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import numpy as np
from pandas import (
DataFrame,
HDFStore,
Index,
date_range,
read_hdf,
)
from ..pandas_vb_common import BaseIO
class HDFStoreDataFrame(BaseIO):
def setup(self):
N = 25000
index = Index([f"i-{i}" for i in range(N)], dtype=object)
self.df = DataFrame(
{"float1": np.random.randn(N), "float2": np.random.randn(N)}, index=index
)
self.df_mixed = DataFrame(
{
"float1": np.random.randn(N),
"float2": np.random.randn(N),
"string1": ["foo"] * N,
"bool1": [True] * N,
"int1": np.random.randint(0, N, size=N),
},
index=index,
)
self.df_wide = DataFrame(np.random.randn(N, 100))
self.start_wide = self.df_wide.index[10000]
self.stop_wide = self.df_wide.index[15000]
self.df2 = DataFrame(
{"float1": np.random.randn(N), "float2": np.random.randn(N)},
index=date_range("1/1/2000", periods=N),
)
self.start = self.df2.index[10000]
self.stop = self.df2.index[15000]
self.df_wide2 = DataFrame(
np.random.randn(N, 100), index=date_range("1/1/2000", periods=N)
)
self.df_dc = DataFrame(
np.random.randn(N, 10), columns=[f"C{i:03d}" for i in range(10)]
)
self.fname = "__test__.h5"
self.store = HDFStore(self.fname)
self.store.put("fixed", self.df)
self.store.put("fixed_mixed", self.df_mixed)
self.store.append("table", self.df2)
self.store.append("table_mixed", self.df_mixed)
self.store.append("table_wide", self.df_wide)
self.store.append("table_wide2", self.df_wide2)
def teardown(self):
self.store.close()
self.remove(self.fname)
def time_read_store(self):
self.store.get("fixed")
def time_read_store_mixed(self):
self.store.get("fixed_mixed")
def time_write_store(self):
self.store.put("fixed_write", self.df)
def time_write_store_mixed(self):
self.store.put("fixed_mixed_write", self.df_mixed)
def time_read_store_table_mixed(self):
self.store.select("table_mixed")
def time_write_store_table_mixed(self):
self.store.append("table_mixed_write", self.df_mixed)
def time_read_store_table(self):
self.store.select("table")
def time_write_store_table(self):
self.store.append("table_write", self.df)
def time_read_store_table_wide(self):
self.store.select("table_wide")
def time_write_store_table_wide(self):
self.store.append("table_wide_write", self.df_wide)
def time_write_store_table_dc(self):
self.store.append("table_dc_write", self.df_dc, data_columns=True)
def time_query_store_table_wide(self):
self.store.select(
"table_wide", where="index > self.start_wide and index < self.stop_wide"
)
def time_query_store_table(self):
self.store.select("table", where="index > self.start and index < self.stop")
def time_store_repr(self):
repr(self.store)
def time_store_str(self):
str(self.store)
def time_store_info(self):
self.store.info()
class HDF(BaseIO):
params = ["table", "fixed"]
param_names = ["format"]
def setup(self, format):
self.fname = "__test__.h5"
N = 100000
C = 5
self.df = DataFrame(
np.random.randn(N, C),
columns=[f"float{i}" for i in range(C)],
index=date_range("20000101", periods=N, freq="h"),
)
self.df["object"] = Index([f"i-{i}" for i in range(N)], dtype=object)
self.df.to_hdf(self.fname, "df", format=format)
# Numeric df
self.df1 = self.df.copy()
self.df1 = self.df1.reset_index()
self.df1.to_hdf(self.fname, "df1", format=format)
def time_read_hdf(self, format):
read_hdf(self.fname, "df")
def peakmem_read_hdf(self, format):
read_hdf(self.fname, "df")
def time_write_hdf(self, format):
self.df.to_hdf(self.fname, "df", format=format)
from ..pandas_vb_common import setup # noqa: F401 isort:skip
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