Refactored Examples. Old examples are moved under old_examples folder (will be reworked or removed by Beta release). These do not need to be included in CI. Added new examples for illustration purposes on how these examples are used and referenced in the documantation. Note that I am still unable to get SDC working out of the box with @njit. All these examples will fail in default settings of SDC. SDC must be fixed, not examples

Author: samaid

examples/basic_workflow.py

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+# *****************************************************************************
+# Copyright (c) 2019, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+import pandas as pd
+from numba import njit
+
+# Dataset for analysis
+FNAME = "employees.csv"
+
+
+# This function gets compiled by Numba*
+@njit
+def get_analyzed_data():
+    df = pd.read_csv(FNAME)
+    s_bonus = pd.Series(df['Bonus %'])
+    s_first_name = pd.Series(df['First Name'])
+    m = s_bonus.mean()
+    names = s_first_name.sort_values()
+    return m, names
+
+
+# Printing names and their average bonus percent
+mean_bonus, sorted_first_names = get_analyzed_data()
+print(sorted_first_names)
+print('Average Bonus %:', mean_bonus)

examples/basic_workflow_parallel.py

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+# *****************************************************************************
+# Copyright (c) 2019, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+import pandas as pd
+from numba import njit
+
+# Dataset for analysis
+FNAME = "employees.csv"
+
+
+# This function gets compiled by Numba* and multi-threaded
+@njit(parallel=True)
+def get_analyzed_data():
+    df = pd.read_csv(FNAME)
+    s_bonus = pd.Series(df['Bonus %'])
+    s_first_name = pd.Series(df['First Name'])
+    m = s_bonus.mean()
+    names = s_first_name.sort_values()
+    return m, names
+
+
+# Printing names and their average bonus percent
+mean_bonus, sorted_first_names = get_analyzed_data()
+print(sorted_first_names)
+print('Average Bonus %:', mean_bonus)

examples/employees.csv

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+,Gender,First Name,Start Date,Last Login Time,Salary,Bonus %,Senior Management,Team
+0,Female,EMILY,2015-12-04,0 days 21:41:41.000000000,39582,1.306,,Business Development
+1,Male,NOAH,2011-02-02,0 days 00:04:19.000000000,124742,5.881,False,Client Services
+2,Male,ISAAC,1994-10-25,0 days 04:35:46.000000000,138462,14.995,True,Sales
+3,Male,,1998-12-24,0 days 18:35:33.000000000,60661,3.477,False,Business Development
+4,,CHRISTOPHER,2002-03-05,0 days 12:26:32.000000000,97764,15.65,False,
+5,Female,MIA,2005-01-20,0 days 17:47:44.000000000,42104,12.595,False,Product
+6,Female,OLIVIA,1994-07-13,0 days 00:43:25.000000000,46646,1.284,False,Client Services
+7,Male,ALEXANDER,2019-09-03,0 days 04:15:00.000000000,123807,17.849,True,Legal
+8,Male,JOSEPH,2008-09-15,0 days 01:16:05.000000000,139681,19.904,False,Engineering
+9,Male,JOSEPH,2009-06-11,0 days 20:27:06.000000000,71359,19.103,False,Client Services