We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Chile inconsistency between live and historical data acquisition
Our systems use historical data to train forecasts. When run in production, those forecasts require live data. Therefore, the two datafeeds need to be consistent.
I think the Chile parser uses two different datafeeds that aren't consistent, and thus our forecasts might be inconsistent.
If in doubt, we should only implement the real-time feed to avoid our database having both data mixed.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `parsers/CL.py`
Content:
```
1 #!/usr/bin/env python3
2 
3 """Parser for the electricity grid of Chile"""
4 
5 import arrow
6 import logging
7 import requests
8 from collections import defaultdict
9 from operator import itemgetter
10 from .lib.validation import validate
11 
12 # Historical API
13 API_BASE_URL = "https://sipub.coordinador.cl/api/v1/recursos/generacion_centrales_tecnologia_horario?"
14 # Live API
15 API_BASE_URL_LIVE_TOT = 'http://panelapp.coordinadorelectrico.cl/api/chart/demanda'
16 API_BASE_URL_LIVE_REN = 'http://panelapp.coordinadorelectrico.cl/api/chart/ernc'  # ERNC = energias renovables no convencionales
17 
18 TYPE_MAPPING = {'hidraulica': 'hydro',
19                 'termica': 'unknown',
20                 'eolica': 'wind',
21                 'solar': 'solar',
22                 'geotermica': 'geothermal'}
23 
24 
25 def get_data_live(session, logger):
26     """Requests live generation data in json format."""
27 
28     s = session or requests.session()
29     json_total = s.get(API_BASE_URL_LIVE_TOT).json()
30     json_ren = s.get(API_BASE_URL_LIVE_REN).json()
31 
32     return json_total, json_ren
33 
34 
35 def production_processor_live(json_tot, json_ren):
36     """
37     Extracts generation data and timestamp into dictionary.
38     Returns a list of dictionaries for all of the available "live" data, usually that day.
39     """
40 
41     gen_total = json_tot['data'][0]['values']
42 
43     if json_ren['data'][1]['key'] == 'ENERGÍA SOLAR':
44         rawgen_sol = json_ren['data'][1]['values']
45     else:
46         raise RuntimeError(
47             f"Unexpected data label. Expected 'ENERGÍA SOLAR' and got {json_ren['data'][1]['key']}")
48 
49     if json_ren['data'][0]['key'] == 'ENERGÍA EÓLICA':
50         rawgen_wind = json_ren['data'][0]['values']
51     else:
52         raise RuntimeError(
53             f"Unexpected data label. Expected 'ENERGÍA EÓLICA' and got {json_ren['data'][0]['key']}")
54 
55     mapped_totals = []
56 
57     for total in gen_total:
58         datapoint = {}
59 
60         dt = total[0]
61         for pair in rawgen_sol:
62             if pair[0] == dt:
63                 solar = pair[1]
64                 break
65         for pair in rawgen_wind:
66             if pair[0] == dt:
67                 wind = pair[1]
68                 break
69 
70         datapoint['datetime'] = arrow.get(dt / 1000, tzinfo='Chile/Continental').datetime
71         datapoint['unknown'] = (total[1] - wind - solar)
72         datapoint['wind'] = wind
73         datapoint['solar'] = solar
74         mapped_totals.append(datapoint)
75 
76     return mapped_totals
77 
78 
79 def production_processor_historical(raw_data):
80     """Takes raw json data and groups by datetime while mapping generation to type.
81     Returns a list of dictionaries.
82     """
83 
84     clean_datapoints = []
85     for datapoint in raw_data:
86         clean_datapoint = {}
87         date, hour = datapoint['fecha'], datapoint['hora']
88         hour -= 1  # `hora` starts at 1
89         date = arrow.get(date, "YYYY-MM-DD", tzinfo='Chile/Continental').shift(hours=hour)
90         clean_datapoint['datetime'] = date.datetime
91 
92         gen_type_es = datapoint['tipo_central']
93         mapped_gen_type = TYPE_MAPPING[gen_type_es]
94         value_mw = float(datapoint['generacion_sum'])
95 
96         clean_datapoint[mapped_gen_type] = value_mw
97 
98         clean_datapoints.append(clean_datapoint)
99 
100     combined = defaultdict(dict)
101     for elem in clean_datapoints:
102         combined[elem['datetime']].update(elem)
103 
104     ordered_data = sorted(combined.values(), key=itemgetter("datetime"))
105 
106     return ordered_data
107 
108 
109 def fetch_production(zone_key='CL', session=None, target_datetime=None, logger=logging.getLogger(__name__)):
110     """Requests the last known production mix (in MW) of a given zone
111     Arguments:
112     zone_key (optional) -- used in case a parser is able to fetch multiple zones
113     session (optional) -- request session passed in order to re-use an existing session
114     target_datetime (optional) -- used if parser can fetch data for a specific day, a string in the form YYYYMMDD
115     logger (optional) -- handles logging when parser is run
116     Return:
117     A list of dictionaries in the form:
118     {
119       'zoneKey': 'FR',
120       'datetime': '2017-01-01T00:00:00Z',
121       'production': {
122           'biomass': 0.0,
123           'coal': 0.0,
124           'gas': 0.0,
125           'hydro': 0.0,
126           'nuclear': null,
127           'oil': 0.0,
128           'solar': 0.0,
129           'wind': 0.0,
130           'geothermal': 0.0,
131           'unknown': 0.0
132       },
133       'storage': {
134           'hydro': -10.0,
135       },
136       'source': 'mysource.com'
137     }
138     """
139 
140     if target_datetime is None:
141         gen_tot, gen_ren = get_data_live(session, logger)
142 
143         processed_data = production_processor_live(gen_tot, gen_ren)
144 
145         data = []
146 
147         for production_data in processed_data:
148             dt = production_data.pop('datetime')
149 
150             datapoint = {
151                 'zoneKey': zone_key,
152                 'datetime': dt,
153                 'production': production_data,
154                 'storage': {
155                     'hydro': None,
156                 },
157                 'source': 'coordinadorelectrico.cl'
158             }
159             datapoint = validate(datapoint, logger,
160                                  remove_negative=True, floor=1000)
161 
162             data.append(datapoint)
163 
164         return data
165 
166     arr_target_datetime = arrow.get(target_datetime)
167     start = arr_target_datetime.shift(days=-1).format("YYYY-MM-DD")
168     end = arr_target_datetime.format("YYYY-MM-DD")
169 
170     date_component = 'fecha__gte={}&fecha__lte={}'.format(start, end)
171 
172     # required for access
173     headers = {'Referer': 'https://www.coordinador.cl/operacion/graficos/operacion-real/generacion-real-del-sistema/',
174                'Origin': 'https://www.coordinador.cl'}
175 
176     s = session or requests.Session()
177     url = API_BASE_URL + date_component
178 
179     req = s.get(url, headers=headers)
180     raw_data = req.json()['aggs']
181     processed_data = production_processor_historical(raw_data)
182 
183     data = []
184     for production_data in processed_data:
185         dt = production_data.pop('datetime')
186 
187         datapoint = {
188             'zoneKey': zone_key,
189             'datetime': dt,
190             'production': production_data,
191             'storage': {
192                 'hydro': None,
193             },
194             'source': 'coordinador.cl'
195         }
196 
197         data.append(datapoint)
198 
199     return data[:-9]
200     """The last 9 datapoints should be omitted because they usually are incomplete and shouldn't appear on the map."""
201 
202 
203 if __name__ == "__main__":
204     """Main method, never used by the Electricity Map backend, but handy for testing."""
205     print('fetch_production() ->')
206     print(fetch_production())
207     # For fetching historical data instead, try:
208     print(fetch_production(target_datetime=arrow.get("20200220", "YYYYMMDD")))
209
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/parsers/CL.py b/parsers/CL.py
--- a/parsers/CL.py
+++ b/parsers/CL.py
@@ -103,6 +103,17 @@
 
     ordered_data = sorted(combined.values(), key=itemgetter("datetime"))
 
+    # For consistency with live API, hydro and geothermal must be squeezed into unknown
+    for datapoint in ordered_data:
+        if 'unknown' not in datapoint:
+            datapoint['unknown'] = 0
+        if 'hydro' in datapoint:
+            datapoint['unknown'] += datapoint['hydro']
+            del datapoint['hydro']
+        if 'geothermal' in datapoint:
+            datapoint['unknown'] += datapoint['geothermal']
+            del datapoint['geothermal']
+
     return ordered_data

{"golden_diff": "diff --git a/parsers/CL.py b/parsers/CL.py\n--- a/parsers/CL.py\n+++ b/parsers/CL.py\n@@ -103,6 +103,17 @@\n \n     ordered_data = sorted(combined.values(), key=itemgetter(\"datetime\"))\n \n+    # For consistency with live API, hydro and geothermal must be squeezed into unknown\n+    for datapoint in ordered_data:\n+        if 'unknown' not in datapoint:\n+            datapoint['unknown'] = 0\n+        if 'hydro' in datapoint:\n+            datapoint['unknown'] += datapoint['hydro']\n+            del datapoint['hydro']\n+        if 'geothermal' in datapoint:\n+            datapoint['unknown'] += datapoint['geothermal']\n+            del datapoint['geothermal']\n+\n     return ordered_data\n", "issue": "Chile inconsistency between live and historical data acquisition\nOur systems use historical data to train forecasts. When run in production, those forecasts require live data. Therefore, the two datafeeds need to be consistent.\r\nI think the Chile parser uses two different datafeeds that aren't consistent, and thus our forecasts might be inconsistent.\r\nIf in doubt, we should only implement the real-time feed to avoid our database having both data mixed.\n", "before_files": [{"content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the electricity grid of Chile\"\"\"\n\nimport arrow\nimport logging\nimport requests\nfrom collections import defaultdict\nfrom operator import itemgetter\nfrom .lib.validation import validate\n\n# Historical API\nAPI_BASE_URL = \"https://sipub.coordinador.cl/api/v1/recursos/generacion_centrales_tecnologia_horario?\"\n# Live API\nAPI_BASE_URL_LIVE_TOT = 'http://panelapp.coordinadorelectrico.cl/api/chart/demanda'\nAPI_BASE_URL_LIVE_REN = 'http://panelapp.coordinadorelectrico.cl/api/chart/ernc'  # ERNC = energias renovables no convencionales\n\nTYPE_MAPPING = {'hidraulica': 'hydro',\n                'termica': 'unknown',\n                'eolica': 'wind',\n                'solar': 'solar',\n                'geotermica': 'geothermal'}\n\n\ndef get_data_live(session, logger):\n    \"\"\"Requests live generation data in json format.\"\"\"\n\n    s = session or requests.session()\n    json_total = s.get(API_BASE_URL_LIVE_TOT).json()\n    json_ren = s.get(API_BASE_URL_LIVE_REN).json()\n\n    return json_total, json_ren\n\n\ndef production_processor_live(json_tot, json_ren):\n    \"\"\"\n    Extracts generation data and timestamp into dictionary.\n    Returns a list of dictionaries for all of the available \"live\" data, usually that day.\n    \"\"\"\n\n    gen_total = json_tot['data'][0]['values']\n\n    if json_ren['data'][1]['key'] == 'ENERG\u00cdA SOLAR':\n        rawgen_sol = json_ren['data'][1]['values']\n    else:\n        raise RuntimeError(\n            f\"Unexpected data label. Expected 'ENERG\u00cdA SOLAR' and got {json_ren['data'][1]['key']}\")\n\n    if json_ren['data'][0]['key'] == 'ENERG\u00cdA E\u00d3LICA':\n        rawgen_wind = json_ren['data'][0]['values']\n    else:\n        raise RuntimeError(\n            f\"Unexpected data label. Expected 'ENERG\u00cdA E\u00d3LICA' and got {json_ren['data'][0]['key']}\")\n\n    mapped_totals = []\n\n    for total in gen_total:\n        datapoint = {}\n\n        dt = total[0]\n        for pair in rawgen_sol:\n            if pair[0] == dt:\n                solar = pair[1]\n                break\n        for pair in rawgen_wind:\n            if pair[0] == dt:\n                wind = pair[1]\n                break\n\n        datapoint['datetime'] = arrow.get(dt / 1000, tzinfo='Chile/Continental').datetime\n        datapoint['unknown'] = (total[1] - wind - solar)\n        datapoint['wind'] = wind\n        datapoint['solar'] = solar\n        mapped_totals.append(datapoint)\n\n    return mapped_totals\n\n\ndef production_processor_historical(raw_data):\n    \"\"\"Takes raw json data and groups by datetime while mapping generation to type.\n    Returns a list of dictionaries.\n    \"\"\"\n\n    clean_datapoints = []\n    for datapoint in raw_data:\n        clean_datapoint = {}\n        date, hour = datapoint['fecha'], datapoint['hora']\n        hour -= 1  # `hora` starts at 1\n        date = arrow.get(date, \"YYYY-MM-DD\", tzinfo='Chile/Continental').shift(hours=hour)\n        clean_datapoint['datetime'] = date.datetime\n\n        gen_type_es = datapoint['tipo_central']\n        mapped_gen_type = TYPE_MAPPING[gen_type_es]\n        value_mw = float(datapoint['generacion_sum'])\n\n        clean_datapoint[mapped_gen_type] = value_mw\n\n        clean_datapoints.append(clean_datapoint)\n\n    combined = defaultdict(dict)\n    for elem in clean_datapoints:\n        combined[elem['datetime']].update(elem)\n\n    ordered_data = sorted(combined.values(), key=itemgetter(\"datetime\"))\n\n    return ordered_data\n\n\ndef fetch_production(zone_key='CL', session=None, target_datetime=None, logger=logging.getLogger(__name__)):\n    \"\"\"Requests the last known production mix (in MW) of a given zone\n    Arguments:\n    zone_key (optional) -- used in case a parser is able to fetch multiple zones\n    session (optional) -- request session passed in order to re-use an existing session\n    target_datetime (optional) -- used if parser can fetch data for a specific day, a string in the form YYYYMMDD\n    logger (optional) -- handles logging when parser is run\n    Return:\n    A list of dictionaries in the form:\n    {\n      'zoneKey': 'FR',\n      'datetime': '2017-01-01T00:00:00Z',\n      'production': {\n          'biomass': 0.0,\n          'coal': 0.0,\n          'gas': 0.0,\n          'hydro': 0.0,\n          'nuclear': null,\n          'oil': 0.0,\n          'solar': 0.0,\n          'wind': 0.0,\n          'geothermal': 0.0,\n          'unknown': 0.0\n      },\n      'storage': {\n          'hydro': -10.0,\n      },\n      'source': 'mysource.com'\n    }\n    \"\"\"\n\n    if target_datetime is None:\n        gen_tot, gen_ren = get_data_live(session, logger)\n\n        processed_data = production_processor_live(gen_tot, gen_ren)\n\n        data = []\n\n        for production_data in processed_data:\n            dt = production_data.pop('datetime')\n\n            datapoint = {\n                'zoneKey': zone_key,\n                'datetime': dt,\n                'production': production_data,\n                'storage': {\n                    'hydro': None,\n                },\n                'source': 'coordinadorelectrico.cl'\n            }\n            datapoint = validate(datapoint, logger,\n                                 remove_negative=True, floor=1000)\n\n            data.append(datapoint)\n\n        return data\n\n    arr_target_datetime = arrow.get(target_datetime)\n    start = arr_target_datetime.shift(days=-1).format(\"YYYY-MM-DD\")\n    end = arr_target_datetime.format(\"YYYY-MM-DD\")\n\n    date_component = 'fecha__gte={}&fecha__lte={}'.format(start, end)\n\n    # required for access\n    headers = {'Referer': 'https://www.coordinador.cl/operacion/graficos/operacion-real/generacion-real-del-sistema/',\n               'Origin': 'https://www.coordinador.cl'}\n\n    s = session or requests.Session()\n    url = API_BASE_URL + date_component\n\n    req = s.get(url, headers=headers)\n    raw_data = req.json()['aggs']\n    processed_data = production_processor_historical(raw_data)\n\n    data = []\n    for production_data in processed_data:\n        dt = production_data.pop('datetime')\n\n        datapoint = {\n            'zoneKey': zone_key,\n            'datetime': dt,\n            'production': production_data,\n            'storage': {\n                'hydro': None,\n            },\n            'source': 'coordinador.cl'\n        }\n\n        data.append(datapoint)\n\n    return data[:-9]\n    \"\"\"The last 9 datapoints should be omitted because they usually are incomplete and shouldn't appear on the map.\"\"\"\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print('fetch_production() ->')\n    print(fetch_production())\n    # For fetching historical data instead, try:\n    print(fetch_production(target_datetime=arrow.get(\"20200220\", \"YYYYMMDD\")))\n", "path": "parsers/CL.py"}], "after_files": [{"content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the electricity grid of Chile\"\"\"\n\nimport arrow\nimport logging\nimport requests\nfrom collections import defaultdict\nfrom operator import itemgetter\nfrom .lib.validation import validate\n\n# Historical API\nAPI_BASE_URL = \"https://sipub.coordinador.cl/api/v1/recursos/generacion_centrales_tecnologia_horario?\"\n# Live API\nAPI_BASE_URL_LIVE_TOT = 'http://panelapp.coordinadorelectrico.cl/api/chart/demanda'\nAPI_BASE_URL_LIVE_REN = 'http://panelapp.coordinadorelectrico.cl/api/chart/ernc'  # ERNC = energias renovables no convencionales\n\nTYPE_MAPPING = {'hidraulica': 'hydro',\n                'termica': 'unknown',\n                'eolica': 'wind',\n                'solar': 'solar',\n                'geotermica': 'geothermal'}\n\n\ndef get_data_live(session, logger):\n    \"\"\"Requests live generation data in json format.\"\"\"\n\n    s = session or requests.session()\n    json_total = s.get(API_BASE_URL_LIVE_TOT).json()\n    json_ren = s.get(API_BASE_URL_LIVE_REN).json()\n\n    return json_total, json_ren\n\n\ndef production_processor_live(json_tot, json_ren):\n    \"\"\"\n    Extracts generation data and timestamp into dictionary.\n    Returns a list of dictionaries for all of the available \"live\" data, usually that day.\n    \"\"\"\n\n    gen_total = json_tot['data'][0]['values']\n\n    if json_ren['data'][1]['key'] == 'ENERG\u00cdA SOLAR':\n        rawgen_sol = json_ren['data'][1]['values']\n    else:\n        raise RuntimeError(\n            f\"Unexpected data label. Expected 'ENERG\u00cdA SOLAR' and got {json_ren['data'][1]['key']}\")\n\n    if json_ren['data'][0]['key'] == 'ENERG\u00cdA E\u00d3LICA':\n        rawgen_wind = json_ren['data'][0]['values']\n    else:\n        raise RuntimeError(\n            f\"Unexpected data label. Expected 'ENERG\u00cdA E\u00d3LICA' and got {json_ren['data'][0]['key']}\")\n\n    mapped_totals = []\n\n    for total in gen_total:\n        datapoint = {}\n\n        dt = total[0]\n        for pair in rawgen_sol:\n            if pair[0] == dt:\n                solar = pair[1]\n                break\n        for pair in rawgen_wind:\n            if pair[0] == dt:\n                wind = pair[1]\n                break\n\n        datapoint['datetime'] = arrow.get(dt / 1000, tzinfo='Chile/Continental').datetime\n        datapoint['unknown'] = (total[1] - wind - solar)\n        datapoint['wind'] = wind\n        datapoint['solar'] = solar\n        mapped_totals.append(datapoint)\n\n    return mapped_totals\n\n\ndef production_processor_historical(raw_data):\n    \"\"\"Takes raw json data and groups by datetime while mapping generation to type.\n    Returns a list of dictionaries.\n    \"\"\"\n\n    clean_datapoints = []\n    for datapoint in raw_data:\n        clean_datapoint = {}\n        date, hour = datapoint['fecha'], datapoint['hora']\n        hour -= 1  # `hora` starts at 1\n        date = arrow.get(date, \"YYYY-MM-DD\", tzinfo='Chile/Continental').shift(hours=hour)\n        clean_datapoint['datetime'] = date.datetime\n\n        gen_type_es = datapoint['tipo_central']\n        mapped_gen_type = TYPE_MAPPING[gen_type_es]\n        value_mw = float(datapoint['generacion_sum'])\n\n        clean_datapoint[mapped_gen_type] = value_mw\n\n        clean_datapoints.append(clean_datapoint)\n\n    combined = defaultdict(dict)\n    for elem in clean_datapoints:\n        combined[elem['datetime']].update(elem)\n\n    ordered_data = sorted(combined.values(), key=itemgetter(\"datetime\"))\n\n    # For consistency with live API, hydro and geothermal must be squeezed into unknown\n    for datapoint in ordered_data:\n        if 'unknown' not in datapoint:\n            datapoint['unknown'] = 0\n        if 'hydro' in datapoint:\n            datapoint['unknown'] += datapoint['hydro']\n            del datapoint['hydro']\n        if 'geothermal' in datapoint:\n            datapoint['unknown'] += datapoint['geothermal']\n            del datapoint['geothermal']\n\n    return ordered_data\n\n\ndef fetch_production(zone_key='CL', session=None, target_datetime=None, logger=logging.getLogger(__name__)):\n    \"\"\"Requests the last known production mix (in MW) of a given zone\n    Arguments:\n    zone_key (optional) -- used in case a parser is able to fetch multiple zones\n    session (optional) -- request session passed in order to re-use an existing session\n    target_datetime (optional) -- used if parser can fetch data for a specific day, a string in the form YYYYMMDD\n    logger (optional) -- handles logging when parser is run\n    Return:\n    A list of dictionaries in the form:\n    {\n      'zoneKey': 'FR',\n      'datetime': '2017-01-01T00:00:00Z',\n      'production': {\n          'biomass': 0.0,\n          'coal': 0.0,\n          'gas': 0.0,\n          'hydro': 0.0,\n          'nuclear': null,\n          'oil': 0.0,\n          'solar': 0.0,\n          'wind': 0.0,\n          'geothermal': 0.0,\n          'unknown': 0.0\n      },\n      'storage': {\n          'hydro': -10.0,\n      },\n      'source': 'mysource.com'\n    }\n    \"\"\"\n\n    if target_datetime is None:\n        gen_tot, gen_ren = get_data_live(session, logger)\n\n        processed_data = production_processor_live(gen_tot, gen_ren)\n\n        data = []\n\n        for production_data in processed_data:\n            dt = production_data.pop('datetime')\n\n            datapoint = {\n                'zoneKey': zone_key,\n                'datetime': dt,\n                'production': production_data,\n                'storage': {\n                    'hydro': None,\n                },\n                'source': 'coordinadorelectrico.cl'\n            }\n            datapoint = validate(datapoint, logger,\n                                 remove_negative=True, floor=1000)\n\n            data.append(datapoint)\n\n        return data\n\n    arr_target_datetime = arrow.get(target_datetime)\n    start = arr_target_datetime.shift(days=-1).format(\"YYYY-MM-DD\")\n    end = arr_target_datetime.format(\"YYYY-MM-DD\")\n\n    date_component = 'fecha__gte={}&fecha__lte={}'.format(start, end)\n\n    # required for access\n    headers = {'Referer': 'https://www.coordinador.cl/operacion/graficos/operacion-real/generacion-real-del-sistema/',\n               'Origin': 'https://www.coordinador.cl'}\n\n    s = session or requests.Session()\n    url = API_BASE_URL + date_component\n\n    req = s.get(url, headers=headers)\n    raw_data = req.json()['aggs']\n    processed_data = production_processor_historical(raw_data)\n\n    data = []\n    for production_data in processed_data:\n        dt = production_data.pop('datetime')\n\n        datapoint = {\n            'zoneKey': zone_key,\n            'datetime': dt,\n            'production': production_data,\n            'storage': {\n                'hydro': None,\n            },\n            'source': 'coordinador.cl'\n        }\n\n        data.append(datapoint)\n\n    return data[:-9]\n    \"\"\"The last 9 datapoints should be omitted because they usually are incomplete and shouldn't appear on the map.\"\"\"\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print('fetch_production() ->')\n    print(fetch_production())\n    # For fetching historical data instead, try:\n    print(fetch_production(target_datetime=arrow.get(\"20200220\", \"YYYYMMDD\")))\n", "path": "parsers/CL.py"}]}