WebCamp Ukraine 2016: Instant messenger with Python. Back-end development
•
1 like•2,306 views
This document discusses building instant messaging platforms with Python. It covers common messaging protocols like XMPP and WebSocket, how they establish and send messages. It also discusses the life of a messaging platform, including authentication, delivery, parsing, and more. Lessons learned include handling bursty traffic, reconnect storms, and preventing incidents. Python is well-suited for messaging backends but other languages may be better for some tasks.
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (16)
Similar to WebCamp Ukraine 2016: Instant messenger with Python. Back-end development
Similar to WebCamp Ukraine 2016: Instant messenger with Python. Back-end development (20)
Recently uploaded
Recently uploaded (20)
WebCamp Ukraine 2016: Instant messenger with Python. Back-end development
- 1. Instant messenger with Python Back-end development Viacheslav Kakovskyi WebCamp 2016
- 2. Me! @kakovskyi Python Developer at SoftServe Contributor of Atlassian HipChat — Python 2, Twisted Maintainer of KPIdata — Python 3, asyncio 2
- 3. Agenda ● What is 'instant messenger'? ● Related projects from my experience ● Messaging protocols ● Life of messaging platform ● Lessons learned ● Summary ● Further reading 3
- 4. What is 'instant messenger'? 4
- 5. What is 'instant messenger'? ● online chat ● real-time delivery ● short messages 5
- 6. What is 'instant messenger'? ● history search ● file sharing ● mobile push notifications ● video calling ● bots and integrations 6
- 7. Related projects from my experience ● Hosted chat for teams and enterprises ● Founded in 2009 by 3 students ● 100 000+ connected users ● 100+ nodes ● REST API for integrations and bots ● Built with Python 2 and Twisted 7
- 8. Messaging protocols Protocol is about: ● Message format ● Allowed types of messages ● Limitations ● Routine ○ How to encode data? ○ How to establish/close connection? ○ How to authenticate? ○ How to encrypt? 8
- 9. Messaging protocols ● OSCAR (1997) ● XMPP (1999) ● Skype (2003) ● WebSocket-based (2011) ● MQTT, MTProto, DHT-based, etc. 9
- 10. XMPP ● XMPP - signaling protocol ● BOSH - transport protocol ● Started from Jabber in 1999 ● XML as a message format ● Stanza - basic unit in XMPP ● Types of stanzas: ○ Message ○ Presence ○ Info/Query 10
- 11. XMPP ● Extensions defined by XEPs (XMPP Extension Protocols): ○ Bidirectional-streams Over Synchronous HTTP (BOSH) ○ Serverless messaging ○ File transfer and etc. 11
- 12. XMPP: Establishing a connection 12 Client: <?xml version='1.0'?> <stream:stream to='example.com' xmlns='jabber:client' xmlns:stream='http://etherx.jabber.org/streams' version='1.0'> Server: <?xml version='1.0'?> <stream:stream from='example.com' id='someid' xmlns='jabber:client' xmlns:stream='http://etherx.jabber. org/streams' version='1.0'>
- 13. XMPP: Sending a message 13 Client: <message from='juliet@example.com' to='romeo@example.net' xml:lang='en'> <body>Art thou not Romeo, and a Montague?</body> </message> Server: <message from='romeo@example.net' to='juliet@example.com' xml: lang='en'> <body> Neither, fair saint, if either thee dislike. </body> </message>
- 14. XMPP: Closing a connection 14 Client: </stream:stream> Server: </stream:stream>
- 15. XMPP: Pros ● Robust and standardized ● Extendable via XEPs ● Secured ● Native support of multi-sessions ● A lot of clients implementations 15
- 16. XMPP: Cons ● Overhead ○ Presence ○ Downloading the World on startup ● XML ○ Large documents ○ Expensive parsing 16
- 17. XMPP and Python ● Servers: ○ TwistedWords - good place to start ○ Tornado-based example ○ aioxmpp ○ XMPPFlask ○ Punjab - BOSH-server on Twisted 17
- 18. XMPP and Python ● Clients: ○ SleekXMPP - mature and solid ○ Slixmpp - asyncio-support ○ TwistedWords ○ Wokkel - Twisted-based ○ xmpp.py ● JS-client: Strophe.js 18
- 19. WebSocket-based solutions ● WebSocket - transport protocol ● Standardized in 2011 by W3C ● Full-duplex communication channel ● JSON as a message format ● Custom message types 19
- 20. WebSocket: Establishing a connection 20 Client: GET /chat HTTP/1.1 Host: server.example.com Upgrade: websocket Connection: Upgrade Sec-WebSocket-Key: dGhlIHNhbXBsZSBub25jZQ== Origin: http://example.com Sec-WebSocket-Protocol: chat, superchat Sec-WebSocket-Version: 13 Server: HTTP/1.1 101 Switching Protocols Upgrade: websocket Connection: Upgrade Sec-WebSocket-Accept: s3pPLMBiTxaQ9kYGzzhZRbK+xOo=
- 21. WebSocket: Sending a message 21 Client: { "type": "message", "ts": 1469563519, "user": "kakovskyi", "text": "Hello, @WebCamp!" } Server: { "type": "notification", "ts": 1469563519, "user": "WebCamp Bot", "text": "Howdy @kakovskyi?" }
- 22. WebSocket: Closing a connection 22 Client: 0x8 Server: 0x8
- 23. WebSocket: Pros ● Supported by majority of browsers ● Low latency ● Small bandwidth ● Easy to start development 23
- 24. WebSocket: Cons ● Needs development of signaling protocol ● Timeouts/reconnections should be additionally handled 24
- 25. WebSocket and Python ● Servers: ○ Autobahn - Twisted and asyncio implementations ○ aiohttp ○ Tornado ○ Flask-SocketIO ○ Flask-Sockets 25
- 26. WebSocket and Python ● Clients: ○ Autobahn ○ aiohttp ○ Tornado-based example ○ Vanilla websocket-client ● JS-client: SocketIO 26
- 27. Life of messaging platform ● Authentication ● Access control checks ● Delivery ○ Messages ○ User's presence ○ Push notifications ● History retrieval ● History search 27
- 28. Life of messaging platform ● Parsing ○ Protocol ○ Message content ● Dealing with file uploads ○ Security checks ○ Thumbnails distribution ● Multi-session support ● Reconnection handling ● Rate-limiting 28
- 29. Life of messaging platform ● Server keeps connections open for every client ● High amount of long-lived concurrent connections ● Multithreaded approach isn't efficient due to overhead ● Requires usage of a select implementation on backend: ○ poll ○ epoll ○ kqueue ● Usage of asynchronous Python frameworks is preferred for high loaded solutions 29
- 30. Life of messaging platform ● Authentication ○ OAuth2 ○ Run encryption operations in a separate Python thread ○ Cache users identities with Redis/Memcached ● Access-control checks ○ Make the checks lightweight and cheap ○ Raise an exception when operation isn't permitted 30 EAFP: Easier to ask for forgiveness than permission
- 31. Delivery ● Make message delivery fault-tolerant ● Limit size of a message ● Filter content of messages: ○ Users like to send chars that break all the things ● Reduce presence traffic, it could be a bottleneck for large chats ● Use asynchronous broker for delivery when a user is offline (email or push) ○ Celery ○ RQ ○ Amazon Simple Queue Service ○ Huey 31
- 32. Life of messaging platform ● Push notifications ■ Vendors ● Amazon SNS ● APNS ● Google Cloud Messaging ● Firebase Cloud Messaging ■ Python tools ● PyAPNs ● Python-GCM ● Pusher ● Be careful with device registration ● Make delivery of pushes fault-tolerant 32
- 33. History retrieval ● Return last messages for every chat instantly ○ Use double writes ■ In-memory queue only for last messages ■ Persistent storage for all the things ● Majority of history retrievals is for the last days ○ Let's optimize the case ● Index messages by date 33
- 34. History search ● ElasticSearch is the default solution for full- text search ● @a_soldatenko: What is the best full text search engine for Python? ● Add timing for search requests 34
- 35. Parsing ● Protocol ○ Avoid to use Pure Python parsers ■ ujson ■ lxml ○ Run benchmarks against your typical cases ● Message content ○ Be careful with regular expressions ■ re2 ■ pyre2 ○ Alternative parsers in Python 35
- 36. Dealing with file uploads ● Security checks ○ File upload vulnerabilities ○ Image upload ■ Decompression bomb ■ Other vulnerabilities with Pillow ○ Amazon S3 as file storage ■ boto ■ aiobotocore ■ botornado ● Thumbnails distribution ○ Delegate that to S3 ○ Requested by a client even if not needed 36
- 37. Life of messaging platform ● Multi-session support ○ Set expiration time ○ Be ready to handle up to 4x sessions per user simultaneously ■ Desktop ■ Mobile ■ Tablet ■ Laptop ● Reconnection handling ○ Spin a proxy layer between messaging server and clients ● Rate-limiting ○ Limit amount of operations per user/group for heavy stuff ○ Leaky bucket ○ Throttling 37
- 38. Lessons learned ● Bursty traffic ○ Load testing is a must, but not always enough ■ Locust ■ Yandex Tank ● Reconnect storm could be a big deal ○ We should handle that on platform and client-side ● AWS issues make bad customers experience ○ Put nodes in Multi-AZ 38
- 39. Lessons learned ● Incidents prevention is cheaper than resolution ○ Grab stats and metrics about your services and storages ■ Redis for per-chat stats ■ StatsD ■ Grafana ○ Be notified when something starts going wrong ■ Elastalert ■ Monit ■ DataDog 39
- 40. Lessons learned ● Don't stick with one language/stack ○ Python is great, but for some cases Go, Ruby or PHP are more suitable from product side ○ Avoid business logic duplication in several repos, spin a service and just call the endpoint ● Releasing new features only for certain groups makes product management easier ○ LaunchDarkly 40
- 41. Lessons learned ● Don’t F**k the Customer ○ Provide unit/integration tests with every PR ○ Have development environment same as prod ○ Have staging environment same as prod ○ Make deployments fast ○ Rollback faster ○ Have a fallback plan 41
- 42. Summary 42
- 43. Summary ● Select a messaging protocol which aligns with your needs ● WebSocket + JSON could be the thing for new projects ● Usage of asynchronous frameworks is preferred ● Execute blocking operations in a separate thread ● Collect metrics for common services operations ● Caching saves a lot of time ● Use C or Cython-based solutions for CPU-bound tasks ● Have fast release/deploy/rollback cycle ● Python is great, but don't hesitate to pick other tools 43
- 44. Further reading ● How HipChat Stores and Indexes Billions of Messages Using ElasticSearch ● @kakovskyi: Maintaining a high load Python project for newcomers ● HipChat: Important improvements to staging, presence & database storage ● HipChat and the little connection that could ● Elasticsearch at HipChat: 10x faster queries ● Atlassian: How IT and SRE use ChatOps to run incident management ● A Study of Internet Instant Messaging and Chat Protocols ● What Is Async, How Does It Work, And When Should I Use It? ● Leaky Bucket & Tocken Bucket - Traffic shaping ● A guide to analyzing Python performance ● Why Leading Companies Dark Launch - LaunchDarkly Blog ● @bmwant: Asyncio-stack for web development 44
- 45. Questions? 45 Viacheslav Kakovskyi viach.kakovskyi@gmail.com @kakovskyi Instant messenger with Python Back-end development