Overhaul of the package

.github/workflows/build-docs.yml

@@ -29,7 +29,7 @@ jobs:
       - name: Build docs
         run: |
           python setup.py build_ext --inplace
-          cp build/lib*/rds2py/rds_parser* src/rds2py/
+          cp build/lib*/rds2py/lib_rds_parser* src/rds2py/
           tox -e docs
           touch ./docs/_build/html/.nojekyll
 

.github/workflows/publish-pypi.yml

@@ -28,7 +28,7 @@ jobs:
 
   build_macosx_x86_64:
     name: Build wheels for macosx x86_64
-    runs-on: macos-11
+    runs-on: macos-13
     steps:
       - name: Check out repository
         uses: actions/checkout@v3

.gitignore

@@ -52,3 +52,6 @@ MANIFEST
 .venv*/
 .conda*/
 .python-version
+
+extern/rds2cpp*
+src/rds2py/lib/parser.cpp

.pre-commit-config.yaml

@@ -25,18 +25,20 @@ repos:
       args: [--in-place, --wrap-descriptions=120, --wrap-summaries=120]
       # --config, ./pyproject.toml
 
-- repo: https://github.com/psf/black
-  rev: 24.8.0
-  hooks:
-  - id: black
-    language_version: python3
+# - repo: https://github.com/psf/black
+#   rev: 24.8.0
+#   hooks:
+#   - id: black
+#     language_version: python3
 
 - repo: https://github.com/astral-sh/ruff-pre-commit
   # Ruff version.
   rev: v0.6.8
   hooks:
     - id: ruff
       args: [--fix, --exit-non-zero-on-fix]
+    # Run the formatter.
+    - id: ruff-format
 
 ## If like to embrace black styles even in the docs:
 # - repo: https://github.com/asottile/blacken-docs

AUTHORS.md

@@ -1,3 +1,3 @@
 # Contributors
 
-* jkanche [[email protected]](mailto:[email protected])
+* Jayaram Kancherla [[email protected]](mailto:[email protected])

CHANGELOG.md

@@ -1,13 +1,17 @@
 # Changelog
 
-## Development
+## Version 0.5.0
 
-- Fix github issue with showing incorrect package version on github pages.
+- Complete overhaul of the codebase using pybind11
+- Streamlined readers for R data types
+- Updated API for all classes and methods
+- Updated documentation and tests.
 
 ## Version 0.4.5
 
 - Switch to pybind11 to implementing the bindings to rds2cpp.
 - Update tests, documentation and actions.
+- Fix github issue with showing incorrect package version on github pages.
 
 ## Version 0.4.4
 

README.md

@@ -4,69 +4,104 @@
 
 # rds2py
 
-Parse and construct Python representations for datasets stored in RDS files. `rds2py` supports a few base classes from R and Bioconductor's `SummarizedExperiment` and `SingleCellExperiment` S4 classes. **_This is possible because of [Aaron's rds2cpp library](https://github.com/LTLA/rds2cpp)._**
-
-The package uses memory views (except for strings) to access the same memory from C++ in Python (through Cython of course). This is especially useful for large datasets so we don't make multiple copies of data.
-
-## Install
+Parse and construct Python representations for datasets stored in RDS files. `rds2py` supports various base classes from R, and Bioconductor's `SummarizedExperiment` and `SingleCellExperiment` S4 classes. ***For more details, check out [rds2cpp library](https://github.com/LTLA/rds2cpp).***
+
+> **Important Version Notice**
+>
+> Version 0.5.0 brings major changes to the package:
+> - Complete overhaul of the codebase using pybind11
+> - Streamlined readers for R data types
+> - Updated API for all classes and methods
+>
+> Please refer to the [documentation](https://biocpy.github.io/rds2py/) for the latest usage guidelines. Previous versions may have incompatible APIs.
+
+The package provides:
+
+- Efficient parsing of RDS files with *minimal* memory overhead
+- Support for R's basic data types and complex S4 objects
+  - Vectors (numeric, character, logical)
+  - Factors
+  - Data frames
+  - Matrices (dense and sparse)
+  - Run-length encoded vectors (Rle)
+- Conversion to appropriate Python/NumPy/SciPy data structures
+  - dgCMatrix (sparse column matrix)
+  - dgRMatrix (sparse row matrix)
+  - dgTMatrix (sparse triplet matrix)
+- Preservation of metadata and attributes from R objects
+- Integration with BiocPy ecosystem for Bioconductor classes
+  - SummarizedExperiment
+  - RangedSummarizedExperiment
+  - SingleCellExperiment
+  - GenomicRanges
+  - MultiAssayExperiment
+
+## Installation
 
 Package is published to [PyPI](https://pypi.org/project/rds2py/)
 
 ```shell
 pip install rds2py
 ```
 
-## Usage
-
-If you do not have an RDS object handy, feel free to download one from [single-cell-test-files](https://github.com/jkanche/random-test-files/releases).
+## Quick Start
 
 ```python
-from rds2py import as_summarized_experiment, read_rds
+from rds2py import read_rds
 
-r_obj = read_rds(<path_to_file>)
+# Read any RDS file
+r_obj = read_rds("path/to/file.rds")
 ```
 
-This `r_obj` holds a dictionary representation of the RDS file, we can now transform this object into Python representations.
-
-`rObj` always contains two keys
+## Usage
 
-- `data`: If atomic entities, contains the NumPy view of the array.
-- `attributes`: Additional properties available for the object.
+If you do not have an RDS object handy, feel free to download one from [single-cell-test-files](https://github.com/jkanche/random-test-files/releases).
 
-In addition, the package provides functions to convert parsed R objects into Python representations.
+### Basic Usage
 
 ```python
-from rds2py import as_spase_matrix, as_summarized_experiment
-
-# to convert an robject to a sparse matrix
-sp_mat = as_sparse(rObj)
-
-# to convert an robject to SCE
-sce = as_summarized_experiment(rObj)
+from rds2py import read_rds
+r_obj = read_rds("path/to/file.rds")
 ```
 
-For more examples converting `data.frame`, `dgCMatrix`, `dgRMatrix`, `dgTMatrix` to Python, checkout the [documentation](https://biocpy.github.io/rds2py/).
+The returned `r_obj` either returns an appropriate Python class if a parser is already implemented or returns the dictionary containing the data from the RDS file.
 
-## Developer Notes
+## Write-your-own-reader
 
-This project uses Cython to provide bindings from C++ to Python.
+In addition, the package provides the dictionary representation of the RDS file, allowing users to write their own custom readers into appropriate Python representations.
 
-Steps to setup dependencies -
+```python
+from rds2py import parse_rds
 
-- git submodules is initialized in `extern/rds2cpp`
-- `cmake .` in `extern/rds2cpp` directory to download dependencies, especially the `byteme` library
+data = parse_rds("path/to/file.rds")
+print(data)
+```
 
-First one needs to build the extern library, this would generate a shared object file to `src/rds2py/core-[*].so`
+if you know this RDS file contains an `GenomicRanges` object, you can use or modify the provided list reader, or write your own parser to convert this dictionary.
 
-```shell
-python setup.py build_ext --inplace
+```python
+from rds2py.read_granges import read_genomic_ranges
+
+gr = read_genomic_ranges(data)
 ```
 
-For typical development workflows, run
+## Type Conversion Reference
 
-```shell
-python setup.py build_ext --inplace && tox
-```
+| R Type | Python/NumPy Type |
+|--------|------------------|
+| numeric | numpy.ndarray (float64) |
+| integer | numpy.ndarray (int32) |
+| character | list of str |
+| logical | numpy.ndarray (bool) |
+| factor | list |
+| data.frame | BiocFrame |
+| matrix | numpy.ndarray or scipy.sparse matrix |
+| dgCMatrix | scipy.sparse.csc_matrix |
+| dgRMatrix | scipy.sparse.csr_matrix |
+
+## Developer Notes
+
+This project uses pybind11 to provide bindings to the rds2cpp library. Please make sure necessary C++ compiler is installed on your system.
 
 <!-- pyscaffold-notes -->
 

docs/tutorial.md

@@ -2,64 +2,40 @@
 
 If you do not have an RDS object handy, feel free to download one from [single-cell-test-files](https://github.com/jkanche/random-test-files/releases).
 
-## Step 1: Read a RDS file in Python
-
-First we need to read the RDS file that can be easily explored in Python. The `read_rds` parses the R object and returns
-a dictionary of the R object.
+### Basic Usage
 
 ```python
 from rds2py import read_rds
-
-rObj = read_rds(<path_to_file>)
+r_obj = read_rds("path/to/file.rds")
 ```
 
-Once we have a realized structure, we can now convert this object to useful Python representations. It contains two keys
-
-- `data`: If atomic entities, contains the numpy view of the memory space.
-- `attributes`: Additional properties available for the object.
-
-The package provides friendly functions to convert some R representations to useful Python representations.
-
-## Step 2: Python representations
+The returned `r_obj` either returns an appropriate Python class if a parser is already implemented or returns the dictionary containing the data from the RDS file.
 
-### Matrices
+## Write-your-own-reader
 
-Use these methods if the RDS file contains either a sparse matrix (`dgCMatrix`, `dgRMatrix`, or `dgTMatrix`) or a dense matrix.
-
-**_Note: If an R object contains `dims` in the `attributes`, we consider this as a matrix._**
+In addition, the package provides the dictionary representation of the RDS file, allowing users to write their own custom readers into appropriate Python representations.
 
 ```python
-from rds2py import as_spase_matrix, as_dense_matrix
-
-# to convert an robject to a sparse matrix
-sp_mat = as_sparse_matrix(rObj)
-
-# to convert an robject to a sparse matrix
-dense_mat = as_dense_matrix(rObj)
-```
-
-### Pandas DataFrame
+from rds2py import parse_rds
 
-Methods are available to construct a pandas `DataFrame` from data stored in an RDS file. The package supports two R classes for this operation - `data.frame` and `DFrame` classes.
-
-```python
-from rds2py import as_pandas
-
-# to convert an robject to DF
-df = as_pandas(rObj)
-```
-
-### S4 classes: specifically `SingleCellExperiment` or `SummarizedExperiment`
-
-We also support `SingleCellExperiment` or `SummarizedExperiment` from Bioconductor. the `as_summarized_experiment` method is how we one can do this operation.
-
-**_Note: This method also serves as an example on how to convert complex R structures into Python representations._**
-
-```python
-from rds2py import as_summarized_experiment
+data = parse_rds("path/to/file.rds")
+print(data)
 
-# to convert an robject to SCE
-sp_mat = as_summarized_experiment(rObj)
+# now write your own parser to convert this dictionary.
 ```
 
-Well thats it, hack on & create more base representations to encapsulate complex structures. If you want to add more representations, feel free to send a PR!
+## Type Conversion Reference
+
+| R Type | Python/NumPy Type |
+|--------|------------------|
+| numeric | numpy.ndarray (float64) |
+| integer | numpy.ndarray (int32) |
+| character | list of str |
+| logical | numpy.ndarray (bool) |
+| factor | list |
+| data.frame | BiocFrame |
+| matrix | numpy.ndarray or scipy.sparse matrix |
+| dgCMatrix | scipy.sparse.csc_matrix |
+| dgRMatrix | scipy.sparse.csr_matrix |
+
+Check out the module reference for more information on these classes.

lib/CMakeLists.txt

@@ -31,6 +31,6 @@ set_property(TARGET ${TARGET} PROPERTY CXX_STANDARD 17)
 target_link_libraries(${TARGET} PRIVATE rds2cpp pybind11::pybind11)
 
 set_target_properties(${TARGET} PROPERTIES
-    OUTPUT_NAME rds_parser
+    OUTPUT_NAME lib_rds_parser
     PREFIX ""
 )

lib/src/rdswrapper.cpp

@@ -20,12 +20,12 @@ class RdsReader {
         if (!ptr) throw std::runtime_error("Null pointer in 'get_rtype'.");
         // py::print("arg::", static_cast<int>(ptr->type()));
         switch (ptr->type()) {
+            case rds2cpp::SEXPType::S4: return "S4";
             case rds2cpp::SEXPType::INT: return "integer";
             case rds2cpp::SEXPType::REAL: return "double";
             case rds2cpp::SEXPType::STR: return "string";
             case rds2cpp::SEXPType::LGL: return "boolean";
             case rds2cpp::SEXPType::VEC: return "vector";
-            case rds2cpp::SEXPType::S4: return "S4";
             case rds2cpp::SEXPType::NIL: return "null";
             default: return "other";
         }
@@ -164,7 +164,7 @@ class RdsObject {
     }
 };
 
-PYBIND11_MODULE(rds_parser, m) {
+PYBIND11_MODULE(lib_rds_parser, m) {
     py::register_exception<std::runtime_error>(m, "RdsParserError");
 
     py::class_<RdsObject>(m, "RdsObject")

setup.cfg

@@ -5,7 +5,7 @@
 
 [metadata]
 name = rds2py
-description = Parse and read RDS files as Python representations
+description = Parse and construct Python representations for datasets stored in RDS files
 author = jkanche
 author_email = [email protected]
 license = MIT
@@ -50,11 +50,13 @@ python_requires = >=3.8
 install_requires =
     importlib-metadata; python_version<"3.8"
     numpy
-    pandas
     scipy
+    biocutils>=0.1.5
     singlecellexperiment>=0.4.1
     summarizedexperiment>=0.4.1
     genomicranges>=0.4.9
+    biocframe
+    multiassayexperiment
 
 [options.packages.find]
 where = src
@@ -65,17 +67,14 @@ exclude =
 # Add here additional requirements for extra features, to install with:
 # `pip install rds2py[PDF]` like:
 # PDF = ReportLab; RXP
+optional =
+    pandas
 
 # Add here test requirements (semicolon/line-separated)
 testing =
     setuptools
     pytest
     pytest-cov
-    numpy
-    pandas
-    scipy
-    singlecellexperiment
-    summarizedexperiment
 
 [options.entry_points]
 # Add here console scripts like:

setup.py

@@ -38,10 +38,7 @@ def build_cmake(self, ext):
                 "lib",
                 "-B",
                 build_temp,
-                "-Dpybind11_DIR="
-                + os.path.join(
-                    os.path.dirname(pybind11.__file__), "share", "cmake", "pybind11"
-                ),
+                "-Dpybind11_DIR=" + os.path.join(os.path.dirname(pybind11.__file__), "share", "cmake", "pybind11"),
                 "-DPYTHON_EXECUTABLE=" + sys.executable,
             ]
             if os.name != "nt":