我要处理的 JSON 文件中有多个字典。
with pm.Model() as model:
# global model parameters
home = pm.Flat("home")
sd_att = pm.HalfStudentT("sd_att", nu=3, sigma=2.5)
sd_def = pm.HalfStudentT("sd_def", nu=3, sigma=2.5)
intercept = pm.Flat("intercept")
# team-specific model parameters
atts_star = pm.Normal("atts_star", mu=0, sigma=sd_att, shape=num_teams)
defs_star = pm.Normal("defs_star", mu=0, sigma=sd_def, shape=num_teams)
atts = pm.Deterministic("atts", atts_star - tt.mean(atts_star))
defs = pm.Deterministic("defs", defs_star - tt.mean(defs_star))
home_theta = tt.exp(intercept + home + atts[home_team] + defs[away_team])
away_theta = tt.exp(intercept + atts[away_team] + defs[home_team])
# likelihood of observed data
home_points = pm.Poisson("home_points", mu=home_theta, observed=observed_home_goals)
away_points = pm.Poisson("away_points", mu=away_theta, observed=observed_away_goals)
我试过了:
data = [
{
'field1' : 'Name',
'value': {
'self': 'www.google.com',
'id': '1234',
'value': 'myname'
}
},
{
'field1' : 'Name1',
'value': {
'self': 'www.google.com',
'id': '2345',
'value': 'myname1'
}
},
{
'field1' : 'Name2',
'value': 'hostname'
}
]
我得到的输出为:
for info in data:
if 'value' in info:
if isinstance(info, dict)
print(info['value']['value'])
我正在寻找以下输出:
myname
myname1
答案 0 :(得分:0)
你可以这样做:
data = [
{
'field1' : 'Name',
'value': {
'self': 'www.google.com',
'id': '1234',
'value': 'myname'
}
},
{
'field1' : 'Name1',
'value': {
'self': 'www.google.com',
'id': '2345',
'value': 'myname1'
}
},
{
'field1' : 'Name2',
'value': 'hostname'
}
]
def deepest_string_value(d):
value = d.get('value')
if isinstance(value, dict):
return deepest_string_value(value)
elif isinstance(value, str):
return value
for row in data:
print(deepest_string_value(row))
输出:
myname
myname1
hostname