CODEWITHSUNDEEP
python-3.7dictionary-comprehension
NewToThis
NewToThis

Reputation: 413

Generate list of values, based on matching keys

I have the below dictionary:

{'Closed': {'High': 33, 'Medium': 474, 'Low': 47, 'Critical': 6}, 'Impact Statement Pending': {'Low': 3, 'Medium': 1, 'Critical': 0, 'High': 0}, 'New': {'Low': 1, 'High': 2, 'Critical': 2, 'Medium': 2}, 'Remediation Plan Pending': {'Medium': 10, 'Low': 1, 'Critical': 1, 'High': 0}, 'Remedy in Progress': {'Medium': 36, 'Low': 18, 'High': 4, 'Critical': 1}}

How might I accomplish creating a list comprised of all values for a specified key? A list for all high values, or another list for all medium values?

The way I am currently accomplishing this doesn't seem like the best way. I've got a list of all severity levels, which I iterate over and compare such as shown below:

trace_list = ['High', 'Medium', 'Critical', 'Low']

total_status_dict = {'Closed': {'High': 33, 'Medium': 474, 'Low': 47, 'Critical': 6}, 'Impact Statement Pending': {'Low': 3, 'Medium': 1, 'Critical': 0, 'High': 0}, 'New': {'Low': 1, 'High': 2, 'Critical': 2, 'Medium': 2}, 'Remediation Plan Pending': {'Medium': 10, 'Low': 1, 'Critical': 1, 'High': 0}, 'Remedy in Progress': {'Medium': 36, 'Low': 18, 'High': 4, 'Critical': 1}}

for item in trace_labels:

     y_values = []

     for key, val in total_status_dict.items():
          for ke in total_status_dict[key]:
               if item is ke:
                    y_values.append(total_status_dict[key][ke])

Upvotes: 0

Views: 134

Answers (1)

jferard
jferard

Reputation: 8190

Note: you are iterating over total_status_dict keys and appending results to a list. Remember that even if dictionaries are officially ordered in Python since 3.7 (see https://docs.python.org/3/whatsnew/3.7.html) you do not always control the Python version of the user. I would rather build a dict key -> item -> value, where key is Closed, Impact Statement Pending, ... and  item is one of the trace_labels than a dict key -> [values] where values is supposed to be ordered as in trace_labels.

Your code is not efficient because you iterate over trace_labels twice:

  • for item in trace_labels:
  • for ke intotal_status_dict[key]: if item is ke:`

How to iterate only once? Instead of building y_values lists one by one (with a whole iteration over total_status_dict each time), you can build several lists at once:

>>> trace_labels = ['High', 'Medium', 'Critical', 'Low']
>>> total_status_dict = {'Closed': {'High': 33, 'Medium': 474, 'Low': 47, 'Critical': 6}, 'Impact Statement Pending': {'Low': 3, 'Medium': 1, 'Critical': 0, 'High': 0}, 'New': {'Low': 1, 'High': 2, 'Critical': 2, 'Medium': 2}, 'Remediation Plan Pending': {'Medium': 10, 'Low': 1, 'Critical': 1, 'High': 0}, 'Remedy in Progress': {'Medium': 36, 'Low': 18, 'High': 4, 'Critical': 1}}
>>> y_values_by_label = {}
>>> for key, value_by_label in total_status_dict.items():
...     for label, value in value_by_label.items(): # total_status_dict[key] is value_by_label
...         y_values_by_label.setdefault(label, {})[key] = value
...
>>> y_values_by_label
{'High': {'Closed': 33, 'Impact Statement Pending': 0, 'New': 2, 'Remediation Plan Pending': 0, 'Remedy in Progress': 4}, 'Medium': {'Closed': 474, 'Impact Statement Pending': 1, 'New': 2, 'Remediation Plan Pending': 10, 'Remedy in Progress': 36}, 'Low': {'Closed': 47, 'Impact Statement Pending': 3, 'New': 1, 'Remediation Plan Pending': 1, 'Remedy in Progress': 18}, 'Critical': {'Closed': 6, 'Impact Statement Pending': 0, 'New': 2, 'Remediation Plan Pending': 1, 'Remedy in Progress': 1}}

setdefault(label, {}) creates a empty dict y_values_by_label[label] = {} if y_values_by_label does not have the key label.

If you want to turn this in a dict comprehension, you have to use your inefficient method:

>>> {label:{k:v for k, value_by_label in total_status_dict.items() for l, v in value_by_label.items() if l==label} for label in trace_labels}
{'High': {'Closed': 33, 'Impact Statement Pending': 0, 'New': 2, 'Remediation Plan Pending': 0, 'Remedy in Progress': 4}, 'Medium': {'Closed': 474, 'Impact Statement Pending': 1, 'New': 2, 'Remediation Plan Pending': 10, 'Remedy in Progress': 36}, 'Critical': {'Closed': 6, 'Impact Statement Pending': 0, 'New': 2, 'Remediation Plan Pending': 1, 'Remedy in Progress': 1}, 'Low': {'Closed': 47, 'Impact Statement Pending': 3, 'New': 1, 'Remediation Plan Pending': 1, 'Remedy in Progress': 18}}

Upvotes: 1

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