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Home - AI & Machine Learning - A Coding Implementation of Superior PyTest to Construct Personalized and Automated Testing with Plugins, Fixtures, and JSON Reporting
AI & Machine Learning

A Coding Implementation of Superior PyTest to Construct Personalized and Automated Testing with Plugins, Fixtures, and JSON Reporting

NextTechBy NextTechOctober 14, 2025No Comments7 Mins Read
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A Coding Implementation of Superior PyTest to Construct Personalized and Automated Testing with Plugins, Fixtures, and JSON Reporting
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On this tutorial, we discover the superior capabilities of PyTest, some of the highly effective testing frameworks in Python. We construct an entire mini-project from scratch that demonstrates fixtures, markers, plugins, parameterization, and customized configuration. We concentrate on displaying how PyTest can evolve from a easy take a look at runner into a strong, extensible system for real-world purposes. By the top, we perceive not simply find out how to write assessments, however find out how to management and customise PyTest’s habits to suit any mission’s wants. Take a look at the FULL CODES right here.

import sys, subprocess, os, textwrap, pathlib, json


subprocess.run([sys.executable, "-m", "pip", "install", "-q", "pytest>=8.0"], test=True)


root = pathlib.Path("pytest_advanced_tutorial").absolute()
if root.exists():
   import shutil; shutil.rmtree(root)
(root / "calc").mkdir(dad and mom=True)
(root / "app").mkdir()
(root / "assessments").mkdir()

We start by establishing our surroundings, importing important Python libraries for file dealing with and subprocess execution. We set up the newest model of PyTest to make sure compatibility after which create a clear mission construction with folders for our predominant code, utility modules, and assessments. This offers us a stable basis to arrange the whole lot neatly earlier than writing any take a look at logic. Take a look at the FULL CODES right here.

(root / "pytest.ini").write_text(textwrap.dedent("""
[pytest]
addopts = -q -ra --maxfail=1 -m "not gradual"
testpaths = assessments
markers =
   gradual: gradual assessments (use --runslow to run)
   io: assessments hitting the file system
   api: assessments patching exterior calls
""").strip()+"n")


(root / "conftest.py").write_text(textwrap.dedent(r'''
import os, time, pytest, json
def pytest_addoption(parser):
   parser.addoption("--runslow", motion="store_true", assist="run gradual assessments")
def pytest_configure(config):
   config.addinivalue_line("markers", "gradual: gradual assessments")
   config._summary = {"handed":0,"failed":0,"skipped":0,"slow_ran":0}
def pytest_collection_modifyitems(config, objects):
   if config.getoption("--runslow"):
       return
   skip = pytest.mark.skip(cause="want --runslow to run")
   for merchandise in objects:
       if "gradual" in merchandise.key phrases: merchandise.add_marker(skip)
def pytest_runtest_logreport(report):
   cfg = report.config._summary
   if report.when=="name":
       if report.handed: cfg["passed"]+=1
       elif report.failed: cfg["failed"]+=1
       elif report.skipped: cfg["skipped"]+=1
       if "gradual" in report.key phrases and report.handed: cfg["slow_ran"]+=1
def pytest_terminal_summary(terminalreporter, exitstatus, config):
   s=config._summary
   terminalreporter.write_sep("=", "SESSION SUMMARY (customized plugin)")
   terminalreporter.write_line(f"Handed: {s['passed']} | Failed: {s['failed']} | Skipped: {s['skipped']}")
   terminalreporter.write_line(f"Gradual assessments run: {s['slow_ran']}")
   terminalreporter.write_line("PyTest completed efficiently ✅" if s["failed"]==0 else "Some assessments failed ❌")


@pytest.fixture(scope="session")
def settings(): return {"env":"prod","max_retries":2}
@pytest.fixture(scope="operate")
def event_log(): logs=[]; yield logs; print("nEVENT LOG:", logs)
@pytest.fixture
def temp_json_file(tmp_path):
   p=tmp_path/"knowledge.json"; p.write_text('{"msg":"hello"}'); return p
@pytest.fixture
def fake_clock(monkeypatch):
   t={"now":1000.0}; monkeypatch.setattr(time,"time",lambda: t["now"]); return t
'''))

We now create our PyTest configuration and plugin recordsdata. In pytest.ini, we outline markers, default choices, and take a look at paths to manage how assessments are found and filtered. In conftest.py, we implement a customized plugin that tracks handed, failed, and skipped assessments, provides a –runslow possibility, and offers fixtures for reusable take a look at assets. This helps us prolong PyTest’s core habits whereas holding our setup clear and modular. Take a look at the FULL CODES right here.

(root/"calc"/"__init__.py").write_text(textwrap.dedent('''
from .vector import Vector
def add(a,b): return a+b
def div(a,b):
   if b==0: elevate ZeroDivisionError("division by zero")
   return a/b
def moving_avg(xs,okay):
   if okay<=0 or okay>len(xs): elevate ValueError("dangerous window")
   out=[]; s=sum(xs[:k]); out.append(s/okay)
   for i in vary(okay,len(xs)):
       s+=xs[i]-xs[i-k]; out.append(s/okay)
   return out
'''))


(root/"calc"/"vector.py").write_text(textwrap.dedent('''
class Vector:
   __slots__=("x","y","z")
   def __init__(self,x=0,y=0,z=0): self.x,self.y,self.z=float(x),float(y),float(z)
   def __add__(self,o): return Vector(self.x+o.x,self.y+o.y,self.z+o.z)
   def __sub__(self,o): return Vector(self.x-o.x,self.y-o.y,self.z-o.z)
   def __mul__(self,s): return Vector(self.x*s,self.y*s,self.z*s)
   __rmul__=__mul__
   def norm(self): return (self.x**2+self.y**2+self.z**2)**0.5
   def __eq__(self,o): return abs(self.x-o.x)<1e-9 and abs(self.y-o.y)<1e-9 and abs(self.z-o.z)<1e-9
   def __repr__(self): return f"Vector({self.x:.2f},{self.y:.2f},{self.z:.2f})"
'''))

We now construct the core calculation module for our mission. Within the calc package deal, we outline easy mathematical utilities, together with addition, division with error dealing with, and a moving-average operate, to exhibit logic testing. Alongside this, we create a Vector class that helps arithmetic operations, equality checks, and norm computation, an ideal instance for testing customized objects and comparisons utilizing PyTest. Take a look at the FULL CODES right here.

(root/"app"/"io_utils.py").write_text(textwrap.dedent('''
import json, pathlib, time
def save_json(path,obj):
   path=pathlib.Path(path); path.write_text(json.dumps(obj)); return path
def load_json(path): return json.masses(pathlib.Path(path).read_text())
def timed_operation(fn,*a,**kw):
   t0=time.time(); out=fn(*a,**kw); t1=time.time(); return out,t1-t0
'''))
(root/"app"/"api.py").write_text(textwrap.dedent('''
import os, time, random
def fetch_username(uid):
   if os.environ.get("API_MODE")=="offline": return f"cached_{uid}"
   time.sleep(0.001); return f"user_{uid}_{random.randint(100,999)}"
'''))


(root/"assessments"/"test_calc.py").write_text(textwrap.dedent('''
import pytest, math
from calc import add,div,moving_avg
from calc.vector import Vector
@pytest.mark.parametrize("a,b,exp",[(1,2,3),(0,0,0),(-1,1,0)])
def test_add(a,b,exp): assert add(a,b)==exp
@pytest.mark.parametrize("a,b,exp",[(6,3,2),(8,2,4)])
def test_div(a,b,exp): assert div(a,b)==exp
@pytest.mark.xfail(raises=ZeroDivisionError)
def test_div_zero(): div(1,0)
def test_avg(): assert moving_avg([1,2,3,4,5],3)==[2,3,4]
def test_vector_ops(): v=Vector(1,2,3)+Vector(4,5,6); assert v==Vector(5,7,9)
'''))


(root/"assessments"/"test_io_api.py").write_text(textwrap.dedent('''
import pytest, os
from app.io_utils import save_json,load_json,timed_operation
from app.api import fetch_username
@pytest.mark.io
def test_io(temp_json_file,tmp_path):
   d={"x":5}; p=tmp_path/"a.json"; save_json(p,d); assert load_json(p)==d
   assert load_json(temp_json_file)=={"msg":"hello"}
def test_timed(capsys):
   val,dt=timed_operation(lambda x:x*3,7); print("dt=",dt); out=capsys.readouterr().out
   assert "dt=" in out and val==21
@pytest.mark.api
def test_api(monkeypatch):
   monkeypatch.setenv("API_MODE","offline")
   assert fetch_username(9)=="cached_9"
'''))


(root/"assessments"/"test_slow.py").write_text(textwrap.dedent('''
import time, pytest
@pytest.mark.gradual
def test_slow(event_log,fake_clock):
   event_log.append(f"begin@{fake_clock['now']}")
   fake_clock["now"]+=3.0
   event_log.append(f"finish@{fake_clock['now']}")
   assert len(event_log)==2
'''))

We add light-weight app utilities for JSON I/O and a mocked API to train real-world behaviors with out exterior companies. We write targeted assessments that use parametrization, xfail, markers, tmp_path, capsys, and monkeypatch to validate logic and unwanted effects. We embody a gradual take a look at wired to our event_log and fake_clock fixtures to exhibit managed timing and session-wide state. Take a look at the FULL CODES right here.

print("📦 Venture created at:", root)
print("n▶️ RUN #1 (default, skips @gradual)n")
r1=subprocess.run([sys.executable,"-m","pytest",str(root)],textual content=True)
print("n▶️ RUN #2 (--runslow)n")
r2=subprocess.run([sys.executable,"-m","pytest",str(root),"--runslow"],textual content=True)


summary_file=root/"abstract.json"
abstract={
   "total_tests":sum("test_" in str(p) for p in root.rglob("test_*.py")),
   "runs": ["default","--runslow"],
   "outcomes": ["success" if r1.returncode==0 else "fail",
               "success" if r2.returncode==0 else "fail"],
   "contains_slow_tests": True,
   "example_event_log":["[email protected]","[email protected]"]
}
summary_file.write_text(json.dumps(abstract,indent=2))
print("n📊 FINAL SUMMARY")
print(json.dumps(abstract,indent=2))
print("n✅ Tutorial accomplished — all assessments & abstract generated efficiently.")

We now run our take a look at suite twice: first with the default configuration that skips gradual assessments, after which once more with the –runslow flag to incorporate them. After each runs, we generate a JSON abstract containing take a look at outcomes, the overall variety of take a look at recordsdata, and a pattern occasion log. This closing abstract provides us a transparent snapshot of our mission’s testing well being, confirming that each one parts work flawlessly from begin to end.

In conclusion, we see how PyTest helps us take a look at smarter, not tougher. We design a plugin that tracks outcomes, makes use of fixtures for state administration, and controls gradual assessments with customized choices, all whereas holding the workflow clear and modular. We conclude with an in depth JSON abstract that demonstrates how simply PyTest can combine with trendy CI and analytics pipelines. With this basis, we at the moment are assured to increase PyTest additional, combining protection, benchmarking, and even parallel execution for large-scale, professional-grade testing.


Take a look at the FULL CODES right here. Be happy to take a look at our GitHub Web page for Tutorials, Codes and Notebooks. Additionally, be happy to observe us on Twitter and don’t neglect to hitch our 100k+ ML SubReddit and Subscribe to our E-newsletter. Wait! are you on telegram? now you possibly can be a part of us on telegram as properly.


Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is dedicated to harnessing the potential of Synthetic Intelligence for social good. His most up-to-date endeavor is the launch of an Synthetic Intelligence Media Platform, Marktechpost, which stands out for its in-depth protection of machine studying and deep studying information that’s each technically sound and simply comprehensible by a large viewers. The platform boasts of over 2 million month-to-month views, illustrating its recognition amongst audiences.

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