def execute(self, variables):
# 如果没有设置前置或后置则无需执行
if self.expr_lines:
for expr_line in self.expr_lines:
if "=" not in expr_line:
print YamlHelper.var_expr(variables, expr_line.strip())
else:
self.add_var(variables, expr_line)
def data_combine(self):
# 将Yaml提供的字典类型转换成列表类型
# yamlLst格式如: ["name", ["value,", "value2", "value3"], ["password", ["value1", "value2", "value3"]]]
yamlLst = []
for key in self.body:
if self.body[key].has_key(YamlTag.Values):
# 如果有values标签，则使用该标签
values = self.body[key][YamlTag.Values]
else:
# 没有values标签，则使用该类型下的默认值
value_type = self.body[key][YamlTag.Type]
values = YamlHelper.yaml_default(value_type)
yamlLst.append([key, values])
lst = [self.lst_dict_lst(item) for item in yamlLst]
dc = lst[0]
if len(lst) == 1:
return dc
else:
for i in range(1, len(lst)):
dc = self.assemble_dict_lst(dc, lst[i])
return dc
def save_check_response(self, data_item, response):
# 先判断文件夹和文件是否存在
if not os.path.exists(self.response_file):
if not os.path.exists(os.path.split(self.response_file)[0]):
os.makedirs(os.path.split(self.response_file)[0])
res_file = open(self.response_file, "w")
res_file.close()
# 读写文件
# 如果已经存在该配置了，则忽略
old_yml_dict = yaml.load(open(self.response_file, "r"))
response_dict = yaml.load(response.text)
res_file = open(self.response_file, "a")
# 获取key值，由于dict具有无序性，再创建key时需要以key做一次排序
key_str = "key_"
# iteritems() 返回一个字典键值对的元组集合
sorted_data_item = sorted(data_item.iteritems(), key=lambda k: k[0], reverse=False)
for item in sorted_data_item:
key_str = key_str + str(item[1]) + "_"
key_str = key_str[0 : len(key_str) - 1]
result_dict = {}
# 先要判断key是否存在，如果存在则不做任何处理，不存在则插入
if (old_yml_dict is None) or (not old_yml_dict.has_key(key_str)):
print "插入新的key: {0}".format(key_str)
result_dict[key_str] = data_item
result_dict[key_str][YamlTag.Response] = response_dict
yaml.dump(result_dict, res_file, default_flow_style=False, indent=4)
res_file.write("\n")
else:
print "已经存在key: {0}".format(key_str)
print "已存在的key的内容为: {0}".format(old_yml_dict[key_str][YamlTag.Response])
# 存在该Key，就需要去比较该key的值和response的值
# 比较 old_yml_dict[YamlTag.Response] 与 response_dict 的值，以old_yml_dict为准
flag = YamlHelper.left_cmp_dict(old_yml_dict[key_str][YamlTag.Response], response_dict)
res_file.close()
return flag
def add_var(self, variables, variable_line):
variable_name = variable_line.split("=")[0].strip()
variables[variable_name] = YamlHelper.var_expr(variables, variable_line.split("=")[1].strip())
def __init__(self, yml_file_path):
api = self.api_content(yml_file_path)
# if api.has_key(YamlTag.Body) and api.has_key(YamlTag.Procedure):
# print "不允许同时配置Body和Procedure标签"
# return None
# Yaml 文件名及输出结果的路径
file_name = os.path.split(yml_file_path)[1]
root_dir = YamlHelper.same_prefix(os.path.abspath(yml_file_path), os.getcwd())
self.interface_name = file_name[0 : file_name.index(".")]
self.response_file = "{0}/response/{1}.yml".format(root_dir, self.interface_name)
# Yaml配置文件定义的全局变量，对应globa标签下的变量
self.variables = YamlVariables(api[YamlTag.Global])
# Yaml请求实例
self.request = YamlHttpRequest(
YamlHelper.var_expr(self.variables.variables, YamlHelper.yaml_tag_value(api, YamlTag.Url)),
YamlHelper.dict_var_expr(self.variables.variables, YamlHelper.yaml_tag_value(api, YamlTag.Auth)),
YamlHelper.dict_var_expr(self.variables.variables, YamlHelper.yaml_tag_value(api, YamlTag.Header)),
YamlHelper.var_expr(self.variables.variables, YamlHelper.yaml_tag_value(api, YamlTag.Method)),
YamlHelper.var_expr(self.variables.variables, YamlHelper.yaml_tag_value(api, YamlTag.Action)),
)
print "全局变量列表: "
for key in self.variables.variables:
print "key = {0} \t\t value = {1}".format(key, self.variables.variables[key])
# 前置操作
self.precondition = YamlStep(YamlHelper.yaml_tag_value(api, YamlTag.Precondition))
# 请求的主体，用来进行请求参数的组合
self.body = YamlHelper.yaml_tag_value(api, YamlTag.Body)
# 执行过程 -- 为避免与body重复，可考虑不要该标签
# self.procedure = YamlStep()
# 后置操作
self.postcondition = YamlStep(YamlHelper.yaml_tag_value(api, YamlTag.Postcondition))
# 参数数据组合
self.data_combination = self.data_combine()
