I am having this method below:
def pagination_logic(self, topic_name):
"""Pagination logic to fetch the complete data.
:param topic_name:str, kafka topic name.
"""
while self.next_page_cursor:
self.fetch_response_from_api()
records = self.extract_records()
self.publish_records(records, topic_name)
if not self.flag:
break
self.extract_next_page_cursor()
self.page += 1
else:
logger.info("Finished fetching data")
I need to write a unit test method. Below is my unit test method
def test_pagination_logic(self):
"""Test for pagination logic."""
allow(self.slack).fetch_response_from_api.and_return(None)
allow(self.slack).extract_records.and_return(RESPONSE.get('entries'))
allow(self.slack).publish_records.and_return(None)
allow(self.slack).extract_next_page_cursor.and_return(None)
self.slack.next_page_cursor = 'abc'
self.slack.flag = 0
result = self.slack.pagination_logic('topic_name')
assert result is None
I know that I can achieve 100% coverage for this by setting the value of self.flag as 1 for the first iteration and 0 for the second iteration.
But how can I achieve that?.
Try doing like this. This is a bit hacky but I think this might work:
class Helper:
def __init__(self):
self.s_obj = None
def update_flag():
if self.s_obj.flag == 1:
self.s_obj.flag = 0
class YourTestClass:
def test_pagination_logic(self):
"""Test for pagination logic."""
...
h_obj = Helper()
h_obj.s_obj = self.slack
allow(self.slack).extract_next_page_cursor.and_return_result_of(h_obj.update_flag)
self.slack.flag = 1
result = self.slack.pagination_logic('topic_name')
....
Related
I created a class to make my life easier while doing some integration tests involving workers and their contracts. The code looks like this:
class ContractID(str):
contract_counter = 0
contract_list = list()
def __new__(cls):
cls.contract_counter += 1
new_entry = super().__new__(cls, f'Some_internal_name-{cls.contract_counter:10d}')
cls.contract_list.append(new_entry)
return new_entry
#classmethod
def get_contract_no(cls, worker_number):
return cls.contract_list[worker_number-1] # -1 so WORKER1 has contract #1 and not #0 etc.
When I'm unit-testing the class, I'm using the following code:
from test_helpers import ContractID
#pytest.fixture
def get_contract_numbers():
test_string_1 = ContractID()
test_string_2 = ContractID()
test_string_3 = ContractID()
return test_string_1, test_string_2, test_string_3
def test_contract_id(get_contract_numbers):
assert get_contract_ids[0] == 'Some_internal_name-0000000001'
assert get_contract_ids[1] == 'Some_internal_name-0000000002'
assert get_contract_ids[2] == 'Some_internal_name-0000000003'
def test_contract_id_get_contract_no(get_contract_numbers):
assert ContractID.get_contract_no(1) == 'Some_internal_name-0000000001'
assert ContractID.get_contract_no(2) == 'Some_internal_name-0000000002'
assert ContractID.get_contract_no(3) == 'Some_internal_name-0000000003'
with pytest.raises(IndexError) as py_e:
ContractID.get_contract_no(4)
assert py_e.type == IndexError
However, when I try to run these tests, the second one (test_contract_id_get_contract_no) fails, because it does not raise the error as there are more than three values. Furthermore, when I try to run all my tests in my folder test/, it fails even the first test (test_contract_id), which is probably because I'm trying to use this function in other tests that run before this test.
After reading this book, my understanding of fixtures was that it provides objects as if they were never called before, which is obviously not the case here. Is there a way how to tell the tests to use the class as if it hasn't been used before anywhere else?
If I understand that correctly, you want to run the fixture as setup code, so that your class has exactly 3 instances. If the fixture is function-scoped (the default) it is indeed run before each test, which will each time create 3 new instances for your class. If you want to reset your class after the test, you have to do this yourself - there is no way pytest can guess what you want to do here.
So, a working solution would be something like this:
#pytest.fixture(autouse=True)
def get_contract_numbers():
test_string_1 = ContractID()
test_string_2 = ContractID()
test_string_3 = ContractID()
yield
ContractID.contract_counter = 0
ContractID.contract_list.clear()
def test_contract_id():
...
Note that I did not yield the test strings, as you don't need them in the shown tests - if you need them, you can yield them, of course. I also added autouse=True, which makes sense if you need this for all tests, so you don't have to reference the fixture in each test.
Another possibility would be to use a session-scoped fixture. In this case the setup would be done only once. If that is what you need, you can use this instead:
#pytest.fixture(autouse=True, scope="session")
def get_contract_numbers():
test_string_1 = ContractID()
test_string_2 = ContractID()
test_string_3 = ContractID()
yield
I have a list of ~300K URLs for an API i need to get data from.
The API limit is 100 calls per second.
I have made a class for the asynchronous but this is working to fast and I am hitting an error on the API.
How do I slow down the asynchronous, so that I can make 100 calls per second?
import grequests
lst = ['url.com','url2.com']
class Test:
def __init__(self):
self.urls = lst
def exception(self, request, exception):
print ("Problem: {}: {}".format(request.url, exception))
def async(self):
return grequests.map((grequests.get(u) for u in self.urls), exception_handler=self.exception, size=5)
def collate_responses(self, results):
return [x.text for x in results]
test = Test()
#here we collect the results returned by the async function
results = test.async()
response_text = test.collate_responses(results)
The first step that I took was to create an object who can distribute a maximum of n coins every t ms.
import time
class CoinsDistribution:
"""Object that distribute a maximum of maxCoins every timeLimit ms"""
def __init__(self, maxCoins, timeLimit):
self.maxCoins = maxCoins
self.timeLimit = timeLimit
self.coin = maxCoins
self.time = time.perf_counter()
def getCoin(self):
if self.coin <= 0 and not self.restock():
return False
self.coin -= 1
return True
def restock(self):
t = time.perf_counter()
if (t - self.time) * 1000 < self.timeLimit:
return False
self.coin = self.maxCoins
self.time = t
return True
Now we need a way of forcing function to only get called if they can get a coin.
To do that we can write a decorator function that we could use like that:
#limitCalls(callLimit=1, timeLimit=1000)
def uniqFunctionRequestingServer1():
return 'response from s1'
But sometimes, multiple functions are calling requesting the same server so we would want them to get coins from the the same CoinsDistribution object.
Therefor, another use of the decorator would be by supplying the CoinsDistribution object:
server_2_limit = CoinsDistribution(3, 1000)
#limitCalls(server_2_limit)
def sendRequestToServer2():
return 'it worked !!'
#limitCalls(server_2_limit)
def sendAnOtherRequestToServer2():
return 'it worked too !!'
We now have to create the decorator, it can take either a CoinsDistribution object or enough data to create a new one.
import functools
def limitCalls(obj=None, *, callLimit=100, timeLimit=1000):
if obj is None:
obj = CoinsDistribution(callLimit, timeLimit)
def limit_decorator(func):
#functools.wraps(func)
def limit_wrapper(*args, **kwargs):
if obj.getCoin():
return func(*args, **kwargs)
return 'limit reached, please wait'
return limit_wrapper
return limit_decorator
And it's done ! Now you can limit the number of calls any API that you use and you can build a dictionary to keep track of your CoinsDistribution objects if you have to manage a lot of them (to differrent API endpoints or to different APIs).
Note: Here I have choosen to return an error message if there are no coins available. You should adapt this behaviour to your needs.
You can just keep track of how much time has passed and decide if you want to do more requests or not.
This will print 100 numbers per second, for example:
from datetime import datetime
import time
start = datetime.now()
time.sleep(1);
counter = 0
while (True):
end = datetime.now()
s = (end-start).seconds
if (counter >= 100):
if (s <= 1):
time.sleep(1) # You can keep track of the time and sleep less, actually
start = datetime.now()
counter = 0
print(counter)
counter += 1
This other question in SO shows exactly how to do this. By the way, what you need is usually called throttling.
I built a class to handle a lot of different functions that take common inputs. However, I just ran into the situation where one of the variables that's fed down through self needs to be changed. How do I do this? This is an example:
class Test:
def __init__(self, test_variable):
self.test_var = test_variable
#property
def some_function(self):
if self.test_var < 0:
self.test_var = 'New Output' #this is the line that I can't get
#get to work and I was hoping to update it here
#so I could use it in later functions
return self.test_var
Thank you!
You should drop the #property attribute. Then, you can set it by just doing x.test_var = 5. E.g.,
class Test:
def __init__(self, test_variable):
self.test_var = test_variable
def some_function(self):
if self.test_var < 0:
self.test_var = 'New Output' #this is the line that I can't get
#get to work and I was hoping to update it here
#so I could use it in later functions
return self.test_var
x = Test(-1)
print(x.some_function())
x.test_var = 5
print(x.some_function())
returns
New Output
5
I have a class containing a list and some boolean methods.
class Cls:
data = [] // populated in __init__()
def flag1(self):
def flag2(self):
def flag3(self): # these all return booleans, based on the data
I want to create a higher level function, taking a parameter one of the flags, manipulating the data in a number of ways, applying the flag to the new data, and counting the number of results.
Something like:
def hof(self, fn):
count = 0
for i in range(1, 10):
new_obj = Cls(self.data+i)
if new_obj.fn():
count +=1
Is there any way to accomplish this without turning all the flags into static methods ?
===
Edit: Made it work, in a very hackish way:
class Cls:
data = []
def __init__(self):
self.data = value
class flag1(self):
return True
class flag2(self):
return False
# The hackish part
flag_dict = {
1: flag1,
2: flag2,
}
def hof(self, flag):
count = 0
for i in range(1,10):
new_obj = Cls(self.data + [i])
if self.flag_dict[flag](new_obj):
count +=1
return count
But it seems like a hack, and it's not quite understandable. Could someone point to a better way ?
Thanks.
You should be able to just pass the methods into the function like instance.hof(Cls.flag1), and internally, write it as if fn(new_obj):, with no need to make it a staticmethod.
I am maintaining a little library of useful functions for interacting with my company's APIs and I have come across (what I think is) a neat question that I can't find the answer to.
I frequently have to request large amounts of data from an API, so I do something like:
class Client(object):
def __init__(self):
self.data = []
def get_data(self, offset = 0):
done = False
while not done:
data = get_more_starting_at(offset)
self.data.extend(data)
offset += 1
if not data:
done = True
This works fine and allows me to restart the retrieval where I left off if something goes horribly wrong. However, since python functions are just regular objects, we can do stuff like:
def yo():
yo.hi = "yo!"
return None
and then we can interrogate yo about its properties later, like:
yo.hi => "yo!"
my question is: Can I rewrite my class-based example to pin the data to the function itself, without referring to the function by name. I know I can do this by:
def get_data(offset=0):
done = False
get_data.data = []
while not done:
data = get_more_starting_from(offset)
get_data.data.extend(data)
offset += 1
if not data:
done = True
return get_data.data
but I would like to do something like:
def get_data(offset=0):
done = False
self.data = [] # <===== this is the bit I can't figure out
while not done:
data = get_more_starting_from(offset)
self.data.extend(data) # <====== also this!
offset += 1
if not data:
done = True
return self.data # <======== want to refer to the "current" object
Is it possible to refer to the "current" object by anything other than its name?
Something like "this", "self", or "memememe!" is what I'm looking for.
I don't understand why you want to do this, but it's what a fixed point combinator allows you to do:
import functools
def Y(f):
#functools.wraps(f)
def Yf(*args):
return inner(*args)
inner = f(Yf)
return Yf
#Y
def get_data(f):
def inner_get_data(*args):
# This is your real get data function
# define it as normal
# but just refer to it as 'f' inside itself
print 'setting get_data.foo to', args
f.foo = args
return inner_get_data
get_data(1, 2, 3)
print get_data.foo
So you call get_data as normal, and it "magically" knows that f means itself.
You could do this, but (a) the data is not per-function-invocation, but per function (b) it's much easier to achieve this sort of thing with a class.
If you had to do it, you might do something like this:
def ybother(a,b,c,yrselflambda = lambda: ybother):
yrself = yrselflambda()
#other stuff
The lambda is necessary, because you need to delay evaluation of the term ybother until something has been bound to it.
Alternatively, and increasingly pointlessly:
from functools import partial
def ybother(a,b,c,yrself=None):
#whatever
yrself.data = [] # this will blow up if the default argument is used
#more stuff
bothered = partial(ybother, yrself=ybother)
Or:
def unbothered(a,b,c):
def inbothered(yrself):
#whatever
yrself.data = []
return inbothered, inbothered(inbothered)
This last version gives you a different function object each time, which you might like.
There are almost certainly introspective tricks to do this, but they are even less worthwhile.
Not sure what doing it like this gains you, but what about using a decorator.
import functools
def add_self(f):
#functools.wraps(f)
def wrapper(*args,**kwargs):
if not getattr(f, 'content', None):
f.content = []
return f(f, *args, **kwargs)
return wrapper
#add_self
def example(self, arg1):
self.content.append(arg1)
print self.content
example(1)
example(2)
example(3)
OUTPUT
[1]
[1, 2]
[1, 2, 3]