merge - 如何从分层文档结构中展开/合并数组？
问题描述
我有一个嵌套的文档结构，我可以过滤它pluck以显示相关部分：
有没有一种优雅的方法可以将最后一级的所有条目合并到一个数组中？
预期结果（条目不是故意唯一的）：
[
'3425b91f-f019-4db3-ad56-c336bf55279b',
'3d07946e-183d-4992-9acd-676f5122e1b1',
'3425b91f-f019-4db3-ad56-c336bf55279b',
'3d07946e-183d-4992-9acd-676f5122e1b1',
'2cd652a6-4dcd-4920-9592-d4cdc5a034bf',
'70fe1812-e1de-447b-ac4f-d89fead4756d',
'2cd652a6-4dcd-4920-9592-d4cdc5a034bf',
'70fe1812-e1de-447b-ac4f-d89fead4756d'
]
我试着用
r.table('periods')['regions']['sites']['plants']['product']['process']['technologies'].run()
但它给出了错误“无法对序列序列执行括号”。
=> 是否有一些替代运算符可以为每个步骤获取合并序列而不是“序列序列”？
就像是
r.table('periods').unwind('regions.sites.plants.product.process.technologies')
这是一些用于创建示例数据的 python 代码：
from rethinkdb import RethinkDB
r = RethinkDB()
r.connect({}).repl()
r.table_create("periods")
def uniqueid():
return r.uuid().run()
periodid_first = uniqueid()
periodid_second = uniqueid()
companyid_2000 = uniqueid()
companyid_2001 = uniqueid()
technologyid_2000_first = uniqueid()
technologyid_2000_second = uniqueid()
technologyid_2001_first = uniqueid()
technologyid_2001_second = uniqueid()
energy_carrierid_2000_first = uniqueid()
energy_carrierid_2000_second = uniqueid()
energy_carrierid_2001_first = uniqueid()
energy_carrierid_2001_second = uniqueid()
periods = [
{
'id': periodid_first,
'start': 2000,
'end': 2000,
# 'sub_periods': [],
'regions': [
{
'id': 'DE',
# 'sub_regions': [],
'sites': [
{
'id': 'first_site_in_germany',
'company': companyid_2000, # => verweist auf periods => companies
'plants': [
{
'id': 'qux',
'product': {
'id': 'Ammoniak',
'process': {
'id': 'SMR+HB',
'technologies': [
technologyid_2000_first, # => verweist auf periods => technologies
technologyid_2000_second
]
}
}
}
]
}
]
},
{
'id': 'FR',
# 'sub_regions': [],
'sites': [
{
'id': 'first_site_in_france',
'company': companyid_2000, # => verweist auf periods => companies
'plants': [
{
'id': 'qux',
'product': {
'id': 'Ammoniak',
'process': {
'id': 'SMR+HB',
'technologies': [
technologyid_2000_first, # => verweist auf periods => technologies
technologyid_2000_second
]
}
}
}
]
}
]
}
],
'companies': [
{
'id': companyid_2000,
'name': 'international_company'
}
],
'technologies': [
{
'id': technologyid_2000_first,
'name': 'SMR',
'specific_cost_per_year': 123,
'specific_energy_consumptions': [
{
'energy_carrier': energy_carrierid_2000_first,
'specific_consumption': 5555
}, # => verweist auf periods => energy_carriers
{
'energy_carrier': energy_carrierid_2000_second,
'energy_consumption': 2333
}
]
},
{
'id': technologyid_2000_second,
'name': 'HB',
'specific_cost_per_year': 1234,
'specific_energy_consumptions': [
{
'energy_carrier': energy_carrierid_2000_first,
'specific_consumption': 555
}, # => verweist auf periods => energy_carriers
{
'energy_carrier': energy_carrierid_2000_second,
'energy_consumption': 233
}
]
}
],
'energy_carriers': [
{
'id': energy_carrierid_2000_first,
'name': 'oil',
'group': 'fuel'
},
{
'id': energy_carrierid_2000_second,
'name': 'gas',
'group': 'fuel'
},
{
'id': uniqueid(),
'name': 'conventional',
'group': 'electricity'
},
{
'id': uniqueid(),
'name': 'green',
'group': 'electricity'
}
],
'networks': [
{
'id': uniqueid(),
'name': 'gas',
'sub_networks': [],
'pipelines': [
]
},
{
'id': uniqueid(),
'name': 'gas',
'sub_networks': [],
'pipelines': [
]
}
]
},
{
'id': periodid_second,
'start': 2001,
'end': 2001,
# 'sub_periods': [],
'regions': [
{
'id': 'DE',
# 'sub_regions': [],
'sites': [
{
'id': 'first_site_in_germany',
'company': companyid_2001, # => verweist auf periods => companies
'plants': [
{
'id': 'qux',
'product': {
'id': 'Ammoniak',
'process': {
'id': 'SMR+HB',
'technologies': [
technologyid_2001_first, # => verweist auf periods => technologies
technologyid_2001_second
]
}
}
}
]
}
]
},
{
'id': 'FR',
# 'sub_regions': [],
'sites': [
{
'id': 'first_site_in_france',
'company': companyid_2001, # => verweist auf periods => companies
'plants': [
{
'id': 'qux',
'product': {
'id': 'Ammoniak',
'process': {
'id': 'SMR+HB',
'technologies': [
technologyid_2001_first, # => verweist auf periods => technologies
technologyid_2001_second
]
}
}
}
]
}
]
}
],
'companies': [
{
'id': companyid_2001,
'name': 'international_company'
}
],
'technologies': [
{
'id': technologyid_2001_first,
'name': 'SMR',
'specific_cost_per_year': 123,
'specific_energy_consumptions': [
{
'energy_carrier': energy_carrierid_2001_first,
'specific_consumption': 5555
}, # => verweist auf periods => energy_carriers
{
'energy_carrier': energy_carrierid_2001_second,
'energy_consumption': 2333
}
]
},
{
'id': technologyid_2001_second,
'name': 'HB',
'specific_cost_per_year': 1234,
'specific_energy_consumptions': [
{
'energy_carrier': energy_carrierid_2001_first,
'specific_consumption': 555
}, # => verweist auf periods => energy_carriers
{
'energy_carrier': energy_carrierid_2001_second,
'energy_consumption': 233
}
]
}
],
'energy_carrieriers': [
{
'id': energy_carrierid_2001_first,
'name': 'oil',
'group': 'fuel'
},
{
'id': energy_carrierid_2001_second,
'name': 'gas',
'group': 'fuel'
},
{
'id': uniqueid(),
'name': 'conventional',
'group': 'electricity'
},
{
'id': uniqueid(),
'name': 'green',
'group': 'electricity'
}
],
'networks': [
{
'id': uniqueid(),
'name': 'gas',
'sub_networks': [],
'pipelines': [
]
},
{
'id': uniqueid(),
'name': 'gas',
'sub_networks': [],
'pipelines': [
]
}
]
}
]
r.table('periods') \
.insert(periods) \
.run()
有关的：
解决方案
嵌套的concat_map结合r.row运算符和括号向下钻取可以解决问题：
r.table('periods') \
.concat_map(r.row['regions']) \
.concat_map(r.row['sites']) \
.concat_map(r.row['plants'])['product']['process'] \
.concat_map(r.row['technologies']) \
.run()