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The first one: If the first value is unique under the same type, then you can try the following structure:

value = '1：n：1'
mapping = defaultdict(dict)
value_type, fir_val, sec_val = value.split(':')
mapping = {
    value_type: {
        fir_val: sec_val 
    }
}

The above means that creating a default value 字典的字典mapping, 然后用類型和第一個值分別作為索引的key, 我個人覺得, 在類型和第一個值的共同約束下, 找到的第二個值should be unique. If it is not unique, then you need to consider whether to overwrite it or exist in the form of a list

Second:
If you use the data structure I mentioned above, then without knowing the first value, you can only traverse mapping[value_type], and then determine whether the value is what you want

What does 1:n:1 mean? Mapping relationship? But this is not important. I have a simple and crude way to write each piece of data as a 3-tuple (type, val1, val2), and then save each piece of data into an array [];
Under construction When making an array, make 3 dicts, typeDict = {type: [arrIdx]}, val1Dict={val1:[arrIdx]}, val2Dict={val2:[arrIdx]}
When you want to use type to find data, just use typeDict from Find all record locations corresponding to type.
Similarly, val1 and val2 are the same.
When you want to find typeA, val1=n, you only need to intersect the result sets found from typeDict, val1Dict.

If there is a large amount of data, it seems that it would be more efficient to use a database such as mysql or pandas that specializes in data processing. Pandas also has a dedicated to_dict function.