Dataford
Interview QuestionsInterview GuidesExperiencesCoaching
New
Pricing
Get started
Dataford
Popular roles
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Browse
Browse All RolesEvery role hub, from analyst to MLBrowse All CompaniesCompany-specific interview loopsAll Interview GuidesThe full guide library
Top questions by role
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Top questions by skill
SQLPythonStatisticsMachine LearningA/B TestingSystem DesignGenerative AIProduct SenseMetricsBehavioral
Browse all questions →Try a mock interview
Experiences
Practice
Mock InterviewsTimed interview simulations with feedbackCoaching1:1 coaching with people at your target companiesSuccess PathYour 6-week structured planModulesCurated lessons by topicWebinarsTalks from ex-Big Tech data leadsPlaygroundA free-form scratch editor
Learn
BlogInterview strategy and career adviceTech Job Market ReportHiring trends across data and AI rolesFor UniversitiesDataford for career centersAbout DatafordWho we are and how we build
Pricing
Build my plan
Aggregate Error Codes from Logs
00:00
5 left

Aggregate Error Codes from Logs

EasyPython

Problem

Given an array of log lines logs and an array of target error codes target_codes, return a dictionary mapping each target error code to the number of times it appears in the logs. A valid error code appears in the form ERROR_CODE=<code> within a log line. Ignore malformed lines and codes not present in target_codes.

Constraints

  • 1 <= len(logs) <= 10^5
  • 1 <= len(target_codes) <= 10^4
  • 1 <= len(logs[i]) <= 10^3
  • Target codes are unique strings
  • A valid code appears as ERROR_CODE=<code> and ends at the next space or end of line

Function Signature

def aggregate_error_codes(logs, target_codes):
Interviewer

Your question is Aggregate Error Codes from Logs. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

You need to log in / sign up to run or submit.
CodePython 3
Sign up free to run your codeLog inLn 2
Run your code to see test output here.