Code Duplication - nicolargo/glances - Measure and Improve Code Quality continuously with Scrutinizer

Code Duplication Length = 51-52 lines in 2 locations

glances/exports/glances_influxdb.py 1 location



        return db

    def _normalize(self, name, columns, points):
        """Normalize data for the InfluxDB's data model.
        Output is a list of measurements."""
        ret = []

        # Build initial dict by crossing columns and point
        data_dict = dict(zip(columns, points))

        # issue1871 - Check if a key exist. If a key exist, the value of
        # the key should be used as a tag to identify the measurement.
        keys_list = [k.split('.')[0] for k in columns if k.endswith('.key')]
        if len(keys_list) == 0:
            keys_list = [None]

        for measurement in keys_list:
            # Manage field
            if measurement is not None:
                fields = {k.replace('{}.'.format(measurement), ''): data_dict[k]
                          for k in data_dict
                          if k.startswith('{}.'.format(measurement))}
            else:
                fields = data_dict
            # Transform to InfluxDB datamodel
            # https://docs.influxdata.com/influxdb/v1.8/write_protocols/line_protocol_reference/
            for k in fields:
                #  Do not export empty (None) value
                if fields[k] is None:
                    fields.pop(k)
                # Convert numerical to float
                try:
                    fields[k] = float(fields[k])
                except (TypeError, ValueError):
                    # Convert others to string
                    try:
                        fields[k] = str(fields[k])
                    except (TypeError, ValueError):
                        pass
            # Manage tags
            tags = self.parse_tags(self.tags)
            if 'key' in fields and fields['key'] in fields:
                # Create a tag from the key
                # Tag should be an string (see InfluxDB data model)
                tags[fields['key']] = str(fields[fields['key']])
                # Remove it from the field list (can not be a field and a tag)
                fields.pop(fields['key'])
            # Add the hostname as a tag
            tags['hostname'] = self.hostname
            # Add the measurement to the list
            ret.append({'measurement': name,
                        'tags': tags,
                        'fields': fields})
        return ret

    def export(self, name, columns, points):
        """Write the points to the InfluxDB server."""

glances/exports/glances_influxdb2.py 1 location


                                                                   exponential_base=2))
        return write_client

    def _normalize(self, name, columns, points):
        """Normalize data for the InfluxDB's data model."""
        ret = []

        # Build initial dict by crossing columns and point
        data_dict = dict(zip(columns, points))

        # issue1871 - Check if a key exist. If a key exist, the value of
        # the key should be used as a tag to identify the measurement.
        keys_list = [k.split('.')[0] for k in columns if k.endswith('.key')]
        if len(keys_list) == 0:
            keys_list = [None]

        for measurement in keys_list:
            # Manage field
            if measurement is not None:
                fields = {k.replace('{}.'.format(measurement), ''): data_dict[k]
                          for k in data_dict
                          if k.startswith('{}.'.format(measurement))}
            else:
                fields = data_dict
            # Transform to InfluxDB datamodel
            # https://docs.influxdata.com/influxdb/v2.0/reference/syntax/line-protocol/
            for k in fields:
                #  Do not export empty (None) value
                if fields[k] is None:
                    fields.pop(k)
                # Convert numerical to float
                try:
                    fields[k] = float(fields[k])
                except (TypeError, ValueError):
                    # Convert others to string
                    try:
                        fields[k] = str(fields[k])
                    except (TypeError, ValueError):
                        pass
            # Manage tags
            tags = self.parse_tags(self.tags)
            if 'key' in fields and fields['key'] in fields:
                # Create a tag from the key
                # Tag should be an string (see InfluxDB data model)
                tags[fields['key']] = str(fields[fields['key']])
                # Remove it from the field list (can not be a field and a tag)
                fields.pop(fields['key'])
            # Add the hostname as a tag
            tags['hostname'] = self.hostname
            # Add the measurement to the list
            ret.append({'measurement': name,
                        'tags': tags,
                        'fields': fields})
        return ret

    def export(self, name, columns, points):
        """Write the points to the InfluxDB server."""

		@@ 99-150 (lines=52) @@
96
97		return db
98
99		def _normalize(self, name, columns, points):
100		"""Normalize data for the InfluxDB's data model.
101		Output is a list of measurements."""
102		ret = []
103
104		# Build initial dict by crossing columns and point
105		data_dict = dict(zip(columns, points))
106
107		# issue1871 - Check if a key exist. If a key exist, the value of
108		# the key should be used as a tag to identify the measurement.
109		keys_list = [k.split('.')[0] for k in columns if k.endswith('.key')]
110		if len(keys_list) == 0:
111		keys_list = [None]
112
113		for measurement in keys_list:
114		# Manage field
115		if measurement is not None:
116		fields = {k.replace('{}.'.format(measurement), ''): data_dict[k]
117		for k in data_dict
118		if k.startswith('{}.'.format(measurement))}
119		else:
120		fields = data_dict
121		# Transform to InfluxDB datamodel
122		# https://docs.influxdata.com/influxdb/v1.8/write_protocols/line_protocol_reference/
123		for k in fields:
124		# Do not export empty (None) value
125		if fields[k] is None:
126		fields.pop(k)
127		# Convert numerical to float
128		try:
129		fields[k] = float(fields[k])
130		except (TypeError, ValueError):
131		# Convert others to string
132		try:
133		fields[k] = str(fields[k])
134		except (TypeError, ValueError):
135		pass
136		# Manage tags
137		tags = self.parse_tags(self.tags)
138		if 'key' in fields and fields['key'] in fields:
139		# Create a tag from the key
140		# Tag should be an string (see InfluxDB data model)
141		tags[fields['key']] = str(fields[fields['key']])
142		# Remove it from the field list (can not be a field and a tag)
143		fields.pop(fields['key'])
144		# Add the hostname as a tag
145		tags['hostname'] = self.hostname
146		# Add the measurement to the list
147		ret.append({'measurement': name,
148		'tags': tags,
149		'fields': fields})
150		return ret
151
152		def export(self, name, columns, points):
153		"""Write the points to the InfluxDB server."""

		@@ 89-139 (lines=51) @@
86		exponential_base=2))
87		return write_client
88
89		def _normalize(self, name, columns, points):
90		"""Normalize data for the InfluxDB's data model."""
91		ret = []
92
93		# Build initial dict by crossing columns and point
94		data_dict = dict(zip(columns, points))
95
96		# issue1871 - Check if a key exist. If a key exist, the value of
97		# the key should be used as a tag to identify the measurement.
98		keys_list = [k.split('.')[0] for k in columns if k.endswith('.key')]
99		if len(keys_list) == 0:
100		keys_list = [None]
101
102		for measurement in keys_list:
103		# Manage field
104		if measurement is not None:
105		fields = {k.replace('{}.'.format(measurement), ''): data_dict[k]
106		for k in data_dict
107		if k.startswith('{}.'.format(measurement))}
108		else:
109		fields = data_dict
110		# Transform to InfluxDB datamodel
111		# https://docs.influxdata.com/influxdb/v2.0/reference/syntax/line-protocol/
112		for k in fields:
113		# Do not export empty (None) value
114		if fields[k] is None:
115		fields.pop(k)
116		# Convert numerical to float
117		try:
118		fields[k] = float(fields[k])
119		except (TypeError, ValueError):
120		# Convert others to string
121		try:
122		fields[k] = str(fields[k])
123		except (TypeError, ValueError):
124		pass
125		# Manage tags
126		tags = self.parse_tags(self.tags)
127		if 'key' in fields and fields['key'] in fields:
128		# Create a tag from the key
129		# Tag should be an string (see InfluxDB data model)
130		tags[fields['key']] = str(fields[fields['key']])
131		# Remove it from the field list (can not be a field and a tag)
132		fields.pop(fields['key'])
133		# Add the hostname as a tag
134		tags['hostname'] = self.hostname
135		# Add the measurement to the list
136		ret.append({'measurement': name,
137		'tags': tags,
138		'fields': fields})
139		return ret
140
141		def export(self, name, columns, points):
142		"""Write the points to the InfluxDB server."""

nicolargo / glances

Code Duplication Length = 51-52 lines in 2 locations

glances/exports/glances_influxdb.py 1 location

glances/exports/glances_influxdb2.py 1 location