def view():
main = Main(db)
pref = main.get_user_pref()
new_resource = flask.request.args.get("new_resource", False)
if new_resource == "true":
new_resource = True
else:
new_resource = False
db_name = flask.request.args.get("database_type", pref[0])
typ = flask.request.args.get("type", pref[1])
country = flask.request.args.get("country", pref[2])
state = flask.request.args.get("state", pref[3])
return_type = flask.request.args.get("return_type", "")
if not return_type:
flask.abort(404)
return
return_type = return_type.lower()
keys = []
values = []
if return_type == "database_type":
keys, values = main.get_databases()
elif return_type == "type":
if not db_name:
db_name = "PowerPlants"
keys, values = main.get_types(db_name)
elif return_type == "country":
if not typ:
flask.abort(404)
return
keys, values = main.get_countries(typ, new_resource=new_resource)
elif return_type == "state":
if not country:
flask.abort(404)
return
keys, values = main.get_states(country, new_resource=new_resource)
values.insert(0, [0, "All"])
return flask.jsonify(keys=keys, values=values)
class Metadata(object):
"""
Computes the values and updates the metadata table.
This table provides summary info for the views.
"""
def __init__(self):
self.conn = connection.Db().session
self.main = Main(connection.Db())
self.moderation = Moderation(connection.Db())
self.select = Select(connection.Db())
self.perf_fields = ("_Performance", "Year_yr",
["Total_Gigawatt_Hours_Generated_nbr", "CO2_Emitted_(Tonnes)_nbr"])
self.unit_fields = ("_Unit_Description", "Date_Commissioned_dt", "Capacity_(MWe)_nbr")
self.alt_types = [4, 7, 8, 10]
self.alt_perf_fields = ("_Performance", "Year_yr",
["Total_Gigawatt_Hours_Generated_nbr", "Plant_Load_Factor_(%)_nbr"])
self.nuclear_perf_fields = ("_Performance", "Year_yr",
["Plant_Load_Factor_(%)_nbr"])
self.nuclear_ghg_fields = ("_Gigawatt_Hours_Generated", "Year_yr",
["Gigawatt_Hours_Generated_nbr"])
self.wind_unit_fields = ("_Unit_Description", "Date_Commissioned_dt",
"Peak_MWe_per_Turbine_nbr", "Number_Of_Turbines_nbr")
def get_unit_data(self, typ, plants):
# units
results = self.select.read(typ[1] + self.unit_fields[0],
columns=["`" + self.unit_fields[1] + "`",
"`" + self.unit_fields[2] + "`", "Description_ID"],
where=[["Description_ID", "in",
[plant[0] for plant in plants]]],
dict_cursor=False)
units = results.fetchall()
cumulative_capacity_total = 0
cumulative_capacity = {}
new_capacity = {}
new_capacity['keys'] = [self.unit_fields[1], self.unit_fields[2]]
cumulative_capacity['keys'] = [self.unit_fields[1], self.unit_fields[2]]
cap_values = {}
cum_cap_values = {}
for unit in units:
if not unit[1] or not unit[0]:
continue
unit_val = math.ceil(float(unit[1]))
cumulative_capacity_total += unit_val
year = unit[0].decode("utf8").split("-")[0]
val = cap_values.get(year, -1)
if val == -1:
cap_values[year] = 0
cap_values[year] += unit_val
prev_year = 0
for year in sorted(cap_values.keys()):
cum_cap_values[year] = cap_values[year] + cum_cap_values.get(prev_year, 0)
prev_year = year
new_capacity['values'] = sorted([list(values) for values in
zip(cap_values.keys(),
cap_values.values())]
)
cumulative_capacity['values'] = sorted([list(values) for values in
zip(cum_cap_values.keys(),
cum_cap_values.values())]
)
return cumulative_capacity_total, cumulative_capacity, new_capacity
def get_wind_unit_data(self, typ, plants):
# units
results = self.select.read(typ[1] + self.wind_unit_fields[0],
columns=["`" + self.wind_unit_fields[1] + "`",
"`" + self.wind_unit_fields[2] + "`",
"`" + self.wind_unit_fields[3] + "`"],
where=[["Description_ID", "in",
[plant[0] for plant in plants]]],
dict_cursor=False)
units = results.fetchall()
cumulative_capacity_total = 0
new_capacity = {}
new_capacity['keys'] = [self.unit_fields[1], self.unit_fields[2]]
cap_values = {}
for unit in units:
if not unit[1] or not unit[0]:
continue
unit_val = math.ceil(float(unit[1]))
cumulative_capacity_total += unit_val
year = unit[0].decode("utf8").split("-")[0]
val = cap_values.get(year, -1)
if val == -1:
cap_values[year] = 0
if unit[2] and float(unit[2]):
cap_values[year] += unit_val * math.ceil(float(unit[2]))
cum_cap_values = {}
prev_year = 0
for year in sorted(cap_values.keys()):
cum_cap_values[year] = cap_values[year] + cum_cap_values.get(prev_year, 0)
prev_year = year
new_capacity['values'] = sorted([list(values) for values in
zip(cap_values.keys(),
cap_values.values())])
cumulative_capacity = {}
cumulative_capacity['values'] = sorted([list(values) for values in
zip(cum_cap_values.keys(),
cum_cap_values.values())]
)
return cumulative_capacity_total, cumulative_capacity, new_capacity
def get_general_performance_data(self, typ, plants):
# performance
cols = [self.perf_fields[1]]
if typ[0] in self.alt_types:
cols.extend(["`" + p_col + "`" for p_col in self.alt_perf_fields[2]])
else:
cols.extend(["`" + p_col + "`" for p_col in self.perf_fields[2]])
results = self.select.read(typ[1] + self.perf_fields[0],
columns=cols,
where=[["Description_ID", "in",
[plant[0] for plant in plants]]],
dict_cursor=False)
performances = results.fetchall()
co2 = {}
ghg = {}
for perf in performances:
year = perf[0].decode("utf8")
if perf[1]:
g_val = ghg.get(year, -1)
if g_val == -1:
ghg[year] = 0
ghg[year] += math.ceil(float(perf[1]))
if perf[2]:
c_val = co2.get(year, -1)
if c_val == -1:
co2[year] = 0
co2[year] += math.ceil(float(perf[2]))
# for plotting purposes, the years in both the dicts must
# be the same. so adding zeros to missing years.
for year in co2.keys():
val = ghg.get(year, -1)
if val == -1:
ghg[year] = 0
for year in ghg.keys():
val = co2.get(year, -1)
if val == -1:
co2[year] = 0
ghg_values = {"keys": [self.perf_fields[1], self.perf_fields[2][0]],
"values": sorted([list(values)
for values in zip(ghg.keys(),
ghg.values())]
)}
co2_values = {"keys": [self.perf_fields[1], self.perf_fields[2][1]],
"values": sorted([list(values) for values in
zip(co2.keys(), co2.values())])}
return ghg_values, co2_values
def get_nuclear_performance_data(self, typ, plants):
# performance
cols = [self.perf_fields[1]]
cols.append("`" + self.nuclear_ghg_fields[2][0] + "`")
ghg_res = self.select.read(typ[1] + self.nuclear_ghg_fields[0],
columns=cols,
where=[["Description_ID", "in",
[plant[0] for plant in plants]]],
dict_cursor=False)
ghg_perf = ghg_res.fetchall()
cols = [self.perf_fields[1]]
cols.append("`" + self.nuclear_perf_fields[2][0] + "`")
reg_res = self.select.read(typ[1] + self.nuclear_perf_fields[0],
columns=cols,
where=[["Description_ID", "in",
[plant[0] for plant in plants]]],
dict_cursor=False)
reg_perf = reg_res.fetchall()
co2 = {}
ghg = {}
for perf in ghg_perf:
year = perf[0].decode("utf8")
if perf[1]:
g_val = ghg.get(year, -1)
if g_val == -1:
ghg[year] = 0
ghg[year] += math.ceil(float(perf[1]))
for perf in reg_perf:
if perf[1]:
c_val = co2.get(year, -1)
if c_val == -1:
co2[year] = 0
co2[year] += math.ceil(float(perf[1]))
# for plotting purposes, the years in both the dicts must
# be the same. so adding zeros to missing years.
for year in co2.keys():
val = ghg.get(year, -1)
if val == -1:
ghg[year] = 0
for year in ghg.keys():
val = co2.get(year, -1)
if val == -1:
co2[year] = 0
ghg_values = {"keys": [self.nuclear_ghg_fields[1], self.nuclear_ghg_fields[2][0]],
"values": sorted([list(values) for values in
zip(ghg.keys(), ghg.values())]
)}
co2_values = {"keys": [self.nuclear_perf_fields[1], self.nuclear_perf_fields[2][0]],
"values": sorted([list(values) for values in
zip(co2.keys(), co2.values())]
)}
return ghg_values, co2_values
def compute(self):
t_keys, types = self.main.get_types("PowerPlants")
#types = [[1, "Coal"]]
session = self.conn.cursor()
for typ in types:
c_keys, countries = self.main.get_countries(typ[0])
#countries = [[38, "Canada"]]
for country in countries:
p_keys, plants = self.moderation.get_all_resources(country_id=country[0], type_id=typ[0])
# unit data
if typ[0] == 10:
cumulative_capacity_total, cumulative_capacity, new_capacity = self.get_wind_unit_data(typ, plants)
else:
cumulative_capacity_total, cumulative_capacity, new_capacity = self.get_unit_data(typ, plants)
# perf data
if typ[0] == 5:
ghg, co2 = self.get_nuclear_performance_data(typ, plants)
else:
ghg, co2 = self.get_general_performance_data(typ, plants)
sql = "INSERT INTO metadata SET Country_ID=%(country_id)s, \
Type_ID=%(type_id)s, Number_of_Plants=%(number_of_plants)s, \
Cumulative_Capacity=%(cum_cap)s, \
Cumulative_Capacity_Total=%(cum_cap_tot)s, New_Capacity_Added=%(new_cap)s, \
Annual_Gigawatt_Hours_Generated=%(ghg)s, Annual_CO2_Emitted=%(co2)s"
session.execute(sql, {
"country_id": country[0],
"type_id": typ[0],
"number_of_plants": str(len(plants)),
"cum_cap": json.dumps(cumulative_capacity),
"cum_cap_tot": str(cumulative_capacity_total),
"new_cap": json.dumps(new_capacity),
"ghg": json.dumps(ghg),
"co2": json.dumps(co2)
})
self.conn.commit()
session.close()