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nat.python 0.3.0.9000 (development version)

nat.python 0.3.0

  • simple_python() now pins the managed environment's Python interpreter to a known-good version (new python_version argument, default "3.12", overridable via options(nat.python.python_version=)) instead of letting reticulate pick, which on a fresh install can be a bleeding-edge Python that key packages do not yet support. An existing environment at a different version is kept, with a warning pointing at simple_python("cleanenv") (#10).
  • pandas2df() now converts pandas extension-array columns that reticulate leaves unconverted, in particular pandas 3.0's default Arrow-backed string dtype (PDEP-14): string columns become R character vectors and other Arrow columns (e.g. int64[pyarrow] ids) map to the same R types as their native-dtype equivalents (#9).
  • simple_python() pins the baseline install to pandas < 3 for now. Although pandas2df() handles pandas 3.0, the pin is retained as a caution while the wider ecosystem settles on pandas 3; lift it (back to pandas) once ready.
  • CI now provisions Python through simple_python() itself (the end-user path), rather than a bespoke reticulate::py_install() call.
  • Testing: added a test-coverage workflow reporting to Codecov (#5) and substantially expanded coverage of previously-untested paths, from 34% to 66% (#6).

nat.python 0.2.0

First tagged release. A small shared layer of Python interoperability and environment management for the natverse, built on reticulate. fafbseg, bancr and seatabler depend on it for both concerns.

Python environment management

  • simple_python() provisions and manages a shared miniconda environment, with curated bundles for the FlyWire/connectomics ecosystem: "basic" (cloud-volume + seatable_api + CAVEclient), "full" (+ navis + fafbseg), "extra" (+ skeletonisation tooling), "minimal" (just pandas, nat.python's own baseline; numpy rides in with it), and "none" for an env with no bundle.
  • check_reticulate() checks a usable Python is available, guiding users to simple_python() when not.

Module management

  • check_module() — install/load gate that checks whether a module is present (from distribution metadata, without importing), imports it, and on absence offers to install it or errors with guidance.
  • module_available(), module_version() / forget_module_version(), py_module_info() for introspecting the environment.

Data conversion

  • pandas2df() converts pandas DataFrames to R, recovering 64-bit id columns as bit64, flattening object/numpy columns and coercing datetimes.
    • Fast-path for pandas nullable Int64/UInt64 extension columns, which reticulate otherwise converts cell-by-cell (~24x faster on large id-heavy frames; output byte-for-byte identical).
    • A bigint argument and unified integer-column classification.
  • null2na() helper for None → NA.

64-bit id marshalling

  • pyids2bit64(), rids2pyint(), rids2raw() round-trip large integer identifiers between R (bit64), numpy and raw bytes without precision loss; int64_overflows() flags values that would overflow.

Datetime

  • ts2pydatetime() converts R timestamps to Python datetimes.