Merge pull request #54 from gisce/new_quarter_hourly_files_magclqh

Nuevo fichero de medidas MAGCLQH para agregaciones de Tipo 4, y 5

README.md

@@ -48,6 +48,8 @@
 - `F3`
 - `F5`
 - `F5D`
+- `MAGCL`
+- `MAGCLQH`
 - `MCIL345`
 - `MCIL345QH`
 - `MEDIDAS`

mesures/headers.py

@@ -313,6 +313,30 @@
     'factura'       # str
 ]
 
+MAGCL_HEADER = [
+    'distribuidora',        # str(4)
+    'comercialitzadora',    # str(4)
+    'agree_tensio',         # str(2)
+    'agree_tarifa',         # str(2)
+    'agree_dh',             # str(2)
+    'agree_tipo',           # str(2)
+    'provincia',            # str(2)
+    'tipus_demanda',        # str(2)
+    'timestamp',            # str(aaaa/mm/dd hh:mm)
+    'estacio',              # str(1) in ('0' for winter, '1' for summer)
+    'magnitud',             # str(2)
+    'consum',               # int(10)
+    'n_punts',              # int(7)
+    'm_iec_real',           # int(10)
+    'n_iec_real',           # int(7)
+    'm_iec_estimada',       # int(10)
+    'n_iec_estimada',       # int(7)
+    'm_integrats_real',     # int(10)
+    'n_integrats_real',     # int(7)
+    'm_integrats_estimada', # int(10)
+    'n_integrats_estimada'  # int(7)
+]
+
 MCIL345_HEADER = [
     'cil',                  # str(25) CUPS + 3 digits ('001' style)
     'timestamp',            # str(aaaa/mm/dd hh)

mesures/magcl.py

@@ -0,0 +1,116 @@
+# -*- coding: utf-8 -*-
+from mesures.dates import *
+from mesures.headers import MAGCL_HEADER as COLUMNS
+from mesures.parsers.dummy_data import DummyCurve
+from mesures.utils import check_line_terminator_param
+import os
+import pandas as pd
+
+
+class MAGCL(object):
+    def __init__(self, data, distributor=None, compression='bz2', columns=COLUMNS, version=0):
+        """
+        :param data: list of dicts or absolute file_path
+        :param distributor: str distributor REE code
+        :param compression: 'bz2', 'gz'... OR False otherwise
+        """
+        if isinstance(data, list):
+            data = DummyCurve(data).curve_data
+        self.columns = columns
+        self.file = self.reader(data)
+        self.generation_date = datetime.now()
+        self.prefix = 'MAGCL'
+        self.version = version
+        self.distributor = distributor
+        self.default_compression = compression
+
+    def __repr__(self):
+        return "{}: {} kWh".format(self.filename, self.total)
+
+    def __gt__(self, other):
+        return self.total > other.total
+
+    def __lt__(self, other):
+        return self.total < other.total
+
+    def __eq__(self, other):
+        return self.file.equals(other.file)
+
+    def __add__(self, other):
+        return self.file.append(other.file)
+
+    def __len__(self):
+        return len(self.file)
+
+    @property
+    def filename(self):
+        filename = "{prefix}_{distributor}_{measures_date}_{timestamp}.{version}".format(
+                prefix=self.prefix, distributor=self.distributor,
+                measures_date=self.measures_date[:10].replace('/', ''),
+                timestamp=self.generation_date.strftime(SIMPLE_DATE_MASK), version=self.version
+            )
+        if self.default_compression:
+            filename += ".{compression}".format(compression=self.default_compression)
+
+        return filename
+
+    @property
+    def total(self):
+        return float(self.file[self.file['magnitud' == 'AE']]['consum'].sum())
+
+    @property
+    def ai(self):
+        return float(self.file[self.file['magnitud' == 'AE']]['consum'].sum())
+
+    @property
+    def ae(self):
+        return float(self.file[self.file['magnitud' == 'AS']]['consum'].sum())
+
+    @property
+    def r1(self):
+        return float(self.file[self.file['magnitud' == 'R1']]['consum'].sum())
+
+    @property
+    def r2(self):
+        return float(self.file[self.file['magnitud' == 'R2']]['consum'].sum())
+
+    @property
+    def r3(self):
+        return float(self.file[self.file['magnitud' == 'R3']]['consum'].sum())
+
+    @property
+    def r4(self):
+        return float(self.file[self.file['magnitud' == 'R4']]['consum'].sum())
+
+    def reader(self, filepath):
+        if isinstance(filepath, str):
+            df = pd.read_csv(filepath, sep=';', names=self.columns)
+        elif isinstance(filepath, list):
+            df = pd.DataFrame(data=filepath)
+        else:
+            raise Exception("Filepath must be an str or a list")
+
+        # TODO data processing
+
+        df = df[self.columns]
+        return df
+
+    def writer(self):
+        existing_files = os.listdir('/tmp')
+        if existing_files:
+            versions = [int(f.split('.')[1]) for f in existing_files if self.filename.split('.')[0] in f]
+            if versions:
+                self.version = max(versions) + 1
+
+        file_path = os.path.join('/tmp', self.filename)
+        kwargs = {'sep': ';',
+                  'header': False,
+                  'columns': self.columns,
+                  'index': False,
+                  check_line_terminator_param(): ';\n'
+                  }
+        if self.default_compression:
+            kwargs.update({'compression': self.default_compression})
+
+        self.file.to_csv(file_path, **kwargs)
+        return file_path

mesures/magclqh.py

@@ -0,0 +1,30 @@
+# -*- coding: utf-8 -*-
+from mesures.dates import *
+from mesures.headers import MAGCL_HEADER as COLUMNS
+from mesures.magcl import MAGCL
+import pandas as pd
+
+
+class MAGCLQH(MAGCL):
+    def __init__(self, data, distributor=None, compression='bz2', columns=COLUMNS, version=0):
+        """
+        :param data: list of dicts or absolute file_path
+        :param distributor: str distributor REE code
+        :param compression: 'bz2', 'gz'... OR False otherwise
+        """
+        super(MAGCLQH, self).__init__(data=data, distributor=distributor, compression=compression, columns=columns,
+                                      version=version)
+        self.prefix = 'MAGCLQH'
+
+    def reader(self, filepath):
+        if isinstance(filepath, str):
+            df = pd.read_csv(filepath, sep=';', names=self.columns)
+        elif isinstance(filepath, list):
+            df = pd.DataFrame(data=filepath)
+        else:
+            raise Exception("Filepath must be an str or a list")
+
+        # TODO data processing
+
+        df = df[self.columns]
+        return df