Real-time Crawlers - Interview Task

Note: The contents of this file were originally provided by the company as part of the interview task description. If you're looking for my solution to the task, please refer to README_SOLUTION.md

Requirements

• docker >=23.0.5
• docker-compose >=2.24.6

How to run

To start the application, run docker-compose up command. The API will then be accessible on port 3000.

Guidelines

1. Please clone / fork this project and share your solution with a link to your repository (e.g. GitHub, GitLab, BitBucket) as we would like you to see your progress (your commit history is important).
2. Keep your solution and code as simple and readable as possible. The fewer external libraries you use, the better.
3. Use the best coding practices you know. We will evaluate the quality of your code, the structure of your application, and the correctness of the solution.
4. Your application should run without any additional infrastructure like external database (you can store the application state in memory).
5. Focus on running and verifying your application along with provided simulation. At the end we expect your application require only our simulation to work.
6. Please do not remove our simulation service definition from docker-compose.yml file. You can add your solution as additional service definition if you want.
7. Don't forget to include the information about how to run / debug your coding task implementation. Please keep the process as simple as possible and describe it in the new file README_SOLUTION.md. Please do not delete original README.md file.

Task and requirements description

You are given an API that exposes simulated data about sport events. A sport event is a match between two competitors e.g. FC Barcelona vs. Real Madrid. The simulation runs in 5-minute cycles. After each cycle, the state on the simulation side is cleaned up, and the simulation restarts with a new set of sports events and mappings.

• During a simulation the following properties of a sport event can change:

1. Event score - one of the competitors can score a goal. Score is divided into different period types: CURRENT, PERIOD_X.
2. Event status - when simulation starts every sport event has PRE status, during the simulation it is changed to LIVE.

• Your task is to implement a TypeScript application that:

1. Constantly consumes data from the simulation API using /api/state endpoint. API calls have to be executed at a frequency of 1000 ms.
2. Fetches and applies mappings from the simulation API using /api/mappings endpoint. Mappings are used to replace unique ids with a corresponding name.
3. Exposes an endpoint /client/state returning your application's internal state reflecting the current state of the ongoing simulation. Response format should be JSON.

• Additional requirements:

1. When a sport event is finished it won't be returned from the simulation API any longer. However, your application's state should still contain such sport event with a status set to REMOVED.
2. Events with status REMOVED should not be exposed by your application's API.
3. Your application should log score and status property change for each sport event (with information about old and new value).
4. If some sport event property mapping can't be resolved, skip processing that sport event and make sure such error is logged with all the necessary information.

Example response from your application API should look like the following:

{
  "3eccf850-571f-4e18-8cb3-2c9e3afade7b": {
    "id": "3eccf850-571f-4e18-8cb3-2c9e3afade7b",
    "status": "LIVE",
    "scores": {
      "CURRENT": {
        "type": "CURRENT",
        "home": "0",
        "away": "0"
      }
    },
    "startTime": "2024-03-04T10:36:07.812Z",
    "sport": "FOOTBALL",
    "competitors": {
      "HOME": {
        "type": "HOME",
        "name": "Juventus"
      },
      "AWAY": {
        "type": "AWAY",
        "name": "Paris Saint-Germain"
      }
    },
    "competition": "UEFA Champions League"
  }
}

Simulation API Specification

GET /api/state

Returns a current state of the simulation.

Endpoint schema

{
    odds: string
}

The odds field contains encoded information about sport events in a current simulation cycle:

1. Sport events are delimited by a new line character: \n
2. A specific fields of an sport event are delimited by a comma character , (check API Data format section below).

Example response

{"odds":"995e0722-4118-4f8e-a517-82f6ea240673,c0a1f678-dbe5-4cc8-aa52-8c822dc65267,7ee17545-acd2-4332-869b-1bef06cfaec8,1709900432183,29190088-763e-4d1c-861a-d16dbfcf858c,3cd8eeee-a57c-48a3-845f-93b561a95782,ac68a563-e511-4776-b2ee-cd395c7dc424,\n4bb7b78f-6a23-43d0-a61a-1341f03f64e0,c0a1f678-dbe5-4cc8-aa52-8c822dc65267,194e22c6-53f3-4f36-af06-53f168ebeee8,1709900380135,d6fdf482-8151-4651-92c2-16e9e8ea4b8b,b582b685-e75c-4139-8274-d19f078eabef,7fa4e60c-71ad-4e76-836f-5c2bc6602156,e2d12fef-ae82-4a35-b389-51edb8dc664e@1:2|6c036000-6dd9-485d-97a1-e338e6a32a51@1:2\nfd903e06-9a7d-423d-8869-1c060cc0b62d,c0a1f678-dbe5-4cc8-aa52-8c822dc65267,7ee17545-acd2-4332-869b-1bef06cfaec8,1709900348483,a950b22c-989b-402f-a1ac-70df8f102e27,5dbdb683-c15f-4d79-a348-03cf2861b954,7fa4e60c-71ad-4e76-836f-5c2bc6602156,e2d12fef-ae82-4a35-b389-51edb8dc664e@1:3|6c036000-6dd9-485d-97a1-e338e6a32a51@1:3\n449a2d53-4845-4a59-9596-4206f2504656,c0a1f678-dbe5-4cc8-aa52-8c822dc65267,7ee17545-acd2-4332-869b-1bef06cfaec8,1709900494110,f0c6f8b4-8fbc-4022-95b3-c68bca32adb9,33ff69aa-c714-470c-b90d-d3883c95adce,ac68a563-e511-4776-b2ee-cd395c7dc424,\n4c6d6c9d-2b47-433d-b2ad-a82cff214805,c0a1f678-dbe5-4cc8-aa52-8c822dc65267,28cb12c0-2542-4790-b66b-e51b9cb30c76,1709900417851,4df1b17c-3bfe-4bbb-8b60-12661c2bb190,7229b223-03d6-4285-afbf-243671088a20,ac68a563-e511-4776-b2ee-cd395c7dc424,\nb874daa4-0ee2-4030-83ac-8bf70100dbb6,c72cbbc8-bac9-4cb7-a305-9a8e7c011817,28cb12c0-2542-4790-b66b-e51b9cb30c76,1709900404465,44bc5cb3-19c0-4f35-8ac6-100cfecf70f1,98841461-0442-4dbb-ae53-2e039bbecad2,7fa4e60c-71ad-4e76-836f-5c2bc6602156,e2d12fef-ae82-4a35-b389-51edb8dc664e@0:0|6c036000-6dd9-485d-97a1-e338e6a32a51@0:0\na32247cb-70a7-4d7b-a69d-37a98a512687,c72cbbc8-bac9-4cb7-a305-9a8e7c011817,194e22c6-53f3-4f36-af06-53f168ebeee8,1709900431402,9012f4c9-1d9c-4137-a60d-94b853972c7e,3138f71d-16f2-46b6-9812-d62e3fa6f981,ac68a563-e511-4776-b2ee-cd395c7dc424,\naf5d53e6-b108-48ce-b3e9-fce1c94af6c4,c72cbbc8-bac9-4cb7-a305-9a8e7c011817,7ee17545-acd2-4332-869b-1bef06cfaec8,1709900352422,259ba76d-189f-420f-be50-0aac633c2153,6acec751-8fc4-4c44-8798-1182699869d0,7fa4e60c-71ad-4e76-836f-5c2bc6602156,e2d12fef-ae82-4a35-b389-51edb8dc664e@1:1|6c036000-6dd9-485d-97a1-e338e6a32a51@1:1|2db8bc38-b46d-4bd9-9218-6f8dbe083517@0:0\n1e9d8eee-e6a7-44c2-ad21-45f6f6d0f646,c72cbbc8-bac9-4cb7-a305-9a8e7c011817,c3215a44-efdb-49fb-9f01-85b26c57bbd4,1709900497047,d34032e0-0e81-4166-8ced-dd8fd6222fcb,e476746c-869d-4aa5-a292-587730514aae,ac68a563-e511-4776-b2ee-cd395c7dc424,\nb2ec3d30-e156-42dd-9074-61681eecd382,c72cbbc8-bac9-4cb7-a305-9a8e7c011817,7ee17545-acd2-4332-869b-1bef06cfaec8,1709900423377,d3fa6d41-af8c-45d1-848c-891ca86731f1,b98bab75-53d3-494e-a3a9-b9d1dd1fb458,ac68a563-e511-4776-b2ee-cd395c7dc424,"}

NOTES:

• With every new simulation cycle a new set of sports events is served

GET /api/mappings

Returns the dictionary used for mapping sport event properties (sport names, competitions, statuses, score period types) to their unique IDs.

Endpoint schema

{
    mappings: string
}

The mappings field has the following format:

id1:value1;id2:value2;idN:valueN...

Example response

{"mappings":"29190088-763e-4d1c-861a-d16dbfcf858c:Real Madrid;33ff69aa-c714-470c-b90d-d3883c95adce:Barcelona;b582b685-e75c-4139-8274-d19f078eabef:Manchester United;4df1b17c-3bfe-4bbb-8b60-12661c2bb190:Liverpool;3cd8eeee-a57c-48a3-845f-93b561a95782:Bayern Munich;a950b22c-989b-402f-a1ac-70df8f102e27:Paris Saint-Germain;5dbdb683-c15f-4d79-a348-03cf2861b954:Juventus;7229b223-03d6-4285-afbf-243671088a20:Chelsea;d6fdf482-8151-4651-92c2-16e9e8ea4b8b:Manchester City;f0c6f8b4-8fbc-4022-95b3-c68bca32adb9:AC Milan;6acec751-8fc4-4c44-8798-1182699869d0:Los Angeles Lakers;9012f4c9-1d9c-4137-a60d-94b853972c7e:Golden State Warriors;44bc5cb3-19c0-4f35-8ac6-100cfecf70f1:Miami Heat;e476746c-869d-4aa5-a292-587730514aae:Chicago Bulls;259ba76d-189f-420f-be50-0aac633c2153:Boston Celtics;98841461-0442-4dbb-ae53-2e039bbecad2:Houston Rockets;3138f71d-16f2-46b6-9812-d62e3fa6f981:Toronto Raptors;b98bab75-53d3-494e-a3a9-b9d1dd1fb458:Dallas Mavericks;d3fa6d41-af8c-45d1-848c-891ca86731f1:Brooklyn Nets;d34032e0-0e81-4166-8ced-dd8fd6222fcb:Denver Nuggets;c3215a44-efdb-49fb-9f01-85b26c57bbd4:UEFA Champions League;7ee17545-acd2-4332-869b-1bef06cfaec8:UEFA Europa League;28cb12c0-2542-4790-b66b-e51b9cb30c76:NBA;194e22c6-53f3-4f36-af06-53f168ebeee8:NBA - pre-season;c0a1f678-dbe5-4cc8-aa52-8c822dc65267:FOOTBALL;c72cbbc8-bac9-4cb7-a305-9a8e7c011817:BASKETBALL;ac68a563-e511-4776-b2ee-cd395c7dc424:PRE;7fa4e60c-71ad-4e76-836f-5c2bc6602156:LIVE;cb807d14-5a98-4b41-8ddc-74a1f5f80f9b:REMOVED;e2d12fef-ae82-4a35-b389-51edb8dc664e:CURRENT;6c036000-6dd9-485d-97a1-e338e6a32a51:PERIOD_1;2db8bc38-b46d-4bd9-9218-6f8dbe083517:PERIOD_2;0cfb491c-7d09-4ffc-99fb-a6ee0cf5d198:PERIOD_3;5a79d3e7-85b3-4d6b-b4bf-ddd743e7162f:PERIOD_4"}

NOTES:

• With every simulation cycle a new set of mappings is served

Simulation API Data Format

Sport Event

Position	Value	Note
0	Sport Event ID
1	Sport ID
2	Competition ID
3	Start time
4	Home Competitor ID
5	Away Competitor ID
6	Sport Event Status ID
7	Scores	Score periods are delimited by | character and have period@home_score:away_score format