Question

我有两个哈希数组：

actual = [{"column_name"=>"NONINTERESTINCOME", "column_data_type"=>"NUMBER"},
 {"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"VARCHAR"},
 {"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"TIMESTAMP"},
 {"column_name"=>"UPDATEDATE", "column_data_type"=>"TIMESTAMP"}]
expected = [{"column_name"=>"NONINTERESTINCOME", "column_data_type"=>"NUMBER"},
 {"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"NUMBER"},
 {"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"NUMBER"},
 {"column_name"=>"UPDATEDATE", "column_data_type"=>"TIMESTAMP"}]

我需要比较这两个哈希值，找出column_data_type不同的哈希值。

比较我们可以直接使用：

diff = actual -   expected

这会将输出打印为：

{"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"VARCHAR"}
{"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"TIMESTAMP"}

我的预期输出是在结果中我想打印实际和预期的数据类型，表示实际和预期的哈希数组中缺少的`column_name'的数据类型，如：

{"column_name"=>"NONINTERESTEXPENSE", "expected_column_data_type"=>"NUMBER", "actual_column_data_type" => "VARCHAR"}
{"column_name"=>"TRANSACTIONDATE", "expected_column_data_type"=>"NUMBER","actual_column_data_type" => "TIMESTAMP" }

Answer 1

无论数组中的哈希顺序如何，这都可以正常工作。

diff = []

expected.each do |elem|
  column_name = elem['column_name']
  column_type = elem['column_data_type']
  match = actual.detect { |elem2| elem2['column_name'] == column_name  }
  if column_type != match['column_data_type']
    diff << { 'column_name' => column_name,
              'expected_column_data_type' => column_type,
              'actual_column_data_type' => match['column_data_type'] }
  end
end

p diff

Answer 2

[actual, expected].map { |a| a.map(&:dup).map(&:values) }
                  .map(&Hash.method(:[]))
                  .reduce do |actual, expected|
                    actual.merge(expected) do |k, o, n|
                      o == n ? nil : {name: k, actual: o, expected: n}
                    end
                  end.values.compact

#⇒ [
#    [0] {
#            :name => "NONINTERESTEXPENSE",
#          :actual => "VARCHAR",
#        :expected => "NUMBER"
#    },
#    [1] {
#            :name => "TRANSACTIONDATE",
#          :actual => "TIMESTAMP",
#        :expected => "NUMBER"
#    }
# ]

上述方法可轻松扩展以合并N个数组（使用reduce.with_index和merge使用键"value_from_#{idx}"。）

Answer 3

这个怎么样？

def select(hashes_array, column_name)
  hashes_array.select { |h| h["column_name"] == column_name }.first
end

diff = (expected - actual).map do |h|
  {
    "column_name" => h["column_name"],
    "expected_column_data_type" => select(expected, h["column_name"])["column_data_type"],
    "actual_column_data_type" => select(actual, h["column_name"])["column_data_type"],
  }
end

PS：肯定这段代码可以改进，看起来更优雅

Answer 4

(expected - actual).
  concat(actual - expected).
  group_by { |column| column['column_name'] }.
  map do |name, (expected, actual)|
    {
      'column_name'               => name,
      'expected_column_data_type' => expected['column_data_type'],
      'actual_column_data_type'   => actual['column_data_type'],
    }
  end

Answer 5

<强>代码

def convert(actual, expected)
  hashify(actual-expected, "actual_data_type").
  merge(hashify(expected-actual, "expected_data_type")) { |_,a,e| a.merge(e) }.values
end

def hashify(arr, key)
  arr.each_with_object({}) { |g,h| h[g["column_name"]] =
    { "column_name"=>g["column_name"], key=>g["column_data_type"] } }
end

示例

actual = [ {"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"TIMESTAMP"}, {"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"VARCHAR"}, {"column_name"=>"NONINTERESTINCOME", "column_data_type"=>"NUMBER"}, {"column_name"=>"UPDATEDATE", "column_data_type"=>"TIMESTAMP"} ] expected = [ {"column_name"=>"NONINTERESTINCOME", "column_data_type"=>"NUMBER"}, {"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"NUMBER"}, {"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"NUMBER"}, {"column_name"=>"UPDATEDATE", "column_data_type"=>"TIMESTAMP"} ] convert(actual, expected) #=> [{"column_name"=>"TRANSACTIONDATE", # "actual_data_type"=>"TIMESTAMP", "expected_data_type"=>"NUMBER"}, # {"column_name"=>"NONINTERESTEXPENSE", # "actual_data_type"=>"VARCHAR", "expected_data_type"=>"NUMBER"}]

<强>解释

对于上面的例子，步骤如下。

首先hashify actual和expected。

f = actual-expected #=> [{"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"TIMESTAMP"}, # {"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"VARCHAR"}] g = hashify(f, "actual_data_type") #=> {"TRANSACTIONDATE"=>{"column_name"=>"TRANSACTIONDATE", # "actual_data_type"=>"TIMESTAMP"}, # "NONINTERESTEXPENSE"=>{ "column_name"=>"NONINTERESTEXPENSE", # "actual_data_type"=>"VARCHAR"}} h = expected-actual #=> [{"column_name"=>"NONINTERESTEXPENSE", "column_data_type"=>"NUMBER"}, # {"column_name"=>"TRANSACTIONDATE", "column_data_type"=>"NUMBER"}] i = hashify(h, "expected_data_type") #=> {"NONINTERESTEXPENSE"=>{"column_name"=>"NONINTERESTEXPENSE", # "expected_data_type"=>"NUMBER"}, # "TRANSACTIONDATE"=>{"column_name"=>"TRANSACTIONDATE", # "expected_data_type"=>"NUMBER"}}

下一次合并g和i使用Hash#merge的形式，它使用一个块来确定合并的两个哈希中存在的键的值。请参阅doc以了解三个块变量的定义（第一个是公共密钥，我用下划线表示，表示它未在块计算中使用）。

j = g.merge(i) { |_,a,e| a.merge(e) } #=> {"TRANSACTIONDATE"=>{"column_name"=>"TRANSACTIONDATE", # "actual_data_type"=>"TIMESTAMP", "expected_data_type"=>"NUMBER"}, # "NONINTERESTEXPENSE"=>{"column_name"=>"NONINTERESTEXPENSE", # "actual_data_type"=>"VARCHAR", "expected_data_type"=>"NUMBER"}}

最后，放下钥匙。

k = j.values #=> [{"column_name"=>"TRANSACTIONDATE", "actual_data_type"=>"TIMESTAMP", # "expected_data_type"=>"NUMBER"}, # {"column_name"=>"NONINTERESTEXPENSE", "actual_data_type"=>"VARCHAR", # "expected_data_type"=>"NUMBER"}]

比较哈希的数组和打印期望＆amp;实际结果

5 个答案: