def update_dollars_ratios():
url = ("http://www.ambito.com/economia/mercados/monedas/dolar/"
"x_dolar_get_grafico.asp?ric={:}&tipo={:}")
begin = datetime(1984, 4, 12)
dollar_vars = {
"ARSB=": {
"name": u"dollar/blue",
"description": u"Dolar blue en Argentina",
"reference": u"ARS/USD"
},
"ARSSCBCRA": {
"name": u"dollar/bcra",
"description": (u"Dolar del Banco Central de la Republica "
"Argentina"),
"reference": u"ARS/USD"
}
}
for k, v in dollar_vars.items():
var = variable(**v)
lapse = "ww" if var['changes'] else "yyyy"
composed_url = url.format(k, lapse)
dollars = map(
lambda (d, v): (datetime.strptime(d, "%Y/%m/%d").date(), v),
eval(GET(composed_url)))
begin = get_next_date(var)
update_prices(var, dollars, begin)
def update_bcra_reserves():
url = "http://www.bcra.gov.ar/Estadisticas/estprv010001.asp"
bcra_vars = {
u"reserve": {
u"name": u"reserve/bcra",
u"description": u"Reservas en dolares del Banco Central de la República Argentina",
u"reference": u"USD"
}
}
variables = {k: variable(**v) for k, v in bcra_vars.items()}
var = variables["reserve"]
first_date = datetime(1996, 03, 02)
data = {
'desde': first_date.strftime("%d/%m/%Y"),
'hasta': datetime.now().strftime("%d/%m/%Y"),
'descri': 1,
'I1.x': 40,
'I1.y': 7,
'I1': 'Enviar',
'fecha': 'Fecha_Serie',
'campo': 'Res_Int_BCRA'
}
page = beautifulsoup(POST(url, data))
rows = page.select("#texto_columna_2 tr")
data = map(lambda r: map(lambda c: c.text, r.select('td')), rows)
data = data[1:]
reserves = map(lambda d:
(datetime.strptime(d[0], "%d/%m/%Y").date(),
float(d[1]) * 1000000),
data)
print reserves
begin = get_next_date(var, first_date)
print begin
update_prices(var, reserves, begin)
print "ready!"
def update_dollars_ratios():
url = ("http://www.ambito.com/economia/mercados/monedas/dolar/"
"x_dolar_get_grafico.asp?ric={:}&tipo={:}")
begin = datetime(1984, 4, 12)
dollar_vars = {
"ARSB=": {
"name": u"dollar/blue",
"description": u"Dolar blue en Argentina",
"reference": u"ARS/USD"
},
"ARSSCBCRA": {
"name":
u"dollar/bcra",
"description": (u"Dolar del Banco Central de la Republica "
"Argentina"),
"reference":
u"ARS/USD"
}
}
for k, v in dollar_vars.items():
var = variable(**v)
lapse = "ww" if var['changes'] else "yyyy"
composed_url = url.format(k, lapse)
dollars = map(
lambda (d, v): (datetime.strptime(d, "%Y/%m/%d").date(), v),
eval(GET(composed_url)))
begin = get_next_date(var)
update_prices(var, dollars, begin)
def update_crops_bcr():
bcr_variables = {
u"Soja": {
"name": u"soy/bcr",
"description": u"Soja de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Trigo": {
"name": u"wheat/bcr",
"description": u"Trigo de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Sorgo": {
"name": u"sorghum/bcr",
"description": u"Sorgo de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u'Ma\xedz': {
"name": u"corn/bcr",
"description": u"Maiz de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Girasol": {
"name": u"sunseed/bcr",
"description": u"Girasol de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
}
}
variables = {k: variable(**v) for k, v in bcr_variables.items()}
is_empty = len(variables["Soja"]['changes']) == 0
if is_empty:
datasets = glob('data/bcr/*.prices.xml')
load_data = partial(load_bcr_dataset, variables=variables)
map(load_data, datasets)
url = 'http://www.bcr.com.ar/Pages/Granos/Cotizaciones/default.aspx'
rows = get_page(url).select('.ms-vb tr')
text = map(lambda r: [c.text for c in r.select('td')], rows)
to_date = lambda d: datetime.strptime(d, '%d/%m/%Y').date()
dts = map(to_date, text[0][2:])
for line in text[2:]:
var = variables[line[0]]
begin = get_next_date(var)
prices = map(lambda v: float(v) if is_float(v) else None, line[2:])
prices = zip(dts, prices)
update_prices(var, prices, begin)
def update_crops_bcr():
bcr_variables = {
u"Soja": {
"name": u"soy/bcr",
"description": u"Soja de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Trigo": {
"name": u"wheat/bcr",
"description": u"Trigo de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Sorgo": {
"name": u"sorghum/bcr",
"description": u"Sorgo de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u'Ma\xedz': {
"name": u"corn/bcr",
"description": u"Maiz de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
},
u"Girasol": {
"name": u"sunseed/bcr",
"description": u"Girasol de la Bolsa de Comercio de Rosario (Arg)",
"reference": u"ARS/tn"
}
}
variables = {k: variable(**v) for k, v in bcr_variables.items()}
is_empty = len(variables["Soja"]['changes']) == 0
if is_empty:
datasets = glob('data/bcr/*.prices.xml')
load_data = partial(load_bcr_dataset, variables=variables)
map(load_data, datasets)
url = 'http://www.bcr.com.ar/Pages/Granos/Cotizaciones/default.aspx'
rows = get_page(url).select('.ms-vb tr')
text = map(lambda r: [c.text for c in r.select('td')], rows)
to_date = lambda d: datetime.strptime(d, '%d/%m/%Y').date()
dts = map(to_date, text[0][2:])
for line in text[2:]:
var = variables[line[0]]
begin = get_next_date(var)
prices = map(lambda v: float(v) if is_float(v) else None, line[2:])
prices = zip(dts, prices)
update_prices(var, prices, begin)
def update_crops_chicago():
chicago_variables = {
u"soybean": {
"name": u"soy/chicago",
"description": u"Soja de la Bolsa de Chicago (USA)",
"reference": u"USD/bushel"
}
}
variables = {k: variable(**v) for k, v in chicago_variables.items()}
url = "http://api.ieconomics.com/ie5/?s=s%201:com&span=1y&_="
data = get_page(url).select('p')[0].text
data = json.loads(data)[0]
data = data['series'][0]['serie']['data']
to_tuple = (lambda r:
(datetime.strptime(r['x_dt'], "%Y-%m-%dT%H:%M:%S.%fZ").date(),
float(r['close'])))
prices = map(to_tuple, data)
for k, var in variables.items():
begin = get_next_date(var)
update_prices(var, prices, begin)
def update_crops_chicago():
chicago_variables = {
u"soybean": {
"name": u"soy/chicago",
"description": u"Soja de la Bolsa de Chicago (USA)",
"reference": u"USD/bushel"
}
}
variables = {k: variable(**v) for k, v in chicago_variables.items()}
url = "http://api.ieconomics.com/ie5/?s=s%201:com&span=1y&_="
data = get_page(url).select('p')[0].text
data = json.loads(data)[0]
data = data['series'][0]['serie']['data']
to_tuple = (lambda r:
(datetime.strptime(r['x_dt'], "%Y-%m-%dT%H:%M:%S.%fZ").date(),
float(r['close'])))
prices = map(to_tuple, data)
for k, var in variables.items():
begin = get_next_date(var)
update_prices(var, prices, begin)
def update_petroleum_wti_barrel_ratios():
url = ("http://www.ambito.com/economia/mercados/petroleo/"
"x_petroleo_get_grafico.asp?ric=1&"
"timeFrom={:}&timeTo={:}&tipo=libre")
begin = datetime(1984, 4, 12)
end = datetime.now()
petroleum_vars = {
u"PETROLEUM": {
u"name": u"petroleum/wti",
u"description": u"Petroleo West Texas Intermediate",
u"reference": u"USD/barrel"
}
}
for k, v in petroleum_vars.items():
var = variable(**v)
begin = get_next_date(var, begin)
p = lambda dt: dt.strftime("%d/%m/%Y")
composed_url = url.format(p(begin), p(end))
prices = map(
lambda (d, v): (datetime.strptime(d, "%Y/%m/%d").date(), v),
eval(GET(composed_url)))
prices = filter(lambda p: p[0] >= begin.date(), prices)
update_prices(var, prices, begin)
def update_crops_afascl():
afascl_variables = {
u"Soja": {
"name": u"soy/afascl",
"description": u"Soja de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Trigo": {
"name": u"wheat/afascl",
"description": u"Trigo de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Sorgo": {
"name": u"sorghum/afscl",
"description": u"Sorgo de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u'Ma\xedz': {
"name": u"corn/afascl",
"description": u"Maiz de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Girasol": {
"name": u"sunseed/afascl",
"description": u"Girasol de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
}
}
variables = {k: variable(**v) for k, v in afascl_variables.items()}
get_prices = partial(get_afascl_prices, variables=variables)
dt = get_next_date(variables['Soja'], date(2007, 10, 1))
while dt.date() <= date.today():
for variable_id, price in get_prices(dt).items():
change(value=price,
moment=dt.strftime('%Y-%m-%d'),
variable_id=variable_id)
dt += timedelta(days=1)
def update_crops_afascl():
afascl_variables = {
u"Soja": {
"name": u"soy/afascl",
"description": u"Soja de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Trigo": {
"name": u"wheat/afascl",
"description": u"Trigo de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Sorgo": {
"name": u"sorghum/afscl",
"description": u"Sorgo de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u'Ma\xedz': {
"name": u"corn/afascl",
"description": u"Maiz de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
},
u"Girasol": {
"name": u"sunseed/afascl",
"description": u"Girasol de la AFSCL de San Martin (Arg)",
"reference": u"ARS/tn"
}
}
variables = {k: variable(**v) for k, v in afascl_variables.items()}
get_prices = partial(get_afascl_prices, variables=variables)
dt = get_next_date(variables['Soja'], date(2007, 10, 1))
while dt.date() <= date.today():
for variable_id, price in get_prices(dt).items():
change(value=price,
moment=dt.strftime('%Y-%m-%d'),
variable_id=variable_id)
dt += timedelta(days=1)