add assets and perf script

example/derive_expression/perf.py

@@ -0,0 +1,143 @@
+
+import timeit
+import numpy as np
+
+BENCHMARKS = [1, 2, 3, 4]
+# BENCHMARKS = [1, 2]
+
+# BENCHMARK 1: NO HOLIDAYS INVOLVED
+
+setup = """
+import polars as pl
+import polars_business
+from datetime import date
+import numpy as np
+import pandas as pd
+import holidays
+import warnings
+
+dates = pl.date_range(date(2020, 1, 1), date(2024, 1, 1), closed='left', eager=True)
+dates = dates.filter(dates.dt.weekday() < 6)
+size = 10_000_000
+input_dates = np.random.choice(dates, size)
+
+df = pl.DataFrame({
+    'ts': input_dates,
+})
+
+df_pd = pd.DataFrame({
+    'ts': input_dates,
+})
+"""
+
+def time_it(statement):
+    results = np.array(timeit.Timer(
+        stmt=statement,
+        setup=setup,
+        )
+        .repeat(7, 3)
+    )/3
+    return round(min(results), 3)
+
+if 1 in BENCHMARKS:
+    print('Polars-business: ', time_it("result_pl = df.select(pl.col('ts').business.advance_n_days(n=17))"))
+    print('NumPy: ', time_it("result_np = np.busday_offset(input_dates, 17)"))
+
+# uncomment, too slow...
+# print('pandas: ', time_it("result_pd = df_pd['ts'] + pd.tseries.offsets.BusinessDay(17)"))
+
+# BENCHMARK 2: WITH HOLIDAYS
+
+setup = """
+import polars as pl
+import polars_business
+from datetime import date
+import numpy as np
+import pandas as pd
+import holidays
+import warnings
+
+uk_holidays = list(holidays.country_holidays('UK', years=[2020, 2021, 2022, 2023]))
+
+dates = pl.date_range(date(2020, 1, 1), date(2024, 1, 1), closed='left', eager=True)
+dates = dates.filter(~dates.is_in(uk_holidays))
+dates = dates.filter(dates.dt.weekday() < 6)
+size = 10_000_000
+input_dates = np.random.choice(dates, size)
+
+df = pl.DataFrame({
+    'ts': input_dates,
+})
+
+df_pd = pd.DataFrame({
+    'ts': input_dates,
+})
+"""
+
+if 2 in BENCHMARKS:
+    print('Polars-business: ', time_it("result_pl = df.select(pl.col('ts').business.advance_n_days(n=17, holidays=uk_holidays))"))
+    print('NumPy: ', time_it("result_np = np.busday_offset(input_dates, 17, holidays=uk_holidays)"))
+
+# BENCHMARK 3: WITH weekends
+
+setup = """
+import polars as pl
+import polars_business
+from datetime import date
+import numpy as np
+import pandas as pd
+import holidays
+import warnings
+
+
+dates = pl.date_range(date(2020, 1, 1), date(2024, 1, 1), closed='left', eager=True)
+weekend = ['Fri', 'Sat']
+dates = dates.filter(~dates.dt.weekday().is_in([5, 6]))
+size = 10_000_000
+input_dates = np.random.choice(dates, size)
+
+df = pl.DataFrame({
+    'ts': input_dates,
+})
+
+df_pd = pd.DataFrame({
+    'ts': input_dates,
+})
+"""
+
+if 3 in BENCHMARKS:
+    print('Polars-business: ', time_it("result_pl = df.select(pl.col('ts').business.advance_n_days(n=17, weekend=weekend))"))
+    print('NumPy: ', time_it("result_np = np.busday_offset(input_dates, 17, weekmask='1111001')"))
+
+
+# BENCHMARK 4: WITH weekends and holidays
+
+setup = """
+import polars as pl
+import polars_business
+from datetime import date
+import numpy as np
+import pandas as pd
+import holidays
+import warnings
+
+uk_holidays = list(holidays.country_holidays('UK', years=[2020, 2021, 2022, 2023]))
+
+dates = pl.date_range(date(2020, 1, 1), date(2024, 1, 1), closed='left', eager=True)
+weekend = ['Fri', 'Sat']
+dates = dates.filter((~dates.dt.weekday().is_in([5, 6])) & (~dates.is_in(uk_holidays)))
+size = 10_000_000
+input_dates = np.random.choice(dates, size)
+
+df = pl.DataFrame({
+    'ts': input_dates,
+})
+
+df_pd = pd.DataFrame({
+    'ts': input_dates,
+})
+"""
+
+if 4 in BENCHMARKS:
+    print('Polars-business: ', time_it("result_pl = df.select(pl.col('ts').business.advance_n_days(n=17, weekend=weekend, holidays=uk_holidays))"))
+    print('NumPy: ', time_it("result_np = np.busday_offset(input_dates, 17, weekmask='1111001', holidays=uk_holidays)"))