python/tests/generic.py

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#
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import datetime
from datetime import timezone

import numpy as np
import pyarrow as pa
import pyarrow.csv

# used to write parquet files
import pyarrow.parquet as pq


def data():
    rng = np.random.default_rng(1)
    data = np.concatenate(
        [
            rng.normal(0, 0.01, size=50),
            rng.normal(50, 0.01, size=50),
        ]
    )
    return pa.array(data)


def data_with_nans():
    rng = np.random.default_rng(0)
    data = rng.normal(0, 0.01, size=50)
    mask = rng.normal(0, 2, size=50)
    data[mask == 0] = np.nan
    return data


def data_datetime(f):
    data = [
        datetime.datetime.now(tz=timezone.utc),
        datetime.datetime.now(tz=timezone.utc) - datetime.timedelta(days=1),
        datetime.datetime.now(tz=timezone.utc) + datetime.timedelta(days=1),
    ]
    return pa.array(data, type=pa.timestamp(f), mask=np.array([False, True, False]))


def data_date32():
    data = [
        datetime.date(2000, 1, 1),
        datetime.date(1980, 1, 1),
        datetime.date(2030, 1, 1),
    ]
    return pa.array(data, type=pa.date32(), mask=np.array([False, True, False]))


def data_timedelta(f):
    data = [
        datetime.timedelta(days=100),
        datetime.timedelta(days=1),
        datetime.timedelta(seconds=1),
    ]
    return pa.array(data, type=pa.duration(f), mask=np.array([False, True, False]))


def data_binary_other():
    return np.array([1, 0, 0], dtype="u4")


def write_parquet(path, data):
    table = pa.Table.from_arrays([data], names=["a"])
    pq.write_table(table, path)
    return str(path)