Python (XI) - automated testing framework

Automated test case

1, a frame. The company has a framework for direct use

2, there is no framework. Choose their own framework, write frame.

Our framework presented here is not a case, then the next, start learning how to do the automation framework

Process

First to set a framework to write automated process:

1. Example data read by
2. Call interface, get results
3. Determine whether the expected results and the actual results are consistent
4. Save the test results, which writes excel
5. Generate test reports, send e-mail

Frame set

Inside the framework, we have what directory it?

• cases: test cases
• conf: configuration files
• lib: Testing Tools
• logs: Logs
• report: report
• main.py: The main program
• readme.txt: Notes

    ATP
    │  main.py
    │  readme.txt
    │
    ├─cases
    │      test.xlsx
    │
    ├─conf
    │  │  settings.py
    │  │
    │  └─__pycache__
    │          settings.cpython-36.pyc
    │
    ├─lib
    │      my_request.py
    │      parse_request_data.py
    │      parse_response_data.py
    │      tools.py
    │
    ├─logs
    │      atp.log
    │
    └─report

All these directories is the basic framework of the whole, we can achieve a complete process, then the process is now divided over what to do

Read test data

Read test cases from Excel

Use Case form we want to set it:

project	url	Request method	Request header	Request parameter	Whether json	expected results	actual results	Whether by	Testers
A test project	/api/user/login	get		username=<username>, password=<password>	Yes	code=0,age>10			Ganzi Wen

Moreover, we support parameterized request parameters, such as <username> in the table is actually read out is replaced with a parameter; Analyzing the expected result can support, such as expected results age> 10, keep up with the actual results returned if the comparison result of age> 10.

1, parameterization

Data falsification module --faker

faker module can generate a lot of stuff: phone number, address, bank card number, zip code, province, etc.

Reference: https://faker.readthedocs.io/en/latest/locales/zh_CN.html

Commonly used methods: 

city_suffix (): city and county 

country (): National 

country_code (): Country code 

district (): District 

geo_coordinate (): geographical coordinates of 

latitude (): geographical coordinates (latitude) 

longitude (): geographical coordinates (longitude) 

lexify (): replace all question marks ( "?") events with random letters. 

numerify (): three random numbers 

postcode (): Zip 

province (): State 

street_address (): Street address 

street_name (): street name 

street_suffix (): Street, road 

random_digit (): 0 ~ 9 random number 

random_digit_not_null (): 1 to the random number 9 

random_element (): random letters 

random_int (): random number, the default 0 to 9999 , can be set by setting min, max 

random_letter (): random letters 

random_number (): random number parameter digits set generated digits 

color_name (): random color name

hex_color (): random HEX color 

rgb_color (): random RGB color 

safe_color_name (): random-safe color name 

safe_hex_color (): random security HEX color 

bs (): random company service name 

company (): random company name (long) 

company_prefix ( ): random company name (short) 

company_suffix (): company type 

credit_card_expire (): random credit card expiration date 

credit_card_full (): generate full credit card information 

credit_card_number (): credit card number 

credit_card_provider (): credit cards 

credit_card_security_code (): Credit Card security code 

CURRENCY_CODE (): money coding 

am_pm the (): AM / the PM 

cENTURY (): random century 

dATE (): random date 

date_between (): randomly generated within a specified date range, parameters: start_date, end_date value: specific date or Today, - 30d, - 30Y similar 

date_between_dates (): randomly generated within a specified date range, use ibid 

date_object (): random production of 1970 -l-1 to random date specified date. 

date_this_month (): 

date_this_year (): 

date_time (): randomly generate a specified time (1 January 1970 to date) 

date_time_ad (): generated the year 1 to the current random time 

date_time_between (): Use with a dates 

future_date (): Future date 

future_datetime (): future time 

month (): random month 

month_name (): random month (English) 

past_date (): randomly generated has a past date 

past_datetime (): randomly generated time that has elapsed 

time (): random 24-hour time 

timedelta (): random acquisition time difference 

time_object (): random 24-hour time, time objects 

time_series (): random TimeSeries Object 

timezone (): random time zone 

unix_time (): random Unix time 

year (): random Year 

file_extension (): random file extension 

file_name (): random file name (including the extension, without path) 

file_path (): random file path (including the file name, extension) 

mime_type (): random mime Type

ascii_company_email (): random ASCII E-mail name 

ascii_email (): random ASCII mailbox 

ascii_free_email (): 

ascii_safe_email (): 

company_email (): 

domain_name (): generating domain name 

domain_word (): Domain term (ie, does not contain a suffix) 

Email () : 

free_email (): 

free_email_domain (): 

f.safe_email (): security mailbox 

f.image_url (): random URL address 

ipv4 (): random IP4 address 

ipv6 (): random IP6 address 

mac_address (): random MAC address 

tld () : Web site domain name suffix (. .com, .net.cn, etc., are not included) 

uri (): random URI address 

uri_extension (): URL file extension 

uri_page (): URL file (containing no suffix) 

uri_path (): URL file path (not including the file name) 

url (): random URL address 

user_name (): random user name 

isbn10 (): random ISBN (10 Wei) 

ISBN13 (): random ISBN (13 Wei) 

the job (): random posts

paragraph (): generating a random paragraph 

paragraphs (): randomly generating a plurality of passages, the number of paragraphs is controlled by the parameter nb, returns an array of 

sentence (): randomly generated word 

sentences (): generating a plurality of random words, similar to the paragraph 

text (): randomly generated article (do not fantasize about artificial intelligence, and so far did not fully understand what a word means) 

word (): randomly generated words 

words (): randomly generating a plurality of words, and the use of paragraphs, sentences, similar 

binary (): randomly generated binary-coded 

boolean (): True / False 

language_code (): randomly generated two coding language 

locale (): randomly generated language / international information 

md5 (): randomly generated MD5 

null_boolean (): NULL / True / False 

password (): randomly generated passwords, optional parameters: length: password length; special_chars: can use special characters; digits: contains numbers; upper_case: contains uppercase letters; lower_case: lowercase letters contain 

sha1 (): random SHA1 

sha256 (): random SHA256 

uuid4 (): random UUID 

first_name (): 

first_name_female (): female name

first_name_male (): male name 

first_romanized_name (): Roman name 

last_name (): 

last_name_female (): female name 

last_name_male (): male surname 

last_romanized_name (): 

name (): randomly generated full name 

name_female (): Men's full name 

name_male () : Women full name 

romanized_name (): Roman name 

msisdn (): mobile station international Subscriber Identity, namely mobile ISDN number of users 

phone_number (): randomly generated phone number 

phonenumber_prefix (): randomly generated segments phone number 

profile (): randomly generated file information 

simple_profile (): simple Profile information generated randomly 

 


generated randomly specified type of data: 

pybool (): 

pydecimal (): 

pydict (): 

pyfloat (): left_digits =. 5 # generated integer bits, 

                  right_digits = 2 # generates decimal digit, 

                  positiveTrue = # if only positive 

pyint (): 

pyiterable () 

pylist () 

pyset () 

pystr () 

pystruct () 

pytuple () 

 

ssn (): generated ID number 

chrome (): randomly generated Chrome browser user_agent information 

firefox (): randomly generated FireFox browser user_agent information 

internet_explorer (): randomly generated IE browser user_agent information 

Opera (): randomly generated Opera browser user_agent information 

Safari (): randomly generated Safari browser user_agent information 

linux_platform_token () : random Linux information 

user_agent (): random user_agent information

faker common method

For example, to generate mail and other:

Import faker 

f = faker.Faker (locale = ' zh-CN ' ) # China's 

Print (f.credit_card_number ()) # credit card number 
Print (f.email ()) # E-mail 
Print (f.phone_number ()) # phone No. 
Print (f.ssn ()) # identification number 
Print (f.user_name ()) # random user name