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api_testing

Python version - 3.6

Install requirements.txt by running - pip install requirements.txt

run stub endpoint

gunicorn api_stub:api

in new terminal tab, run pytest to test API endpoint

pytest

STUB API Endpoint implemented - /emojis

Answers to the questions

1. What concerns would you have from a testing perspective?

  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc

2. How would you go about tackling the QA for this work?

  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time of the endpoint, how fast the endpoint is returning the result

3. What sort of tests would be worth describing or worth automating?

  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion

4. What tools would you use?

I have used following tools:

About

No description, website, or topics provided.

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Readme
Activity

Stars

0 stars

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1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
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observer.observe(document.body, { childList: true, subtree: true });
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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var style = document.createElement('style');
style.textContent = '
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color-scheme: dark light;
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})();
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requirements.txt
requirements.txt
test_api.py
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Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Packages
Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
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if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
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if (q) {
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var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
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node.parentNode.replaceChild(frag, node);
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} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
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Array.from(node.childNodes).forEach(highlight);
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highlight(document.body);
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var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
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if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
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observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - jssparas/api_testing · GitHub
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Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - jssparas/api_testing · GitHub
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requirements.txt
requirements.txt
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Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - jssparas/api_testing · GitHub
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api_stub.py
config.py
config.py
requirements.txt
requirements.txt
test_api.py
test_api.py
Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - jssparas/api_testing · GitHub
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README.md
api_stub.py
api_stub.py
config.py
config.py
requirements.txt
requirements.txt
test_api.py
test_api.py
Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
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Repository files navigation
api_testing
Python version - 3.6
Install requirements.txt by running -
pip install requirements.txt
run stub endpoint
gunicorn api_stub:api
in new terminal tab, run pytest to test API endpoint
pytest
STUB API Endpoint implemented - /emojis
Answers to the questions
1. What concerns would you have from a testing perspective?
  • Firstly, would do an impact analysis of the project, like what all can be the use-cases of these API endpoints.
  • What could be the scenarios wherein the user will be using these APIs
  • What could be the load factor, performance hits, etc
2. How would you go about tackling the QA for this work?
  • We need to understand the scope of the project, types of testing methodologies (functional or non-functional)
  • functional like how does an API endpoint behaves given different user-inputs, what are the different outputs we get
with different sets of inputs.
  • non-functional like performance testing, hitting the API endpoint with large number of simultaenous requests and check the response time
of the endpoint, how fast the endpoint is returning the result
3. What sort of tests would be worth describing or worth automating?
  • We can always automate tests that will be required as a part of regression suite i.e. need to be tested in every version release
like checking various reponses (happy path tests), basically the behaviour which API endpoints must show in ideal case.
  • And also some negative tests, like if an API is supposed not to implement POST request, then that automated test must be there with 404 status assertion
4. What tools would you use?
I have used following tools:
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