Design and implementation of a RPC library in Audebert python - - PowerPoint PPT Presentation

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Design and implementation of a RPC library in Audebert python - - PowerPoint PPT Presentation

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Design and implementa- tion of a RPC library in python Rmi Design and implementation of a RPC library in Audebert python Introduction Client Service Decorators Signatures Rmi Audebert More signatures Conclusion 2014-07-18 Rmi

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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Design and implementation of a RPC library in python

Rémi Audebert 2014-07-18

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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Introduction

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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Remote procedure call

RPC Services with methods Clients Request from a client to a service Reply from a service to a client

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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Remote procedure call

RPC Services with methods Clients Request from a client to a service Reply from a service to a client RPC system: Cellaserv2 Based on TCP/IP Centralized server Uses protocol buffers More information: https://code.evolutek.org/cellaserv2

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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Register + Request + Reply

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The requierements of this library

Technical Python3 No external libraries Handle Client and Service Usage Easy to use Hard to misuse Fail gracefully Target users: mostly sleep deprived

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Design and implementa- tion of a RPC library in python Rémi Audebert Introduction Client Service

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The rush friendly requirement

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Client

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CellaservProxy

Code from cellaserv.proxy import CellaservProxy client = CellaservProxy() Configuration CellaservProxy(host="example.org", port=4242) Environnment variables: CS_HOST, CS_PORT Configuration file: /etc/conf.d/cellaserv Usage

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CellaservProxy

Code from cellaserv.proxy import CellaservProxy client = CellaservProxy() Configuration CellaservProxy(host="example.org", port=4242) Environnment variables: CS_HOST, CS_PORT Configuration file: /etc/conf.d/cellaserv Usage now = client.time.date()

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Implementation

Usage client.time.date() cellaserv/proxy.py class CellaservProxy(cellaserv.client.SynClient): ... def __getattr__(self, service_name): return ServiceProxy(self.conn, service_name)

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Implementation

Usage client.time.date() cellaserv/proxy.py class CellaservProxy(cellaserv.client.SynClient): ... def __getattr__(self, "time"): return ServiceProxy(self.conn, "time")

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client.time.date()

Figure 1: Execution

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Service

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Decorators

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Service’s design

Simple usage import time from cellaserv.service import Service class Time(Service): @Service.action def date(self): return time.time() Time().run()

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Python’s feature: decorators

Simple usage >>> def log_usage(f): ... def wrap(*args, **kwargs): ... print("{} called".format(f)) ... return f(*args, **kwargs) ... return wrap ... >>> my_len = log_usage(len) >>> my_len([42]) <built-in function len> called 1

Note: this decorator should use @functools.wraps(f). Rémi Audebert Design and implementation of a RPC library in python 2014-07-18 15 / 32

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Service’s design

Advanced usage class Date(Service): @Service.action("heure") @Service.action("time_" + get_timezone()) def time(self): return time.time()

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Function decorator: caution

What is the difference between: Name of the method is name of the function @Service.action def action1(self): pass Name of the method is given by the user @Service.action("action_name") def action2(self): pass

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Function decorator: caution

Name of the method is name of the function action1 = Service.action(action1) Name of the method is given by the user action2 = Service.action("action_name")(action2)

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Python’s feature: decorators

class Service: @staticmethod def action(method_or_name): def _set_action(method, action): try: method._actions.append(action) except AttributeError: method._actions = [action] return method def _wrapper(method): return _set_action(method, method_or_name) if callable(method_or_name): return _set_action(method_or_name, method_or_name.__name__) else: return _wrapper

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Signatures

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Dealing with TypeError

We want to emit a warning when the user send a request with bad arguments.

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Dealing with TypeError

We want to emit a warning when the user send a request with bad arguments. Bad prototype >>> def f(): ... pass >>> f(42) TypeError: f() takes 0 positional arguments but 1 was given

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Dealing with TypeError

We want to emit a warning when the user send a request with bad arguments. Bad prototype >>> def f(): ... pass >>> f(42) TypeError: f() takes 0 positional arguments but 1 was given Bad service code >>> def f(): ... 1 + 'a' >>> f() TypeError: unsupported operand type(s) for +: 'int' and 'str'

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Dealing with TypeError: simple solution

Report all exceptions to the user.

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Checking signatures: quick and dirty solution

Hack Use the stack size. Bad prototype >>> try: ... f(42) ... except: ... print(len(inspect.trace())) 1 Internal error >>> try: ... f() ... except: ... print(len(inspect.trace())) 2

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PEP-0362: Function Signature Object

The signature object inspect.signature(f) (new in python3.3) Code >>> def f(a, b): ... pass >>> sig = inspect.signature(f) >>> print(sig) (a, b) >>> sig.parameters mappingproxy(OrderedDict([('x', <Parameter at ... 'x'>), ('y', <Parameter at ... 'y'>)]))

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Check signature compatibility?

Use the bind() method >>> def f(a, b): ... pass >>> sig = inspect.signature(f) >>> user_kwargs = {'a': 42, 'b': 1.2} >>> sig.bind(**user_kwargs) <inspect.BoundArguments object at ...>

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Check signature compatibility?

Use the bind() method >>> def f(a, b): ... pass >>> sig = inspect.signature(f) >>> user_kwargs = {'a': 42, 'b': 1.2} >>> sig.bind(**user_kwargs) <inspect.BoundArguments object at ...>

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Bind is smart

Advanced signatures >>> def f(a, *args, v=False, **kwargs): ... pass >>> sig = inspect.signature(f) >>> user_args = ('x', 'y') >>> user_kwargs = {'a': 42, 'v': True} >>> sig.bind(*user_args, **user_kwargs) <inspect.BoundArguments object at ...> >>> sig.bind() TypeError: 'a' parameter lacking default value

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Bind is slow. . .

63 times slower than: Code try: f(**user_kwargs) except TypeError as e: // use inspect.stack() The EAFP coding style Easier to ask for forgiveness than permission. Assume the user is mostly right.

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More signatures

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Give the user all he needs

PEP-3107: Function Annotations (python3.0) >>> def is_safe(pos: '(x, y) 30mm radius') -> bool: ... pass >>> print(inspect.signature(is_safe)) (pos:'(x, y) 30mm radius') -> bool

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Conclusion

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More fun in this library

Synchronous and Asynchronous clients Service’s dependencies Events Attributes over RPC Descriptors Identification of services Supports down to python3.1 Manages user’s threads automatically Metaclass . . .

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Conclusion

This talk Code: http://code.evolutek.eu/python-cellaserv2 Doc: http://doc.evolutek.eu/info/cellaserv.html Discuss: #evolutek<<@irc.rezosup.org Contact IRC: halfr@irc.rezosup.org Mail: halfr@lse.epita.fr Twitter: @halfr

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