Updated script that can be controled by Nodejs web app
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mac OS
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import re
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import numpy as np
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import pytest
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from pandas._libs.tslibs import Timestamp
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import pandas as pd
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from pandas import (
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DataFrame,
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HDFStore,
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Index,
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MultiIndex,
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Series,
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_testing as tm,
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concat,
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date_range,
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)
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from pandas.tests.io.pytables.common import (
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_maybe_remove,
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ensure_clean_store,
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)
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from pandas.util import _test_decorators as td
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pytestmark = pytest.mark.single_cpu
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def test_format_type(tmp_path, setup_path):
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df = DataFrame({"A": [1, 2]})
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with HDFStore(tmp_path / setup_path) as store:
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store.put("a", df, format="fixed")
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store.put("b", df, format="table")
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assert store.get_storer("a").format_type == "fixed"
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assert store.get_storer("b").format_type == "table"
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def test_format_kwarg_in_constructor(tmp_path, setup_path):
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# GH 13291
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msg = "format is not a defined argument for HDFStore"
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with pytest.raises(ValueError, match=msg):
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HDFStore(tmp_path / setup_path, format="table")
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def test_api_default_format(tmp_path, setup_path):
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# default_format option
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with ensure_clean_store(setup_path) as store:
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df = DataFrame(
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1.1 * np.arange(120).reshape((30, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=Index([f"i-{i}" for i in range(30)], dtype=object),
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)
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with pd.option_context("io.hdf.default_format", "fixed"):
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_maybe_remove(store, "df")
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store.put("df", df)
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assert not store.get_storer("df").is_table
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msg = "Can only append to Tables"
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with pytest.raises(ValueError, match=msg):
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store.append("df2", df)
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with pd.option_context("io.hdf.default_format", "table"):
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_maybe_remove(store, "df")
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store.put("df", df)
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assert store.get_storer("df").is_table
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_maybe_remove(store, "df2")
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store.append("df2", df)
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assert store.get_storer("df").is_table
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path = tmp_path / setup_path
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df = DataFrame(
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1.1 * np.arange(120).reshape((30, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=Index([f"i-{i}" for i in range(30)], dtype=object),
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)
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with pd.option_context("io.hdf.default_format", "fixed"):
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df.to_hdf(path, key="df")
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with HDFStore(path) as store:
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assert not store.get_storer("df").is_table
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with pytest.raises(ValueError, match=msg):
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df.to_hdf(path, key="df2", append=True)
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with pd.option_context("io.hdf.default_format", "table"):
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df.to_hdf(path, key="df3")
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with HDFStore(path) as store:
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assert store.get_storer("df3").is_table
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df.to_hdf(path, key="df4", append=True)
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with HDFStore(path) as store:
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assert store.get_storer("df4").is_table
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def test_put(setup_path):
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with ensure_clean_store(setup_path) as store:
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ts = Series(
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np.arange(10, dtype=np.float64), index=date_range("2020-01-01", periods=10)
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)
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df = DataFrame(
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np.random.default_rng(2).standard_normal((20, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=date_range("2000-01-01", periods=20, freq="B"),
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)
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store["a"] = ts
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store["b"] = df[:10]
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store["foo/bar/bah"] = df[:10]
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store["foo"] = df[:10]
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store["/foo"] = df[:10]
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store.put("c", df[:10], format="table")
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# not OK, not a table
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msg = "Can only append to Tables"
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with pytest.raises(ValueError, match=msg):
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store.put("b", df[10:], append=True)
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# node does not currently exist, test _is_table_type returns False
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# in this case
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_maybe_remove(store, "f")
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with pytest.raises(ValueError, match=msg):
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store.put("f", df[10:], append=True)
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# can't put to a table (use append instead)
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with pytest.raises(ValueError, match=msg):
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store.put("c", df[10:], append=True)
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# overwrite table
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store.put("c", df[:10], format="table", append=False)
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tm.assert_frame_equal(df[:10], store["c"])
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def test_put_string_index(setup_path):
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with ensure_clean_store(setup_path) as store:
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index = Index([f"I am a very long string index: {i}" for i in range(20)])
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s = Series(np.arange(20), index=index)
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df = DataFrame({"A": s, "B": s})
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store["a"] = s
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tm.assert_series_equal(store["a"], s)
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store["b"] = df
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tm.assert_frame_equal(store["b"], df)
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# mixed length
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index = Index(
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["abcdefghijklmnopqrstuvwxyz1234567890"]
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+ [f"I am a very long string index: {i}" for i in range(20)]
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)
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s = Series(np.arange(21), index=index)
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df = DataFrame({"A": s, "B": s})
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store["a"] = s
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tm.assert_series_equal(store["a"], s)
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store["b"] = df
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tm.assert_frame_equal(store["b"], df)
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def test_put_compression(setup_path):
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with ensure_clean_store(setup_path) as store:
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df = DataFrame(
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np.random.default_rng(2).standard_normal((10, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=date_range("2000-01-01", periods=10, freq="B"),
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)
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store.put("c", df, format="table", complib="zlib")
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tm.assert_frame_equal(store["c"], df)
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# can't compress if format='fixed'
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msg = "Compression not supported on Fixed format stores"
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with pytest.raises(ValueError, match=msg):
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store.put("b", df, format="fixed", complib="zlib")
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@td.skip_if_windows
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def test_put_compression_blosc(setup_path):
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df = DataFrame(
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np.random.default_rng(2).standard_normal((10, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=date_range("2000-01-01", periods=10, freq="B"),
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)
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with ensure_clean_store(setup_path) as store:
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# can't compress if format='fixed'
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msg = "Compression not supported on Fixed format stores"
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with pytest.raises(ValueError, match=msg):
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store.put("b", df, format="fixed", complib="blosc")
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store.put("c", df, format="table", complib="blosc")
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tm.assert_frame_equal(store["c"], df)
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def test_put_mixed_type(setup_path):
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df = DataFrame(
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np.random.default_rng(2).standard_normal((10, 4)),
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columns=Index(list("ABCD"), dtype=object),
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index=date_range("2000-01-01", periods=10, freq="B"),
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)
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df["obj1"] = "foo"
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df["obj2"] = "bar"
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df["bool1"] = df["A"] > 0
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df["bool2"] = df["B"] > 0
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df["bool3"] = True
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df["int1"] = 1
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df["int2"] = 2
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df["timestamp1"] = Timestamp("20010102").as_unit("ns")
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df["timestamp2"] = Timestamp("20010103").as_unit("ns")
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df["datetime1"] = Timestamp("20010102").as_unit("ns")
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df["datetime2"] = Timestamp("20010103").as_unit("ns")
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df.loc[df.index[3:6], ["obj1"]] = np.nan
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df = df._consolidate()
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with ensure_clean_store(setup_path) as store:
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_maybe_remove(store, "df")
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with tm.assert_produces_warning(pd.errors.PerformanceWarning):
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store.put("df", df)
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expected = store.get("df")
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tm.assert_frame_equal(expected, df)
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@pytest.mark.parametrize("format", ["table", "fixed"])
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@pytest.mark.parametrize(
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"index",
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[
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Index([str(i) for i in range(10)]),
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Index(np.arange(10, dtype=float)),
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Index(np.arange(10)),
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date_range("2020-01-01", periods=10),
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pd.period_range("2020-01-01", periods=10),
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],
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)
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def test_store_index_types(setup_path, format, index):
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# GH5386
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# test storing various index types
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with ensure_clean_store(setup_path) as store:
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df = DataFrame(
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np.random.default_rng(2).standard_normal((10, 2)),
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columns=list("AB"),
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index=index,
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)
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_maybe_remove(store, "df")
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store.put("df", df, format=format)
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tm.assert_frame_equal(df, store["df"])
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def test_column_multiindex(setup_path):
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# GH 4710
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# recreate multi-indexes properly
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index = MultiIndex.from_tuples(
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[("A", "a"), ("A", "b"), ("B", "a"), ("B", "b")], names=["first", "second"]
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)
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df = DataFrame(np.arange(12).reshape(3, 4), columns=index)
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expected = df.set_axis(df.index.to_numpy())
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with ensure_clean_store(setup_path) as store:
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store.put("df", df)
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tm.assert_frame_equal(
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store["df"], expected, check_index_type=True, check_column_type=True
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)
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store.put("df1", df, format="table")
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tm.assert_frame_equal(
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store["df1"], expected, check_index_type=True, check_column_type=True
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)
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msg = re.escape("cannot use a multi-index on axis [1] with data_columns ['A']")
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with pytest.raises(ValueError, match=msg):
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store.put("df2", df, format="table", data_columns=["A"])
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msg = re.escape("cannot use a multi-index on axis [1] with data_columns True")
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with pytest.raises(ValueError, match=msg):
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store.put("df3", df, format="table", data_columns=True)
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# appending multi-column on existing table (see GH 6167)
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with ensure_clean_store(setup_path) as store:
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store.append("df2", df)
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store.append("df2", df)
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tm.assert_frame_equal(store["df2"], concat((df, df)))
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# non_index_axes name
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df = DataFrame(np.arange(12).reshape(3, 4), columns=Index(list("ABCD"), name="foo"))
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expected = df.set_axis(df.index.to_numpy())
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with ensure_clean_store(setup_path) as store:
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store.put("df1", df, format="table")
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tm.assert_frame_equal(
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store["df1"], expected, check_index_type=True, check_column_type=True
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)
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def test_store_multiindex(setup_path):
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# validate multi-index names
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# GH 5527
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with ensure_clean_store(setup_path) as store:
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def make_index(names=None):
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dti = date_range("2013-12-01", "2013-12-02")
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mi = MultiIndex.from_product([dti, range(2), range(3)], names=names)
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return mi
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# no names
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_maybe_remove(store, "df")
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df = DataFrame(np.zeros((12, 2)), columns=["a", "b"], index=make_index())
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store.append("df", df)
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tm.assert_frame_equal(store.select("df"), df)
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# partial names
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_maybe_remove(store, "df")
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df = DataFrame(
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np.zeros((12, 2)),
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columns=["a", "b"],
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index=make_index(["date", None, None]),
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)
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store.append("df", df)
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tm.assert_frame_equal(store.select("df"), df)
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# series
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_maybe_remove(store, "ser")
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ser = Series(np.zeros(12), index=make_index(["date", None, None]))
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store.append("ser", ser)
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xp = Series(np.zeros(12), index=make_index(["date", "level_1", "level_2"]))
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tm.assert_series_equal(store.select("ser"), xp)
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# dup with column
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_maybe_remove(store, "df")
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df = DataFrame(
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np.zeros((12, 2)),
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columns=["a", "b"],
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index=make_index(["date", "a", "t"]),
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)
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msg = "duplicate names/columns in the multi-index when storing as a table"
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with pytest.raises(ValueError, match=msg):
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store.append("df", df)
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# dup within level
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_maybe_remove(store, "df")
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df = DataFrame(
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np.zeros((12, 2)),
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columns=["a", "b"],
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index=make_index(["date", "date", "date"]),
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)
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with pytest.raises(ValueError, match=msg):
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store.append("df", df)
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# fully names
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_maybe_remove(store, "df")
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df = DataFrame(
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np.zeros((12, 2)),
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columns=["a", "b"],
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index=make_index(["date", "s", "t"]),
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)
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store.append("df", df)
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tm.assert_frame_equal(store.select("df"), df)
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@pytest.mark.parametrize("format", ["fixed", "table"])
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def test_store_periodindex(tmp_path, setup_path, format):
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# GH 7796
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# test of PeriodIndex in HDFStore
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df = DataFrame(
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np.random.default_rng(2).standard_normal((5, 1)),
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index=pd.period_range("20220101", freq="M", periods=5),
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)
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path = tmp_path / setup_path
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df.to_hdf(path, key="df", mode="w", format=format)
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expected = pd.read_hdf(path, "df")
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tm.assert_frame_equal(df, expected)
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