In C#: How to declare a generic Dictionary with a type as key and an IEnumerable of that type as value?

Use System.ComponentModel.Design.ServiceContainer that is already available in .Net framework. ServiceContainer container = new ServiceContainer(); IList<int> integers = new List<int>(); IList<string> strings = new List<string>(); IList<double> doubles = new List<double>(); container.AddService(typeof(IEnumerable<int>), integers); container.AddService(typeof(IEnumerable<string>), strings); container.AddService(typeof(IEnumerable<double>), doubles);

Java invert map

The values in a map may not be unique. But if they are (in your case) you can do as you wrote in your question and create a generic method to convert it: private static <V, K> Map<V, K> invert(Map<K, V> map) { Map<V, K> inv = new HashMap<V, K>(); for (Entry<K, V> entry : … Read more

python dict.update() equivalent in javascript

You can use the destructuring assignment. const first_dict = { ‘key_one’: ‘value_one’, ‘key_two’: ‘value_two’ } const second_dict = { ‘key_one’: ‘value_from_second_dict’, ‘key_three’: ‘value_three’ } const accumulative = { …first_dict, …second_dict } console.log(accumulative) /* [object Object] { key_one: “value_from_second_dict”, key_three: “value_three”, key_two: “value_two” } */

Create a dictionary by zipping together two lists of uneven length [duplicate]

Use itertools.cycle to cycle around to the beginning of L2: from itertools import cycle dict(zip(L1, cycle(L2))) # {‘A’: ‘1’, ‘B’: ‘2’, ‘C’: ‘3’, ‘D’: ‘1’, ‘E’: ‘2’} In your case, concatenating L2 with itself also works. # dict(zip(L1, L2 * 2)) dict(zip(L1, L2 + L2)) # {‘A’: ‘1’, ‘B’: ‘2’, ‘C’: ‘3’, ‘D’: ‘1’, ‘E’: … Read more

Merging two CSV files using Python

When I’m working with csv files, I often use the pandas library. It makes things like this very easy. For example: import pandas as pd a = pd.read_csv(“filea.csv”) b = pd.read_csv(“fileb.csv”) b = b.dropna(axis=1) merged = a.merge(b, on=’title’) merged.to_csv(“output.csv”, index=False) Some explanation follows. First, we read in the csv files: >>> a = pd.read_csv(“filea.csv”) >>> … Read more

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