.2 installer 4. Restart RStudio to use the new R version
macOS: 1. Download R 4.4.2 from CRAN macOS
archives 2. Install the .pkg file (this will replace
your current R installation) 3. Restart RStudio to use the new R
version
Linux (Ubuntu/Debian):
# Remove current R version
sudo apt remove r-base r-base-core r-base-dev
# Add CRAN repository for specific R version
sudo apt update
sudo apt install software-properties-common
sudo add-apt-repository "deb https://cloud.r-project.org/bin/linux/ubuntu $(lsb_release -cs)-cran40/"
# Install R 4.4
sudo apt install r-base=4.4.2-1cran1.2004.0 r-base-core=4.4.2-1cran1.2004.0Linux (Amazon Linux/RHEL/CentOS):
# Remove current R version
sudo dnf remove R R-core R-devel
# Option 1: Install from source (recommended for version control)
sudo dnf groupinstall -y "Development Tools"
sudo dnf install -y gcc-gfortran readline-devel libX11-devel libXt-devel \
zlib-devel bzip2-devel xz-devel pcre2-devel curl-devel
# Download and compile R 4.4.2
cd /tmp
wget https://cran.r-project.org/src/base/R-4/R-4.4.2.tar.gz
tar -xzf R-4.4.2.tar.gz
cd R-4.4.2
./configure --enable-R-shlib --with-blas --with-lapack
make
sudo make install
# Fix PATH if older R version is still being used
echo 'export PATH="/usr/local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrcVerify downgrade:
R.version.string
# Should show something like "R version 4.4.2 (2024-11-01)"Troubleshooting Amazon Linux R Installation: If
which R still shows an old R version after compilation:
# Check current R location
which R
# If it shows /usr/local/R-4.5.1/bin/R instead of /usr/local/bin/R:
export PATH="/usr/local/bin:$PATH"
echo 'export PATH="/usr/local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrcAfter downgrading R: 1. Restart your R session/RStudio 2. Reinstall synapser using the recommended method:
remotes::install_cran("synapser", repos = c("http://ran.synapse.org", "https://cloud.r-project.org"))
packageVersion("synapser")
# Should show version 2.1.1 or laterSynapser is compatible with reticulate and the two packages can be used together in the same R session.
If you are getting this kind error:
synStore(tmp2)
Error in value[[3L]](cond) : 'concreteType'As of synapser v2.0.0, it is still only compatible with reticulate
v1.28 due to a miscellaneous update in reticulate
v1.29. Specifically, py_to_r() now succeeds when
converting subtypes of the built-in Python types (e.g. list, dict, str).
This change, while beneficial for general use, breaks synapser’s
internal type conversion mechanisms.
Why this limitation exists: Synapser relies on specific behavior in reticulate’s type conversion system to properly handle Synapse objects and their metadata. The changes in reticulate v1.29+ alter how Python objects are converted back to R, causing compatibility issues with synapser’s architecture.
To install the compatible version:
remotes::install_version("reticulate", "1.28")Alternative approach: If you need to use a newer version of reticulate for other projects, you can use the Synapse Python client directly through reticulate instead of synapser.
The core of the Synapser library is the python client. Reticulate is used to translate R to Python and back.
These are the documented conversions from R to Python: Reticulate Type Conversions
NA values in R do not have a direct equivalent in
Python. This has been a topic of great discussion. Synapser is not
trying to solve this. NA values in R are handled by
Reticulate per the implementation defined in Reticulate.
When working with R and Reticulate, NA values in types tables are converted by Reticulate depending on the data type.
For numeric data types, NA values are converted to the corresponding
R value NA_real_. For integer data types, NA values are
converted to NA_integer_. For logical data types, NA values
are converted to NA_logical_. For character data types, NA
values are converted to NA_character_.
In addition, Reticulate also converts any values that cannot be
coerced to the specified data type to NA_character_.
Reticulate performs these conversions automatically.
When Reticulate converts R objects to Python objects, the NA values
in R types tables are converted to Python’s None.
R’s NA is a logical constant of length 1 which is used
to represent the absence of a value. In Python, the equivalent of
NA is None, which is a special constant used
to indicate the absence of a value.
Reticulate automatically converts NA values in R types
tables to None when converting R objects to Python. This
ensures that the data types and values remain consistent between the two
languages.
Examples:
NAs to Python
True, which convert back to TRUE in R
na_logical = NA
class(na_logical)
## [1] "logical"
na_py <- reticulate::r_to_py(na_logical)
na_py
## True
na_r <- reticulate::py_to_r(na_py)
na_r
## [1] TRUE
na_logical = c(T, F, NA)
class(na_logical)
## [1] "logical"
na_py <- reticulate::r_to_py(na_logical)
na_py
## [True, False, True]
na_r <- reticulate::py_to_r(na_py)
na_r
## [1] TRUE FALSE TRUENAs to Python strings,
which convert back to characters in R
na_char = c("T", "F", NA)
class(na_char)
## [1] "character"
na_py <- reticulate::r_to_py(na_char)
na_py
## ['T', 'F', 'NA']
na_r <- reticulate::py_to_r(na_py)
na_r
## [1] "T" "F" "NA"NAs to Python
np.nan, which convert back to NA in RStarting with the Synapse Python client version 4.2.0, a change to how the Synapse Cache writes entries was introduced. The purpose of the change was to more accurately track when a file was last modified, and what the MD5 checksum of the file was at that point in time. Prior to this change the Synapse cache was a simple key-value store, however, with the new change, the cache is now a dictionary of dictionaries.
If you find that you receive the following error when trying to use
synGet:
> synapser::synGet("syn12345")
Error in value[[3L]](cond) : 'dict' object has no attribute 'endswith'You may have a “poisoned” cache. This can happen if you, or someone using the file system where your Synapse cache is stored, has ran the newer Synapse Python client - while you are still using the older version of Synapser/Python Client.
To resolve this issue, you can either:
Delete the Synapse cache directory: This will
force Synapser to re-download all files from Synapse and rebuild the
cache. By default the cache is stored in
~/.synapseCache.
Note: The following suggested commands have the potential to delete many files, so please ensure you have backups of any important data before running them. The cache directory is typically used to store temporary files and metadata. Deleting this data will only affect your local machine - It will not affect any data that is stored in Synapse. This will require you to re-download files from Synapse.
The exact commands will depend on your operating system, but here are some examples:
Linux/macOS:
Windows:
Upgrade to the latest version of Synapser: This will ensure that you are using the latest version of the Synapse Python client, which is compatible with the new cache format.
remotes::install_cran("synapser", repos = c("http://ran.synapse.org", "https://cloud.r-project.org"))