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django-perf-rec-4.9.0


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توضیحات

Keep detailed records of the performance of your Django code.
ویژگی مقدار
سیستم عامل -
نام فایل django-perf-rec-4.9.0
نام django-perf-rec
نسخه کتابخانه 4.9.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Adam Johnson
ایمیل نویسنده me@adamj.eu
آدرس صفحه اصلی https://github.com/adamchainz/django-perf-rec
آدرس اینترنتی https://pypi.org/project/django-perf-rec/
مجوز MIT
=============== django-perf-rec =============== .. image:: https://img.shields.io/github/actions/workflow/status/adamchainz/django-perf-rec/main.yml?branch=main&style=for-the-badge :target: https://github.com/adamchainz/django-perf-rec/actions?workflow=CI .. image:: https://img.shields.io/pypi/v/django-perf-rec.svg?style=for-the-badge :target: https://pypi.org/project/django-perf-rec/ .. image:: https://img.shields.io/badge/code%20style-black-000000.svg?style=for-the-badge :target: https://github.com/psf/black .. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white&style=for-the-badge :target: https://github.com/pre-commit/pre-commit :alt: pre-commit "Keep detailed records of the performance of your Django code." **django-perf-rec** is like Django's ``assertNumQueries`` on steroids. It lets you track the individual queries and cache operations that occur in your code. Use it in your tests like so: .. code-block:: python def test_home(self): with django_perf_rec.record(): self.client.get("/") It then stores a YAML file alongside the test file that tracks the queries and operations, looking something like: .. code-block:: yaml MyTests.test_home: - cache|get: home_data.user_id.# - db: 'SELECT ... FROM myapp_table WHERE (myapp_table.id = #)' - db: 'SELECT ... FROM myapp_table WHERE (myapp_table.id = #)' When the test is run again, the new record will be compared with the one in the YAML file. If they are different, an assertion failure will be raised, failing the test. Magic! The queries and keys are 'fingerprinted', replacing information that seems variable with `#` and `...`. This is done to avoid spurious failures when e.g. primary keys are different, random data is used, new columns are added to tables, etc. If you check the YAML file in along with your tests, you'll have unbreakable performance with much better information about any regressions compared to ``assertNumQueries``. If you are fine with the changes from a failing test, just remove the file and rerun the test to regenerate it. For more information, see our `introductory blog post <https://adamj.eu/tech/2016/09/26/introducing-django-perf-rec/>`_ that says a little more about why we made it. Installation ============ Use **pip**: .. code-block:: bash python -m pip install django-perf-rec Requirements ============ Python 3.7 to 3.11 supported. Django 2.2 to 4.2 supported. ---- **Are your tests slow?** Check out my book `Speed Up Your Django Tests <https://adamchainz.gumroad.com/l/suydt>`__ which covers loads of ways to write faster, more accurate tests. ---- API === ``record(record_name: str | None=None, path: str | None=None, capture_traceback: callable[[Operation], bool] | None=None, capture_operation: callable[[Operation], bool] | None=None)`` --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Return a context manager that will be used for a single performance test. The arguments must be passed as keyword arguments. ``path`` is the path to a directory or file in which to store the record. If it ends with ``'/'``, or is left as ``None``, the filename will be automatically determined by looking at the filename the calling code is in and replacing the ``.py[c]`` extension with ``.perf.yml``. If it points to a directory that doesn't exist, that directory will be created. ``record_name`` is the name of the record inside the performance file to use. If left as ``None``, the code assumes you are inside a Django ``TestCase`` and uses magic stack inspection to find that test case, and uses a name based upon the test case name + the test method name + an optional counter if you invoke ``record()`` multiple times inside the same test method. Whilst open, the context manager tracks all DB queries on all connections, and all cache operations on all defined caches. It names the connection/cache in the tracked operation it uses, except from for the ``default`` one. When the context manager exits, it will use the list of operations it has gathered. If the relevant file specified using ``path`` doesn't exist, or doesn't contain data for the specific ``record_name``, it will be created and saved and the test will pass with no assertions. However if the record **does** exist inside the file, the collected record will be compared with the original one, and if different, an ``AssertionError`` will be raised. When running on pytest, this will use its fancy assertion rewriting; in other test runners/uses the full diff will be attached to the message. Example: .. code-block:: python import django_perf_rec from app.models import Author class AuthorPerformanceTests(TestCase): def test_special_method(self): with django_perf_rec.record(): list(Author.objects.special_method()) ``capture_traceback``, if not ``None``, should be a function that takes one argument, the given DB or cache operation, and returns a ``bool`` indicating if a traceback should be captured for the operation (by default, they are not). Capturing tracebacks allows fine-grained debugging of code paths causing the operations. Be aware that records differing only by the presence of tracebacks will not match and cause an ``AssertionError`` to be raised, so it's not normally suitable to permanently record the tracebacks. For example, if you wanted to know what code paths query the table ``my_table``, you could use a ``capture_traceback`` function like so: .. code-block:: python def debug_sql_query(operation): return "my_tables" in operation.query def test_special_method(self): with django_perf_rec.record(capture_traceback=debug_sql_query): list(Author.objects.special_method()) The performance record here would include a standard Python traceback attached to each SQL query containing "my_table". ``capture_operation``, if not ``None``, should be a function that takes one argument, the given DB or cache operation, and returns a ``bool`` indicating if the operation should be recorded at all (by default, all operations are recorded). Not capturing some operations allows for hiding some code paths to be ignored in your tests, such as for ignoring database queries that would be replaced by an external service in production. For example, if you knew that in testing all queries to some table would be replaced in production with something else you could use a ``capture_operation`` function like so: .. code-block:: python def hide_my_tables(operation): return "my_tables" in operation.query def test_special_function(self): with django_perf_rec.record(capture_operation=hide_my_tables): list(Author.objects.all()) ``TestCaseMixin`` ----------------- A mixin class to be added to your custom ``TestCase`` subclass so you can use **django-perf-rec** across your codebase without needing to import it in each individual test file. It adds one method, ``record_performance()``, whose signature is the same as ``record()`` above. Example: .. code-block:: python # yplan/test.py from django.test import TestCase as OrigTestCase from django_perf_rec import TestCaseMixin class TestCase(TestCaseMixin, OrigTestCase): pass # app/tests/models/test_author.py from app.models import Author from yplan.test import TestCase class AuthorPerformanceTests(TestCase): def test_special_method(self): with self.record_performance(): list(Author.objects.special_method()) ``get_perf_path(file_path)`` ---------------------------- Encapsulates the logic used in ``record()`` to form ``path`` from the path of the file containing the currently running test, mostly swapping '.py' or '.pyc' for '.perf.yml'. You might want to use this when calling ``record()`` from somewhere other than inside a test (which causes the automatic inspection to fail), to match the same filename. ``get_record_name(test_name, class_name=None)`` ----------------------------------------------- Encapsulates the logic used in ``record()`` to form a ``record_name`` from details of the currently running test. You might want to use this when calling ``record()`` from somewhere other than inside a test (which causes the automatic inspection to fail), to match the same ``record_name``. Settings ======== Behaviour can be customized with a dictionary called ``PERF_REC`` in your Django settings, for example: .. code-block:: python PERF_REC = { "MODE": "once", } The possible keys to this dictionary are explained below. ``HIDE_COLUMNS`` ---------------- The ``HIDE_COLUMNS`` setting may be used to change the way **django-perf-rec** simplifies SQL in the recording files it makes. It takes a boolean: * ``True`` (default) causes column lists in queries to be collapsed, e.g. ``SELECT a, b, c FROM t`` becomes ``SELECT ... FROM t``. This is useful because selected columns often don't affect query time in typical Django applications, it makes the records easier to read, and they then don't need updating every time model fields are changed. * ``False`` stops the collapsing behaviour, causing all the columns to be output in the files. ``MODE`` -------- The ``MODE`` setting may be used to change the way **django-perf-rec** behaves when a performance record does not exist during a test run. * ``'once'`` (default) creates missing records silently. * ``'none'`` raises ``AssertionError`` when a record does not exist. You probably want to use this mode in CI, to ensure new tests fail if their corresponding performance records were not committed. * ``'all'`` creates missing records and then raises ``AssertionError``. * ``'overwrite'`` creates or updates records silently. Usage in Pytest =============== If you're using Pytest, you might want to call ``record()`` from within a Pytest fixture and have it automatically apply to all your tests. We have an example of this, see the file `test_pytest_fixture_usage.py <https://github.com/adamchainz/django-perf-rec/blob/main/tests/test_pytest_fixture_usage.py>`_ in the test suite.


نیازمندی

مقدار نام
>=3.2 Django
- PyYAML
>=0.4.4 sqlparse


زبان مورد نیاز

مقدار نام
>=3.7 Python


نحوه نصب


نصب پکیج whl django-perf-rec-4.9.0:

    pip install django-perf-rec-4.9.0.whl


نصب پکیج tar.gz django-perf-rec-4.9.0:

    pip install django-perf-rec-4.9.0.tar.gz