csv_reader

Stable type · Native arrays and readers

Tier: stable · Kind: type · Topic: Native arrays and readers

Python	Julia	Rust
`CSVReader`	`CSVReader`	not exported

Python

class CSVReader
CSVReader.formats() -> List[str]
CSVReader.extensions() -> List[str]
CSVReader.open(blob_path: Any) -> Any
CSVReader.read_native(handle: Any, variables: Optional[Sequence[str]] = None, select: Optional[Any] = None, *, numeric_columns: Optional[Sequence[str]] = None, delimiter: str = ',', header_row: int = 0, **_: Any) -> NativeDataset

The active csv reader — a non-NetCDF format behind the same registry.

Columns named in numeric_columns parse to float64 1-D arrays keyed by the column (file_variable) name; every other column is returned as a list of str. All fields carry the single dimension index; there are no coordinates.

numeric_columns is REQUIRED by the loader spec and is not inferred: the corpus location_id column is digit-only text ("1"/"2") yet must stay a string, so “parses as a number” is not a safe signal. When it is None the reader falls back to best-effort inference (every value parses as a float), which the loader/.esm node should override. Quoted fields with embedded delimiters are handled by csv; matches the Julia CSVReader.

Members

read_native — Decode a delimited-text blob into a NativeDataset of points.

Source

Example (provider)

source = DataSource(
    "stations",
    "csv",  # the format-registry key that selects the reader
    (FIXTURES / "stations.csv").as_uri(),
    variables=["value", "location_id"],
    reader_kwargs={"numeric_columns": ["latitude", "longitude", "value"]},
)
data = Provider(source, cache).materialize()
assert isinstance(data, NativeDataset)
assert data.variable_names() == ["location_id", "value"]
assert data["value"].data.dtype == np.float64
assert list(data["value"].data) == [152.3, 168.7, 98.1, 110.4]
# Digit-only text columns stay strings: nothing is inferred.
assert data["location_id"].data == ["1", "1", "2", "2"]

From docs/api/examples/python/provider.py

Julia

struct CSVReader <: Reader
CSVReader()

CSVReader()

The csv format reader — a second reader proving a non-NetCDF format plugs into FORMAT_REGISTRY unchanged (spec/conformance.md). Columns named in numeric_columns parse to Float64 1-D arrays keyed by the column (file_variable) name; every other column is returned as a String array. All fields have a single dimension index; there are no coordinates.

numeric_columns is REQUIRED by the loader spec and is not inferred: the corpus location_id column is digit-only text ("1","2") yet must stay a string, so “parses as a number” is not a safe signal. When numeric_columns === nothing the reader falls back to best-effort inference (every value parses as a float), which the loader/.esm node should override. Quoted fields with embedded delimiters are not handled (the points corpus has none); add that when a loader needs it.

Source

Example (provider)

url = "file://" * abspath(joinpath(FIXTURES, "stations.csv"))
p = const_provider(cache, url; format = "csv", source_loader = "stations",
                   variables = ["value", "location_id"],
                   reader_kwargs = (numeric_columns = ["latitude", "longitude", "value"],))
@assert is_const(p) && refresh_times(p) == Float64[]  # a CONST provider never refreshes
data = materialize(p)
@assert data isa NativeDataset
@assert Set(variable_names(data)) == Set(["location_id", "value"])
@assert data["value"].data == [152.3, 168.7, 98.1, 110.4]
# Digit-only text columns stay strings: nothing is inferred.
@assert data["location_id"].data == ["1", "1", "2", "2"]

From docs/api/examples/julia/provider.jl

Rust

Rust does not export this type.