Python 参数校验的进化

2021-11-04 02:15:56

事情的起因是感觉目前项目中的参数校验方法写的太简单了,很多时候需要在server层再if else处理,于是就动手准备写一个好用一点的,可以自定义校验参数规则的参数校验器,考虑到要可以灵活的配置就萌生了大概的印象:

使用map - 参数A:ruleA,参数B-ruleB..等等,对参数进行规则绑定
使用装饰器
可扩展,可以自定义校验规则

于是第一个版本实现如下:

版本1



# -*- coding:utf-8 -*-

__author__ = "aleimu"

__date__ = "2018-12-6"

__doc__ = "一个实用的入参校验装饰器--针对目前,前端 url?&amp;a=1&amp;b=2或-d'a=1&amp;b=2c=qwe'形式的非json(所有参数都是str类型)" \

          "入参的校验"

import copy

import traceback

from collections import OrderedDict

from functools import wraps

from flask import Flask, json, jsonify, request

app = Flask(__name__)

def verify_args(need=None, length=None, check=None, strip=True, default=(False, None), diy_func=None, release=False):

    """

    约束:

    1. 简化了传参校验,使用位置传参或者关键词传参(一个参数对应一个参数),不允许使用one to list等python高级传参特性

    2. 所有的参数都是str/unicode类型的,前端没有使用json带参数类型的入参方式

    :param need: 必须参数,且不能为None或者""

    :param length: 参数长度范围

    :param check:  str的常用类方法/属性如下:

        isalnum 判断字符串中只能由字母和数字的组合，不能有特殊符号

        isalpha 字符串里面都是字母，并且至少是一个字母，结果就为真，（汉字也可以）其他情况为假

        isdigit 函数判断是否全为数字

    :param strip:对字段进行前后过滤空格

    :param default:将"" 装换成None

    :param diy_func:自定义的对某一参数的校验函数格式: {key:func},类似check, diy_func={"a": lambda x: x + "aa"})

    :param release:发生参数校验异常后是否依然让参数进入主流程函数

    :return:

    """

    def wraps_1(f):

        @wraps(f)

        def wraps_2(*args, **kwargs):

            if release:

                args_bak = args[:]

                kwargs_bak = copy.deepcopy(kwargs)  # 下面流程异常时,是否直接使用 原参数传入f todo

            print ("in", args, kwargs)

            args_template = f.func_code.co_varnames

            print("args_template:", args_template)

            args_dict = OrderedDict()

            req_args_need_list = []

            req_args_types_list = []

            try:

                for i, x in enumerate(args):

                    args_dict[args_template[i]] = x

                sorted_kwargs = sort_by_co_varnames(args_template, kwargs)

                args_dict.update(sorted_kwargs)

                print("args_dict:", args_dict)

                # need

                if need:

                    for k in need:

                        if k not in args_dict:

                            req_args_need_list.append(k)

                        else:

                            if args_dict[k] == None or args_dict[k] == "":

                                req_args_need_list.append(k)

                    if req_args_need_list:

                        return False, "%s is in need" % req_args_need_list

                # strip

                if strip:

                    for k in args_dict:

                        if args_dict[k]:

                            args_dict[k] = args_dict[k].strip()

                # length

                if length:

                    for k in args_dict:

                        if k in length:

                            if not (len(args_dict[k]) &gt;= length[k][0] and len(args_dict[k]) &lt;= length[k][1]):

                                return False, "%s length err" % k

                # default:

                if default[0]:

                    for x in args_dict:

                        if args_dict[x] == "":

                            args_dict[x] = default[1]

                # check

                if check:

                    for k in check:

                        check_func = getattr(type(args_dict[k]), check[k], None)

                        if not (k in args_dict and check_func and check_func(args_dict[k])):

                            req_args_types_list.append(k)

                    if req_args_types_list:

                        return False, "%s type err" % req_args_types_list

                # diy_func

                if diy_func:

                    for k in args_dict:

                        if k in diy_func:

                            args_dict[k] = diy_func[k](args_dict[k])

            except Exception as e:

                print("verify_args catch err: ", traceback.format_exc())

                if release:

                    return f(*args_bak, **kwargs_bak)

                else:

                    return False, str(e)

            return f(*args_dict.values())

        return wraps_2

    return wraps_1

def sort_by_co_varnames(all_args, kwargs):

    new_ordered = OrderedDict()

    for x in all_args:

        if x in kwargs:

            new_ordered[x] = kwargs[x]

    return new_ordered

@app.route("/", methods=["GET", "POST", "PUT"])

def index():

    a = request.values.get("a")

    b = request.values.get("b")

    c = request.values.get("c")

    d = request.values.get("d")

    e = request.values.get("e")

    f = request.values.get("f")

    g = request.values.get("g")

    status, data = todo(a, b, c, d, e=e, f=f, g=g)

    if status:

        return jsonify({"code": 200, "data": data, "err": None})

    else:

        return jsonify({"code": 500, "data": None, "err": data})

@verify_args(need=['a', 'b', 'c'], length={"a": (6, 50)}, strip=True,

             check={"b": 'isdigit', "c": "isalnum"},

             default=(True, None),

             diy_func={"a": lambda x: x + "aa"})

def todo(a, b, c, d, e='  1  ', f='2    ', g=''):

    return True, {"a": a, "b": b, "c": c, "d": d, "e": e, "f": f, "g": g}

if __name__ == "__main__":

    app.run(host='0.0.0.0', port=6000, debug=True)

"""

# curl "http://127.0.0.1:6000/" -d "pwd=123&amp;a=1111111&amp;b=2&amp;c=3&amp;d=d&amp;e=eeeeee&amp;f=12345&amp;g="

{

  "code": 200,

  "data": {

    "a": "1111111aa",

    "b": "2",

    "c": "3",

    "d": "d",

    "e": "eeeeee",

    "f": "12345",

    "g": null

  },

  "err": null

}

# curl "http://127.0.0.1:6000/" -d "pwd=123&amp;a=1111111&amp;b=2&amp;c=3346()*&amp;d=d&amp;e=eeeeee&amp;f=12345&amp;g="

{

  "code": 500,

  "data": null,

  "err": "['c'] type err"

}

# curl "http://127.0.0.1:6000/" -d "pwd=123&amp;a=1111111&amp;b=2&amp;c=&amp;d=d&amp;e=eeeeee&amp;f=12345&amp;g="

{

  "code": 500,

  "data": null,

  "err": "['c'] is in need"

}   

# curl "http://127.0.0.1:6000/" -d "pwd=123&amp;a=1111111&amp;b=2&amp;c=  1  &amp;d=d&amp;e=eeeeee&amp;f=12345&amp;g="

{

  "code": 200,

  "data": {

    "a": "1111111aa",

    "b": "2",

    "c": "1",

    "d": "d",

    "e": "eeeeee",

    "f": "12345",

    "g": null

  },

  "err": null

}

"""

第一个版本切合了当前项目中经常遇到的校验问题,实现起来较简单,基本满足要求.
想要更通用点,更多校验规则一些,就需要每次为verify_args添加参数写if else了,嗯.....有点不优雅啊,于是去看github上有啥好的实现.
找到了如下几个项目:

https://github.com/keleshev/s... 嗯,1.6K的star,思路一致,实现的优雅,但是不好扩展啊....
https://github.com/kvesteri/v... 额,Python Data Validation for Humans™. not for me....
https://github.com/mansam/val... 嗯,思路一致,实现也简单,挺好扩展的,就用它了!

这里说说validator.py ,给个例子



from validator import Required, Not, Truthy, Blank, Range, Equals, In, validate

# let's say that my dictionary needs to meet the following rules...

rules = {

    "foo": [Required, Equals(123)],

    "bar": [Required, Truthy()],

    "baz": [In(["spam", "eggs", "bacon"])],

    "qux": [Not(Range(1, 100))] # by default, Range is inclusive

}

# then this following dict would pass:

passes = {

    "foo": 123,

    "bar": True, # or a non-empty string, or a non-zero int, etc...

    "baz": "spam",

    "qux": 101

}

print validate(rules, passes)

# (True, {})

# but this one would fail

fails = {

    "foo": 321,

    "bar": False, # or 0, or [], or an empty string, etc...

    "baz": "barf",

    "qux": 99

}

print validate(rules, fails)

# (False,

#  {

#  'foo': ["must be equal to '123'"],

#  'bar': ['must be True-equivalent value'],

#  'baz': ["must be one of ['spam', 'eggs', 'bacon']"],

#  'qux': ['must not fall between 1 and 100']

#  })

嗯,使用第一个版本封装一下validator.py就好了!考虑到需要写个dome来试试,就选了flask,嗯,对了,先去github 上搜一下 flask validator 没准已经有现成的呢,实现思路基本一致,但是......前几个star多的都不令人满意,还是自己造*吧.
先实现常见的在route上加装饰器版本,这样的话,就可以直接接收request收到的参数,然后直接校验了,有问题就直接返回错误给调用者,于是有了版本2

版本2



rules_example = {

    "a": [Required, Equals("123")],  # foo must be exactly equal to 123

    "b": [Required, Truthy()],  # bar must be equivalent to True

    "c": [In(["spam", "eggs", "bacon"])],  # baz must be one of these options

    "d": [Not(Range(1, 100))],  # qux must not be a number between 1 and 100 inclusive

    "e": [Length(0, maximum=5)],

    "f": [Required, InstanceOf(str)],

    "g": [Required, Not(In(["spam", "eggs", "bacon"]))],

    "h": [Required, Pattern("\d\d\%")],

    "i": [Required, GreaterThan(1, reverse=True, auto=True)],  # auto 自动转换成float类型来做比较

    "j": [lambda x: x == "bar"],

    "k": [Required, Isalnum()],  # 判断字符串中只能由字母和数字的组合，不能有特殊符号

    "l": [Required, Isalpha()],  # 字符串里面都是字母，并且至少是一个字母，结果就为真，（汉字也可以）其他情况为假

    "m": [Required, Isdigit()],  # 判断字符串是否全为数字

}

def validator_wrap(rules, strip=True, diy_func=None):

    """装饰器版 - 只能检测是否符合规则,不能修改参数

    :param rules:参数的校验规则,map

    :param strip:对字段进行前后空格检测

    :param diy_func:自定义的对某一参数的校验函数格式: {key:func},类似check, diy_func={"a": lambda x: x=="aa"})

    """

    def decorator(f):

        @wraps(f)

        def decorated_func(*args, **kwargs):

            try:

                args_dict = OrderedDict()

                if request.values:

                    args_dict.update(request.values)

                if request.json:

                    args_dict.update(request.json)

                # strip

                if strip:

                    for k in args_dict:

                        if args_dict[k] and isstr(args_dict[k]):

                            if args_dict[k][0] == " " or args_dict[k][-1] == " ":

                                return jsonify({"code": 500, "data": None, "err": "%s should not contain spaces" % k})

                # diy_func

                if diy_func:

                    for k in args_dict:

                        if k in diy_func:

                            args_dict[k] = diy_func[k](args_dict[k])

                # rules

                if rules:

                    result, err = validate(rules, args_dict)

                    if not result:

                        return jsonify(

                            {"code": 500, "data": None, "err": err})

            except Exception as e:

                print("verify_args catch err: ", traceback.format_exc())

                return jsonify({"code": 500, "data": None, "err": str(e)})

            return f(*args, **kwargs)

        return decorated_func

    return decorator

@app.route("/wrap", methods=["GET", "POST", "PUT"])

@validator_wrap(rules=rules_example, strip=True)  # 姿势 1:只能检测是否符合规则,不能修改参数,不符合就会直接返回json给调用者

def wrap_example():

    a = request.values.get("a")

    b = request.values.get("b")

    c = request.values.get("c")

    d = request.values.get("d")

    e = request.values.get("e")

    f = request.values.get("f")

    g = request.values.get("g")

    h = request.values.get("h")

    i = request.values.get("i")

    j = request.values.get("j")

    k = request.values.get("k")

    l = request.values.get("l")

    m = request.values.get("m")

    status, data = todo(a=a, b=b, c=c, d=d, e=e, f=f, g=g, h=h, i=i, j=j, k=k, l=l, m=m)

    if status:

        return jsonify({"code": 200, "data": data, "err": None})

    else:

        return jsonify({"code": 500, "data": None, "err": data})

好像挺好的,基本满足要求了,但是再route上加装饰器,那就改变不了参数的值了,虽然有些参数不一定符合要求,但是简单修补一下还是可以用的,还得继续寻找能够改变入参的方式,第一反应是在装饰器中修改request.values或者request.json的值,让进入到主函数后获取更新后的值,上下求索未得门径,request.value.update方法是被禁用的,继续看源码,后面的实现使用了dict的复杂封装,不好改啊,这样太绕了,还是直接调用函数吧,不玩装饰器了.于是又了版本3

版本3



def validator_func(rules, strip=True, default=(False, None), diy_func=None, release=False):

    """函数版-返回dict,代替request.values/request.json

    :param rules:参数的校验规则,map

    :param strip:对字段进行前后过滤空格

    :param default:将"" 装换成None

    :param diy_func:自定义的对某一参数的校验函数格式: {key:func},类似check, diy_func={"a": lambda x: x + "aa"})

    :param release:发生参数校验异常后是否依然让参数进入主流程函数

    """

    args_dict = OrderedDict()

    try:

        if request.values:

            args_dict.update(request.values)

        if request.json:

            args_dict.update(request.json)

        if release:

            args_dict_copy = copy.deepcopy(args_dict)  # 下面流程异常时,是否直接使用 原参数传入f # fixme

        # strip

        if strip:

            for k in args_dict:

                if isstr(args_dict[k]):

                    args_dict[k] = args_dict[k].strip()

        # default

        if default[0]:

            for x in args_dict:

                if args_dict[x] == "":

                    args_dict[x] = default[1]

        # diy_func

        if diy_func:

            for k in args_dict:

                if k in diy_func:

                    args_dict[k] = diy_func[k](args_dict[k])

        # rules

        if rules:

            result, err = validate(rules, args_dict)

            if not result:

                return False, err

    except Exception as e:

        print("verify_args catch err: ", traceback.format_exc())  # TODO

        if release:

            return True, args_dict_copy

        else:

            return False, str(e)

    return True, args_dict

@app.route("/func", methods=["GET", "POST", "PUT"])

def func_example():

    result, request_args = validator_func(rules=rules_example, strip=True)  # 姿势 2

    if not result:

        return jsonify({"code": 500, "data": None, "err": request_args})

    a = request_args.get("a")

    b = request_args.get("b")

    c = request_args.get("c")

    d = request_args.get("d")

    e = request_args.get("e")

    f = request_args.get("f")

    g = request_args.get("g")

    h = request_args.get("h")

    i = request_args.get("i")

    j = request_args.get("j")

    k = request_args.get("k")

    l = request_args.get("l")

    m = request_args.get("m")

    status, data = todo(a=a, b=b, c=c, d=d, e=e, f=f, g=g, h=h, i=i, j=j, k=k, l=l, m=m)

    if status:

        return jsonify({"code": 200, "data": data, "err": None})

    else:

        return jsonify({"code": 500, "data": None, "err": data})

嗯,还行吧,就是不怎么优雅,还是有点喜欢装饰器版本,但是苦于能力有限,不想看ImmutableMultiDict,MultiDict的实现,还是将第一个版本融合一下吧,装饰route不行,装饰todo还不行吗.于是有了版本4

版本4



def validator_args(rules, strip=True, default=(False, None), diy_func=None, release=False):

    """针对普通函数的参数校验的装饰器

    :param rules:参数的校验规则,map

    :param strip:对字段进行前后过滤空格

    :param default:将"" 装换成None

    :param diy_func:自定义的对某一参数的校验函数格式: {key:func},类似check, diy_func={"a": lambda x: x + "aa"})

    :param release:发生参数校验异常后是否依然让参数进入主流程函数

    """

    def decorator(f):

        @wraps(f)

        def decorated_func(*args, **kwargs):

            if release:

                args_bak = args[:]

                kwargs_bak = copy.deepcopy(kwargs)  # 下面流程异常时,是否直接使用 原参数传入f # fixme

            try:

                args_template = f.func_code.co_varnames

            except:

                args_template = f.__code__.co_varnames

            args_dict = OrderedDict()

            try:

                for i, x in enumerate(args):

                    args_dict[args_template[i]] = x

                sorted_kwargs = sort_by_co_varnames(args_template, kwargs)

                args_dict.update(sorted_kwargs)

                # strip

                if strip:

                    for k in args_dict:

                        if isstr(args_dict[k]):

                            args_dict[k] = args_dict[k].strip()

                # default

                if default[0]:

                    for x in args_dict:

                        if args_dict[x] == "":

                            args_dict[x] = default[1]

                # diy_func

                if diy_func:

                    for k in args_dict:

                        if k in diy_func:

                            args_dict[k] = diy_func[k](args_dict[k])

                # rules

                if rules:

                    result, err = validate(rules, args_dict)

                    if not result:

                        return False, err

            except Exception as e:

                print("verify_args catch err: ", traceback.format_exc())

                if release:

                    return f(*args_bak, **kwargs_bak)

                else:

                    return False, str(e)

            return f(*args_dict.values())

        return decorated_func

    return decorator

@validator_args(rules=rules_example, strip=True)  # 姿势 3

def todo(a, b, c, d, e, f, g, h, i, j, k, l, m):

    return True, {"a": a, "b": b, "c": c, "d": d, "e": e, "f": f, "g": g, "h": h, "i": i, "j": j, "k": k, "l": l,

                  "m": m}

哎,就这样吧,打包一下,随便选吧,爱用哪个用哪个,反正我都写出来了.简单说就是:

validator_func 针对flask的request.json/requests.values的参数校验以及修改,修改的方式有限,可以自己控制
validator_wrap 是针对flask route的装饰器,针对request.json/requests.values的参数校验,只是校验,当然校验的方式可以自己写扩展
validator_args 针对普通函数的参数校验以及修改,注意不要使用python传参的高级特性(一个参数对应多个值),这个方法可以脱离flask使用,所以如果需要就直接copy过去吧.

嗯,最后还是分享一下到git上吧, https://github.com/aleimu/flask-validator 喜欢的点个star.

码农公寓

版本1

版本2

版本3

版本4

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