Refactored the Python database script: separated functionality in modules, now complies to the PEP8 style, added proper command-line argument parsing, and cleaned-up

7 files changed, 389 insertions, 285 deletions

diff --git a/scripts/database/database.py b/scripts/database/database.py
index a70b9fc1..e115d68c 100644..100755
--- a/scripts/database/database.py
+++ b/scripts/database/database.py
@@ -1,326 +1,112 @@
 #!/usr/bin/env python
 
-# ==================================================================================================
-# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
-# project loosely follows the Google C++ styleguide and uses a max-width of 100 characters per line.
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
 #
 # Author(s):
 #   Cedric Nugteren <www.cedricnugteren.nl>
-#
-# ==================================================================================================
 
-# System modules
 import sys
 import os.path
 import glob
-import re
-import json
-try:
-	from urllib.request import urlopen # Python 3
-except ImportError:
-	from urllib2 import urlopen # Python 2
+import argparse
 
-# Additional modules
 import pandas as pd
-print("## Using pandas version "+pd.__version__+", requires at least 0.17.0")
+
+import database.io as io
+import database.db as db
+import database.clblast as clblast
+import database.bests as bests
+import database.defaults as defaults
 
 # Server storing a copy of the database
 DATABASE_SERVER_URL = "http://www.cedricnugteren.nl/tuning/clblast.db"
 
-# Constants
-VENDOR_DEFAULT = "default"
-DEVICETYPE_DEFAULT = "All"
-DEVICENAME_DEFAULT = "default"
-
-# Attributes
-DEVICETYPE_ATTRIBUTES = ["device_vendor", "device_type"]
-DEVICE_ATTRIBUTES = ["device", "device_core_clock", "device_compute_units"]
-KERNEL_ATTRIBUTES = ["precision", "kernel_family"]
-ARGUMENT_ATTRIBUTES = ["arg_m", "arg_n", "arg_k", "arg_alpha", "arg_beta"]
-ATTRIBUTES = DEVICE_ATTRIBUTES + DEVICETYPE_ATTRIBUTES + KERNEL_ATTRIBUTES + ARGUMENT_ATTRIBUTES
-
 # OpenCL vendor names and their short name
-VENDOR_NAMES = { "device_vendor": {
+VENDOR_TRANSLATION_TABLE = {"device_vendor": {
   "GenuineIntel": "Intel",
   "Intel(R) Corporation": "Intel",
   "Advanced Micro Devices, Inc.": "AMD",
   "NVIDIA Corporation": "NVIDIA",
 }}
 
-# Pandas options
-pd.set_option('display.width', 1000)
-
-# ==================================================================================================
-# Database operations
-# ==================================================================================================
-
-# Downloads the database and save it to disk
-def DownloadDatabase(filename):
-	print("## Downloading database from '"+DATABASE_SERVER_URL+"'...")
-	df = urlopen(DATABASE_SERVER_URL)
-	output = open(file_db,'wb')
-	output.write(df.read())
-	output.close()
-
-# Loads the database from disk
-def LoadDatabase(filename):
-	return pd.read_pickle(filename)
-
-# Saves the database to disk
-def SaveDatabase(df, filename):
-	df.to_pickle(filename)
-
-# Loads JSON data from file
-def ImportDataFromFile(filename):
-	with open(filename) as f:
-		data = json.load(f)
-	json_data = pd.DataFrame(data)
-	df = pd.io.json.json_normalize(json_data["results"])
-	for attribute in ATTRIBUTES:
-		if attribute == "kernel_family":
-			df[attribute] = re.sub(r'_\d+', '', data[attribute])
-		elif attribute in data:
-			df[attribute] = data[attribute]
-		else:
-			df[attribute] = 0
-	return df
-
-# Returns the row-wise concatenation of two dataframes
-def ConcatenateData(df1, df2):
-	return pd.concat([df1, df2])
-
-# Removes duplicates from a dataframe
-def RemoveDuplicates(df):
-	return df.drop_duplicates()
-
-# database = database[(database["device"] != "AMD Radeon R9 M370X Compute Engine") | (database["kernel_family"] != "xgemm") | (database["precision"] != "32")]
-def RemoveEntriesByDevice(df, devicename):
-	return df[df["device"] != devicename]
-
-def RemoveEntriesByKernelFamily(df, familyname):
-	return df[df["kernel_family"] != familyname]
-
-def GetEntriesByField(df, field, value):
-	return df[df[field] == value]
-
-# Example usage:
-# df = UpdateDatabase(df, (df["kernel_family"] == "xdot") & (df["arg_n"] == "67108864"), "arg_n", "2097152")
-def UpdateDatabase(df, condition, field, value):
-	df.loc[condition, field] = value
-	return df
-
-# Fixes the problem that some vendors use multiple different names
-def SanitizeVendorNames(df):
-	df = df.replace(VENDOR_NAMES)
-	return df
-
-# Retrieves the results with the lowest execution times
-def GetBestResults(df):
-	dfbest = pd.DataFrame()
-	grouped = df.groupby(ATTRIBUTES+["kernel"])
-	for name, dfgroup in grouped:
-		besttime = dfgroup["time"].min()
-		bestcase = dfgroup[dfgroup["time"] == besttime].iloc[0]
-		dfbest = dfbest.append(bestcase, ignore_index=True)
-	return dfbest
-
-# Sets defaults for devices of the same type/vendor based on the smallest values of all know
-# entries. The average might be better for performance but some parameters might not be supported
-# on other devices.
-def CalculateDefaults(df):
-	dfdefault = pd.DataFrame()
-
-	# Defaults per type/vendor
-	groups = df.groupby(DEVICETYPE_ATTRIBUTES+KERNEL_ATTRIBUTES+ARGUMENT_ATTRIBUTES+["kernel"])
-	for name, dfgroup in groups:
-		default_values = dfgroup.min(axis=0)
-		default_values["device"] = DEVICENAME_DEFAULT
-		default_values["device_compute_units"] = 0
-		default_values["device_core_clock"] = 0
-		default_values["time"] = 0.0
-		dfdefault = dfdefault.append(default_values, ignore_index=True)
-	
-	# Checks for mis-matched arguments
-	groups = dfdefault.groupby(DEVICETYPE_ATTRIBUTES+KERNEL_ATTRIBUTES+["kernel"])
-	for name, dfgroup in groups:
-		if len(dfgroup) != 1:
-			description = dfgroup["kernel"].min() + " " + dfgroup["device_vendor"].min()
-			print("[WARNING] Entries for a single kernel with multiple argument values: " + description)
-			
-	# Defaults in general
-	groups = df.groupby(KERNEL_ATTRIBUTES+ARGUMENT_ATTRIBUTES+["kernel"])
-	for name, dfgroup in groups:
-		default_values = dfgroup.min(axis=0)
-		default_values["device_vendor"] = VENDOR_DEFAULT
-		default_values["device_type"] = DEVICETYPE_DEFAULT
-		default_values["device"] = DEVICENAME_DEFAULT
-		default_values["device_compute_units"] = 0
-		default_values["device_core_clock"] = 0
-		default_values["time"] = 0.0
-		dfdefault = dfdefault.append(default_values, ignore_index=True)
-	
-	# Database with both types of defaults only
-	return dfdefault
-
-# ==================================================================================================
-# C++ header generation
-# ==================================================================================================
-
-# The C++ header
-def GetHeader(family):
-	return("""
-// =================================================================================================
-// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
-// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
-// width of 100 characters per line.
-//
-// Author(s):
-//   Database generator <database.py>
-//
-// This file populates the database with best-found tuning parameters for the '%s' kernels.
-//
-// =================================================================================================
-
-namespace clblast {
-// ================================================================================================="""
-	% family.title())
-
-# The C++ footer
-def GetFooter():
-	return("\n} // namespace clblast\n")
-
-# The start of a new C++ precision entry
-def GetPrecision(family, precision):
-	precisionstring = ""
-	if precision == "16":
-		precisionstring = "Half"
-	elif precision == "32":
-		precisionstring = "Single"
-	elif precision == "64":
-		precisionstring = "Double"
-	elif precision == "3232":
-		precisionstring = "ComplexSingle"
-	elif precision == "6464":
-		precisionstring = "ComplexDouble"
-	else:
-		print("[ERROR] Unknown precision")
-		sys.exit()
-	return("\n\nconst Database::DatabaseEntry Database::%s%s = {\n  \"%s\", Precision::k%s, {\n"
-	       % (family.title(), precisionstring, family.title(), precisionstring))
-
-# The C++ device type and vendor
-def GetDeviceVendor(vendor, devtype):
-	if vendor == VENDOR_DEFAULT and devtype == DEVICETYPE_DEFAULT:
-		return("    { // Default\n      kDeviceType%s, \"%s\", {\n" % (devtype, vendor))
-	return("    { // %s %ss\n      kDeviceType%s, \"%s\", {\n" % (vendor, devtype, devtype[0].upper() + devtype[1:], vendor))
-
-# Prints the data to a C++ database
-def PrintData(df, outputdir):
-
-	# Iterates over the kernel families: creates a new file per family
-	for family, dffamily in df.groupby(["kernel_family"]):
-		dffamily = dffamily.dropna(axis=1, how='all')
-		f = open(os.path.join(outputdir, family+'.hpp'), 'w+')
-		f.write(GetHeader(family))
-
-		# Loops over the different entries for this family and prints their headers
-		for precision, dfprecision in dffamily.groupby(["precision"]):
-			f.write(GetPrecision(family, precision))
-			for vendor, dfvendor in dfprecision.groupby(["device_vendor"]):
-				for devtype, dfdevtype in dfvendor.groupby(["device_type"]):
-					f.write(GetDeviceVendor(vendor, devtype))
-					for device, dfdevice in dfdevtype.groupby(["device"]):
-						devicename = "\"%s\"," % device
-						f.write("        { %-50s { " % devicename)
 
-						# Collects the paramaters for this case and prints them
-						parameters = []
-						for kernel, dfkernel in dfdevice.groupby(["kernel"]):
-							dfkernel = dfkernel.dropna(axis=1)
-							col_names = [col for col in list(dfkernel) if col.startswith('parameters.') and col != "parameters.PRECISION"]
-							parameters += ["{\"%s\",%d}" % (p.replace("parameters.",""), dfkernel[p].iloc[0]) for p in col_names]
-						f.write(", ".join(parameters))
-						f.write(" } },\n")
+def main(argv):
 
-					# Prints the footers
-					f.write("      }\n    },\n")
-			f.write("  }\n};\n\n// =================================================================================================")
-		f.write(GetFooter())
+    # Parses the command-line arguments
+    parser = argparse.ArgumentParser()
+    parser.add_argument("source_folder", help="The folder with JSON files to parse to add to the database")
+    parser.add_argument("clblast_root", help="Root of the CLBlast sources")
+    parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script")
+    cl_args = parser.parse_args(argv)
 
-# ==================================================================================================
-# Command-line arguments parsing and verification
-# ==================================================================================================
+    # Parses the path arguments
+    database_filename = os.path.join(cl_args.clblast_root, "scripts", "database", "database.db")
+    json_files = os.path.join(cl_args.source_folder, "*.json")
+    cpp_database_path = os.path.join(cl_args.clblast_root, "src", "database", "kernels")
 
-# Checks for the number of command-line arguments
-if len(sys.argv) != 3:
-	print("[ERROR] Usage: database.py <folder_with_json_files> <root_of_clblast>")
-	sys.exit()
+    # Checks whether the command-line arguments are valid
+    clblast_header = os.path.join(cl_args.clblast_root, "include", "clblast.h")  # Not used but just for validation
+    if not os.path.isfile(clblast_header):
+        raise RuntimeError("The path '" + cl_args.clblast_root + "' does not point to the root of the CLBlast library")
+    if len(glob.glob(json_files)) < 1:
+        print("[database] The path '" + cl_args.source_folder + "' does not contain any JSON files")
 
-# Parses the command-line arguments
-path_json = sys.argv[1]
-path_clblast = sys.argv[2]
-file_db = os.path.join(path_clblast, "scripts", "database", "database.db")
-glob_json = os.path.join(path_json, "*.json")
+    # Pandas options
+    pd.set_option('display.width', 1000)
+    if cl_args.verbose:
+        print("[database] Using pandas version " + pd.__version__)
 
-# Checks whether the command-line arguments are valid; exists otherwise
-clblast_h = os.path.join(path_clblast, "include", "clblast.h") # Not used but just for validation
-if not os.path.isfile(clblast_h):
-	print("[ERROR] The path '"+path_clblast+"' does not point to the root of the CLBlast library")
-	sys.exit()
-if len(glob.glob(glob_json)) < 1:
-	print("## The path '"+path_json+"' does not contain any JSON files")
+    # Downloads the database if a local copy is not present
+    if not os.path.isfile(database_filename):
+        io.download_database(database_filename, DATABASE_SERVER_URL)
 
-# ==================================================================================================
-# The main body of the script
-# ==================================================================================================
+    # Loads the database from disk
+    database = io.load_database(database_filename)
 
-# Downloads the database if a local copy is not present
-db_exists = os.path.isfile(file_db)
-if not db_exists:
-	DownloadDatabase(file_db)
+    # Loops over all JSON files in the supplied folder
+    for file_json in glob.glob(json_files):
 
-# Loads the database from disk
-print("## Loading the database from disk...")
-database = LoadDatabase(file_db)
+        # Loads the newly imported data
+        sys.stdout.write("[database] Processing '"+file_json+"' ")  # No newline printed
+        imported_data = io.load_json_to_pandas(file_json)
 
-# Loops over all JSON files in the supplied folder
-for file_json in glob.glob(glob_json):
+        # Fixes the problem that some vendors use multiple different names
+        imported_data = db.find_and_replace(imported_data, VENDOR_TRANSLATION_TABLE)
 
-	# Loads the newly imported data
-	sys.stdout.write("## Processing '"+file_json+"' ")
-	imported_data = ImportDataFromFile(file_json)
-	imported_data = SanitizeVendorNames(imported_data)
+        # Adds the new data to the database
+        old_size = len(database.index)
+        database = db.concatenate_database(database, imported_data)
+        database = db.remove_duplicates(database)
+        new_size = len(database.index)
+        print("with " + str(new_size - old_size) + " new items")  # Newline printed here
 
-	# Adds the new data to the database
-	old_size = len(database.index)
-	database = ConcatenateData(database, imported_data)
-	database = RemoveDuplicates(database)
-	new_size = len(database.index)
-	print("with "+str(new_size-old_size)+" new items")
+    # Stores the modified database back to disk
+    if len(glob.glob(json_files)) >= 1:
+        io.save_database(database, database_filename)
 
-# Stores the modified database back to disk
-if len(glob.glob(glob_json)) >= 1:
-	print("## Storing the database to disk...")
-	SaveDatabase(database, file_db)
+    # Optional: update the database here. Default is disabled, code below is just an example
+    if False:  # TODO: Use command-line arguments to enable updates in a flexible way
+        database = db.update_database(database,
+                                      ((database["kernel"] == "CopyMatrixFast") &
+                                       (database["precision"] == "3232")),
+                                      "arg_alpha", "2+0.5i")
+        io.save_database(database, database_filename)
 
-# Optional: update the database here. Default is disabled, code below is just an example
-if False:
-	database = UpdateDatabase(database, ((database["kernel"] == "CopyMatrixFast") & (database["precision"] == "3232")), "arg_alpha", "2+0.5i")
-	SaveDatabase(database, file_db)
+    # Retrieves the best performing results
+    print("[database] Calculating the best results per device/kernel...")
+    database_best_results = bests.get_best_results(database)
 
-# Retrieves the best performing results
-print("## Calculating the best results per device/kernel...")
-bests = GetBestResults(database)
+    # Determines the defaults for other vendors and per vendor
+    database_defaults = defaults.calculate_defaults(database_best_results)
+    database_best_results = db.concatenate_database(database_best_results, database_defaults)
 
-# Determines the defaults for other vendors and per vendor
-defaults = CalculateDefaults(bests)
-bests = ConcatenateData(bests, defaults)
+    # Outputs the database as a C++ database
+    print("[database] Producing a C++ database in '" + cpp_database_path + "'...")
+    clblast.print_cpp_database(database_best_results, cpp_database_path)
 
-# Outputs the data as a C++ database
-path_cpp_database = os.path.join(path_clblast, "src", "database", "kernels")
-print("## Producing a C++ database in '"+path_cpp_database+"'...")
-PrintData(bests, path_cpp_database)
+    print("[database] All done")
 
-print("## All done")
 
-# ==================================================================================================
+if __name__ == '__main__':
+    main(sys.argv[1:])
diff --git a/scripts/database/database/__init__.py b/scripts/database/database/__init__.py
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/scripts/database/database/__init__.py
diff --git a/scripts/database/database/bests.py b/scripts/database/database/bests.py
new file mode 100644
index 00000000..edb81733
--- /dev/null
+++ b/scripts/database/database/bests.py
@@ -0,0 +1,20 @@
+
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
+#
+# Author(s):
+#   Cedric Nugteren <www.cedricnugteren.nl>
+
+import pandas as pd
+import clblast
+
+
+def get_best_results(df):
+    """Retrieves the results with the lowests execution times"""
+    database_bests = pd.DataFrame()
+    database_entries = df.groupby(clblast.ATTRIBUTES + ["kernel"])
+    for name, database_entry in database_entries:
+        best_time = database_entry["time"].min()
+        best_parameters = database_entry[database_entry["time"] == best_time].iloc[0]
+        database_bests = database_bests.append(best_parameters, ignore_index=True)
+    return database_bests
diff --git a/scripts/database/database/clblast.py b/scripts/database/database/clblast.py
new file mode 100644
index 00000000..9c9f7eb4
--- /dev/null
+++ b/scripts/database/database/clblast.py
@@ -0,0 +1,132 @@
+
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
+#
+# Author(s):
+#   Cedric Nugteren <www.cedricnugteren.nl>
+
+import os
+
+# Constants from the C++ code
+VENDOR_DEFAULT = "default"
+DEVICE_TYPE_DEFAULT = "All"
+DEVICE_NAME_DEFAULT = "default"
+
+# List of attributes
+DEVICE_TYPE_ATTRIBUTES = ["device_vendor", "device_type"]
+DEVICE_ATTRIBUTES = ["device", "device_core_clock", "device_compute_units"]
+KERNEL_ATTRIBUTES = ["precision", "kernel_family"]
+ARGUMENT_ATTRIBUTES = ["arg_m", "arg_n", "arg_k", "arg_alpha", "arg_beta"]
+ATTRIBUTES = DEVICE_ATTRIBUTES + DEVICE_TYPE_ATTRIBUTES + KERNEL_ATTRIBUTES + ARGUMENT_ATTRIBUTES
+
+
+def precision_to_string(precision):
+    """Translates a precision number (represented as Python string) into a descriptive string"""
+    if precision == "16":
+        return "Half"
+    elif precision == "32":
+        return "Single"
+    elif precision == "64":
+        return "Double"
+    elif precision == "3232":
+        return "ComplexSingle"
+    elif precision == "6464":
+        return "ComplexDouble"
+    else:
+        raise("Unknown precision: " + precision)
+
+
+def get_cpp_separator():
+    """Retrieves a C++ comment separator"""
+    return "// ================================================================================================="
+
+
+def get_cpp_header(family):
+    """Retrieves the C++ header"""
+    return ("\n" + get_cpp_separator() + """
+// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
+// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
+// width of 100 characters per line.
+//
+// Author(s):
+//   Database generator <database.py>
+//
+// This file populates the database with best-found tuning parameters for the '%s' kernels.
+//\n"""
+            % family.title() + get_cpp_separator() + "\n\nnamespace clblast {\n" + get_cpp_separator())
+
+
+def get_cpp_footer():
+    """Retrieves the C++ footer"""
+    return "\n} // namespace clblast\n"
+
+
+def get_cpp_precision(family, precision):
+    """Retrieves the C++ code for the start of a new precision"""
+    precision_string = precision_to_string(precision)
+    return("\n\nconst Database::DatabaseEntry Database::%s%s = {\n  \"%s\", Precision::k%s, {\n"
+           % (family.title(), precision_string, family.title(), precision_string))
+
+
+def get_cpp_device_vendor(vendor, device_type):
+    """Retrieves the C++ code for the (default) vendor and device type"""
+    if vendor == VENDOR_DEFAULT and device_type == DEVICE_TYPE_DEFAULT:
+        return "    { // Default\n      kDeviceType%s, \"%s\", {\n" % (device_type, vendor)
+    device_type_caps = device_type[0].upper() + device_type[1:]
+    return "    { // %s %ss\n      kDeviceType%s, \"%s\", {\n" % (vendor, device_type, device_type_caps, vendor)
+
+
+def print_cpp_database(database, output_dir):
+    """Outputs the database as C++ code"""
+
+    # Iterates over the kernel families
+    for family_name, family_database in database.groupby(["kernel_family"]):
+        family_database = family_database.dropna(axis=1, how='all')
+
+        # Opens a new file for each kernel family
+        full_path = os.path.join(output_dir, family_name+'.hpp')
+        with open(full_path, 'w+') as f:
+            f.write(get_cpp_header(family_name))
+
+            # Loops over the different precision (e.g. 16, 32, 3232, 64, 6464)
+            for precision, precision_database in family_database.groupby(["precision"]):
+                f.write(get_cpp_precision(family_name, precision))
+
+                # Loops over a combination of device vendors and device types (e.g. AMD GPU)
+                for vendor, vendor_database in precision_database.groupby(["device_vendor"]):
+                    for device_type, device_type_database in vendor_database.groupby(["device_type"]):
+                        f.write(get_cpp_device_vendor(vendor, device_type))
+
+                        # Loops over every device of this vendor-type combination
+                        for device_name, device_database in device_type_database.groupby(["device"]):
+                            device_name_quoted = "\"%s\"," % device_name
+                            device_name_cpp = "        { %-50s { " % device_name_quoted
+                            f.write(device_name_cpp)
+
+                            # Collects the parameters for this entry
+                            parameters = []
+                            for kernel, kernel_database in device_database.groupby(["kernel"]):
+                                kernel_database = kernel_database.dropna(axis=1)
+
+                                # Only consider the actual parameters, not the precision
+                                def is_parameter(column):
+                                    return column.startswith('parameters.') and column != "parameters.PRECISION"
+                                column_names = [col for col in list(kernel_database) if is_parameter(col)]
+
+                                for p in column_names:
+                                    parameter_name = p.replace("parameters.", "")
+                                    parameter_value = int(kernel_database[p].iloc[0])
+                                    parameters.append("{\"" + parameter_name + "\"," + str(parameter_value) + "}")
+
+                            # Prints the entry
+                            f.write(", ".join(parameters))
+                            f.write(" } },\n")
+
+                        # Prints the vendor-type combination footer
+                        f.write("      }\n    },\n")
+
+                # Prints the precision footer
+                f.write("  }\n};\n\n" + get_cpp_separator())
+
+            # Prints the file footer
+            f.write(get_cpp_footer())
diff --git a/scripts/database/database/db.py b/scripts/database/database/db.py
new file mode 100644
index 00000000..60cfbcfa
--- /dev/null
+++ b/scripts/database/database/db.py
@@ -0,0 +1,50 @@
+
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
+#
+# Author(s):
+#   Cedric Nugteren <www.cedricnugteren.nl>
+
+import pandas as pd
+
+
+def get_entries_by_field(database, field, value):
+    """Retrieves entries from the database with a specific value for a given field"""
+    return database[database[field] == value]
+
+
+def concatenate_database(database1, database2):
+    """Concatenates two databases row-wise and returns the result"""
+    return pd.concat([database1, database2])
+
+
+def remove_duplicates(database):
+    """Removes duplicates from a database"""
+    return database.drop_duplicates()
+
+
+def find_and_replace(database, dictionary):
+    """Finds and replaces entries in a database based on a dictionary. Example:
+    dictionary = { "key_to_edit": { find1: replace1, find2, replace2 } }"""
+    return database.replace(dictionary)
+
+
+def remove_entries_by_key_value(database, key, value):
+    """Removes entries in the databased which have a specific value for a given key"""
+    return database[database[key] != value]
+
+
+def remove_entries_by_device(database, device_name):
+    """Shorthand for the above, specifically removes entries for a given device"""
+    return remove_entries_by_key_value(database, "device", device_name)
+
+
+def remove_entries_by_kernel_family(database, kernel_family_name):
+    """Shorthand for the above, specifically removes entries for a given kernel family"""
+    return remove_entries_by_key_value(database, "kernel_family", kernel_family_name)
+
+
+def update_database(database, condition, field, value):
+    """Updates the database by writing a specific value to a given field, given certain conditions"""
+    database.loc[condition, field] = value
+    return database
diff --git a/scripts/database/database/defaults.py b/scripts/database/database/defaults.py
new file mode 100644
index 00000000..357c3a3a
--- /dev/null
+++ b/scripts/database/database/defaults.py
@@ -0,0 +1,58 @@
+
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
+#
+# Author(s):
+#   Cedric Nugteren <www.cedricnugteren.nl>
+
+import pandas as pd
+import clblast
+
+
+def set_default_device(database_entry):
+    """Sets the device name and parameters to some default values"""
+    database_entry["device"] = clblast.DEVICE_NAME_DEFAULT
+    database_entry["device_compute_units"] = 0
+    database_entry["device_core_clock"] = 0
+    return database_entry
+
+
+def set_default_time(database_entry):
+    """Sets the execution time to some default value"""
+    database_entry["time"] = 0.0
+    return database_entry
+
+
+def calculate_defaults(df):
+    """# Sets defaults for devices of the same type/vendor based on the smallest values of all known entries. The average
+    might be better for performance but some parameters might not be supported on other devices."""
+    database_defaults = pd.DataFrame()
+
+    # Defaults per combination of device vendors and device types (e.g. AMD GPU)
+    database_type_vendor = df.groupby(clblast.DEVICE_TYPE_ATTRIBUTES + clblast.KERNEL_ATTRIBUTES + ["kernel"] +
+                                      clblast.ARGUMENT_ATTRIBUTES)
+    for group_name, database_group in database_type_vendor:
+        default_values = database_group.min(axis=0)
+        default_values = set_default_device(default_values)
+        default_values = set_default_time(default_values)
+        database_defaults = database_defaults.append(default_values, ignore_index=True)
+
+    # Checks for mis-matched arguments
+    groups = database_defaults.groupby(clblast.DEVICE_TYPE_ATTRIBUTES + clblast.KERNEL_ATTRIBUTES + ["kernel"])
+    for group_name, database_group in groups:
+        if len(database_group) != 1:
+            description = database_group["kernel"].min() + " " + database_group["device_vendor"].min()
+            print("[WARNING] Entries for a single kernel with multiple argument values: " + description)
+
+    # Defaults over all device types and vendors
+    groups = df.groupby(clblast.KERNEL_ATTRIBUTES + ["kernel"] + clblast.ARGUMENT_ATTRIBUTES)
+    for group_name, database_group in groups:
+        default_values = database_group.min(axis=0)
+        default_values["device_vendor"] = clblast.VENDOR_DEFAULT
+        default_values["device_type"] = clblast.DEVICE_TYPE_DEFAULT
+        default_values = set_default_device(default_values)
+        default_values = set_default_time(default_values)
+        database_defaults = database_defaults.append(default_values, ignore_index=True)
+
+    # Database with both types of defaults only
+    return database_defaults
diff --git a/scripts/database/database/io.py b/scripts/database/database/io.py
new file mode 100644
index 00000000..ad2f7ae9
--- /dev/null
+++ b/scripts/database/database/io.py
@@ -0,0 +1,58 @@
+
+# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
+# PEP8 Python style guide and uses a max-width of 120 characters per line.
+#
+# Author(s):
+#   Cedric Nugteren <www.cedricnugteren.nl>
+
+import re
+import json
+
+try:
+    from urllib.request import urlopen  # Python 3
+except ImportError:
+    from urllib2 import urlopen  # Python 2
+
+import pandas as pd
+
+import clblast
+
+
+def download_database(filename, database_url):
+    """Downloads a database and saves it to disk"""
+    print("[database] Downloading database from '" + database_url + "'...")
+    database = urlopen(database_url)
+    with open(filename, 'wb') as f:
+        f.write(database.read())
+
+
+def load_database(filename):
+    """Loads a database from disk"""
+    print("[database] Loading database from '" + filename + "'")
+    return pd.read_pickle(filename)
+
+
+def save_database(database, filename):
+    """Saves a database to disk"""
+    print("[database] Saving database to '" + filename + "'")
+    database.to_pickle(filename)
+
+
+def load_json_to_pandas(filename):
+    """Loads JSON data from file and converts it to a pandas database"""
+    with open(filename) as f:
+        json_data = json.load(f)
+
+    # Gathers all results and stores them in a new database
+    json_database = pd.DataFrame(json_data)
+    new_database = pd.io.json.json_normalize(json_database["results"])
+
+    # Sets the common attributes to each entry in the results
+    for attribute in clblast.ATTRIBUTES:
+        if attribute == "kernel_family":
+            new_database[attribute] = re.sub(r'_\d+', '', json_data[attribute])
+        elif attribute in json_data:
+            new_database[attribute] = json_data[attribute]
+        else:
+            new_database[attribute] = 0  # For example a parameters that was not used by this kernel
+    return new_database