%global _empty_manifest_terminate_build 0
Name:		python-sqlalchemy-easy-profile
Version:	1.3.0
Release:	1
Summary:	An easy profiler for SQLAlchemy queries
License:	MIT License
URL:		https://github.com/dmvass/sqlalchemy-easy-profile
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/84/7f/b2503e4ed65bc58c69c9adf1e2651c521b100fc23b9eac53ba6befa6acce/sqlalchemy-easy-profile-1.3.0.tar.gz
BuildArch:	noarch

Requires:	python3-sqlalchemy
Requires:	python3-sqlparse
Requires:	python3-tox

%description
# SQLAlchemy Easy Profile
[![Build Status](https://travis-ci.com/dmvass/sqlalchemy-easy-profile.svg?branch=master)](https://travis-ci.com/dmvass/sqlalchemy-easy-profile)
[![image](https://img.shields.io/pypi/v/sqlalchemy-easy-profile.svg)](https://pypi.python.org/pypi/sqlalchemy-easy-profile)
[![codecov](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile/branch/master/graph/badge.svg)](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/LICENSE)

Inspired by [django-querycount](https://github.com/bradmontgomery/django-querycount),
is a library that hooks into SQLAlchemy to collect metrics, streaming statistics into
console output and help you understand where in application you have slow or redundant
queries.

![report example](https://raw.githubusercontent.com/dmvass/sqlalchemy-easy-profile/master/images/report-example.png?raw=true)

## Installation
Install the package with pip:
```
pip install sqlalchemy-easy-profile
```

## Session profiler
The profiling session hooks into SQLAlchemy and captures query statements, duration information,
and query parameters. You also may have multiple profiling sessions active at the same
time on the same or different Engines. If multiple profiling sessions are active on the
same engine, queries on that engine will be collected by both sessions and reported on
different reporters.

You may begin and commit a profiling session as much as you like. Calling begin on an already
started session or commit on an already committed session will raise an `AssertionError`.
You also can use a contextmanager interface for session profiling or used it like a decorator.
This has the effect of only profiling queries occurred within the decorated function or inside
a manager context.

How to use `begin` and `commit`:
```python
from easy_profile import SessionProfiler

profiler = SessionProfiler()

profiler.begin()
session.query(User).filter(User.name == "Arthur Dent").first()
profiler.commit()

print(profiler.stats)
```

How to use as a context manager interface:
```python
profiler = SessionProfiler()
with profiler:
    session.query(User).filter(User.name == "Arthur Dent").first()

print(profiler.stats)
```

How to use profiler as a decorator:
```python
profiler = SessionProfiler()

class UsersResource:
    @profiler()
    def on_get(self, req, resp, **args, **kwargs):
        return session.query(User).all()
```

Keep in mind that profiler decorator interface accepts a special reporter and
If it was not defined by default will be used a base streaming reporter. Decorator
also accept `name` and `name_callback` optional parameters.

## WSGI integration
Easy Profiler provides a specified middleware which can prints the number of database
queries for each HTTP request and can be applied as a WSGI server middleware. So you
can easily integrate Easy Profiler into any WSGI application.

How to integrate with a Flask application:
```python
from flask import Flask
from easy_profile import EasyProfileMiddleware

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app)
```

How to integrate with a Falcon application: 
```python
import falcon
from easy_profile import EasyProfileMiddleware

api = application = falcon.API()
application = EasyProfileMiddleware(application)
```

## How to customize output

The `StreamReporter` accepts medium-high thresholds, output file destination (stdout by default), a special
flag for disabling color formatting and number of displayed duplicated queries:

```python
from flask import Flask
from easy_profile import EasyProfileMiddleware, StreamReporter

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app, reporter=StreamReporter(display_duplicates=100))
```

Any custom reporter can be created as:

```python
from easy_profile.reporters import Reporter

class CustomReporter(Reporter):

    def report(self, path, stats):
        """Do something with path and stats.
        
        :param str path: where profiling occurred
        :param dict stats: profiling statistics

        """
        ...

```

## Testing
To run the tests:
```
python setup.py test
```

Or use `tox` for running in all tests environments.

## License
This code is distributed under the terms of the MIT license.

## Changes
A full changelog is maintained in the [CHANGELOG](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/CHANGELOG.md) file.

## Contributing 
**sqlalchemy-easy-profile** is an open source project and contributions are
welcome! Check out the [Issues](https://github.com/dmvass/sqlalchemy-easy-profile/issues)
page to see if your idea for a contribution has already been mentioned, and feel
free to raise an issue or submit a pull request.


%package -n python3-sqlalchemy-easy-profile
Summary:	An easy profiler for SQLAlchemy queries
Provides:	python-sqlalchemy-easy-profile
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-sqlalchemy-easy-profile
# SQLAlchemy Easy Profile
[![Build Status](https://travis-ci.com/dmvass/sqlalchemy-easy-profile.svg?branch=master)](https://travis-ci.com/dmvass/sqlalchemy-easy-profile)
[![image](https://img.shields.io/pypi/v/sqlalchemy-easy-profile.svg)](https://pypi.python.org/pypi/sqlalchemy-easy-profile)
[![codecov](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile/branch/master/graph/badge.svg)](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/LICENSE)

Inspired by [django-querycount](https://github.com/bradmontgomery/django-querycount),
is a library that hooks into SQLAlchemy to collect metrics, streaming statistics into
console output and help you understand where in application you have slow or redundant
queries.

![report example](https://raw.githubusercontent.com/dmvass/sqlalchemy-easy-profile/master/images/report-example.png?raw=true)

## Installation
Install the package with pip:
```
pip install sqlalchemy-easy-profile
```

## Session profiler
The profiling session hooks into SQLAlchemy and captures query statements, duration information,
and query parameters. You also may have multiple profiling sessions active at the same
time on the same or different Engines. If multiple profiling sessions are active on the
same engine, queries on that engine will be collected by both sessions and reported on
different reporters.

You may begin and commit a profiling session as much as you like. Calling begin on an already
started session or commit on an already committed session will raise an `AssertionError`.
You also can use a contextmanager interface for session profiling or used it like a decorator.
This has the effect of only profiling queries occurred within the decorated function or inside
a manager context.

How to use `begin` and `commit`:
```python
from easy_profile import SessionProfiler

profiler = SessionProfiler()

profiler.begin()
session.query(User).filter(User.name == "Arthur Dent").first()
profiler.commit()

print(profiler.stats)
```

How to use as a context manager interface:
```python
profiler = SessionProfiler()
with profiler:
    session.query(User).filter(User.name == "Arthur Dent").first()

print(profiler.stats)
```

How to use profiler as a decorator:
```python
profiler = SessionProfiler()

class UsersResource:
    @profiler()
    def on_get(self, req, resp, **args, **kwargs):
        return session.query(User).all()
```

Keep in mind that profiler decorator interface accepts a special reporter and
If it was not defined by default will be used a base streaming reporter. Decorator
also accept `name` and `name_callback` optional parameters.

## WSGI integration
Easy Profiler provides a specified middleware which can prints the number of database
queries for each HTTP request and can be applied as a WSGI server middleware. So you
can easily integrate Easy Profiler into any WSGI application.

How to integrate with a Flask application:
```python
from flask import Flask
from easy_profile import EasyProfileMiddleware

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app)
```

How to integrate with a Falcon application: 
```python
import falcon
from easy_profile import EasyProfileMiddleware

api = application = falcon.API()
application = EasyProfileMiddleware(application)
```

## How to customize output

The `StreamReporter` accepts medium-high thresholds, output file destination (stdout by default), a special
flag for disabling color formatting and number of displayed duplicated queries:

```python
from flask import Flask
from easy_profile import EasyProfileMiddleware, StreamReporter

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app, reporter=StreamReporter(display_duplicates=100))
```

Any custom reporter can be created as:

```python
from easy_profile.reporters import Reporter

class CustomReporter(Reporter):

    def report(self, path, stats):
        """Do something with path and stats.
        
        :param str path: where profiling occurred
        :param dict stats: profiling statistics

        """
        ...

```

## Testing
To run the tests:
```
python setup.py test
```

Or use `tox` for running in all tests environments.

## License
This code is distributed under the terms of the MIT license.

## Changes
A full changelog is maintained in the [CHANGELOG](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/CHANGELOG.md) file.

## Contributing 
**sqlalchemy-easy-profile** is an open source project and contributions are
welcome! Check out the [Issues](https://github.com/dmvass/sqlalchemy-easy-profile/issues)
page to see if your idea for a contribution has already been mentioned, and feel
free to raise an issue or submit a pull request.


%package help
Summary:	Development documents and examples for sqlalchemy-easy-profile
Provides:	python3-sqlalchemy-easy-profile-doc
%description help
# SQLAlchemy Easy Profile
[![Build Status](https://travis-ci.com/dmvass/sqlalchemy-easy-profile.svg?branch=master)](https://travis-ci.com/dmvass/sqlalchemy-easy-profile)
[![image](https://img.shields.io/pypi/v/sqlalchemy-easy-profile.svg)](https://pypi.python.org/pypi/sqlalchemy-easy-profile)
[![codecov](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile/branch/master/graph/badge.svg)](https://codecov.io/gh/dmvass/sqlalchemy-easy-profile)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/LICENSE)

Inspired by [django-querycount](https://github.com/bradmontgomery/django-querycount),
is a library that hooks into SQLAlchemy to collect metrics, streaming statistics into
console output and help you understand where in application you have slow or redundant
queries.

![report example](https://raw.githubusercontent.com/dmvass/sqlalchemy-easy-profile/master/images/report-example.png?raw=true)

## Installation
Install the package with pip:
```
pip install sqlalchemy-easy-profile
```

## Session profiler
The profiling session hooks into SQLAlchemy and captures query statements, duration information,
and query parameters. You also may have multiple profiling sessions active at the same
time on the same or different Engines. If multiple profiling sessions are active on the
same engine, queries on that engine will be collected by both sessions and reported on
different reporters.

You may begin and commit a profiling session as much as you like. Calling begin on an already
started session or commit on an already committed session will raise an `AssertionError`.
You also can use a contextmanager interface for session profiling or used it like a decorator.
This has the effect of only profiling queries occurred within the decorated function or inside
a manager context.

How to use `begin` and `commit`:
```python
from easy_profile import SessionProfiler

profiler = SessionProfiler()

profiler.begin()
session.query(User).filter(User.name == "Arthur Dent").first()
profiler.commit()

print(profiler.stats)
```

How to use as a context manager interface:
```python
profiler = SessionProfiler()
with profiler:
    session.query(User).filter(User.name == "Arthur Dent").first()

print(profiler.stats)
```

How to use profiler as a decorator:
```python
profiler = SessionProfiler()

class UsersResource:
    @profiler()
    def on_get(self, req, resp, **args, **kwargs):
        return session.query(User).all()
```

Keep in mind that profiler decorator interface accepts a special reporter and
If it was not defined by default will be used a base streaming reporter. Decorator
also accept `name` and `name_callback` optional parameters.

## WSGI integration
Easy Profiler provides a specified middleware which can prints the number of database
queries for each HTTP request and can be applied as a WSGI server middleware. So you
can easily integrate Easy Profiler into any WSGI application.

How to integrate with a Flask application:
```python
from flask import Flask
from easy_profile import EasyProfileMiddleware

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app)
```

How to integrate with a Falcon application: 
```python
import falcon
from easy_profile import EasyProfileMiddleware

api = application = falcon.API()
application = EasyProfileMiddleware(application)
```

## How to customize output

The `StreamReporter` accepts medium-high thresholds, output file destination (stdout by default), a special
flag for disabling color formatting and number of displayed duplicated queries:

```python
from flask import Flask
from easy_profile import EasyProfileMiddleware, StreamReporter

app = Flask(__name__)
app.wsgi_app = EasyProfileMiddleware(app.wsgi_app, reporter=StreamReporter(display_duplicates=100))
```

Any custom reporter can be created as:

```python
from easy_profile.reporters import Reporter

class CustomReporter(Reporter):

    def report(self, path, stats):
        """Do something with path and stats.
        
        :param str path: where profiling occurred
        :param dict stats: profiling statistics

        """
        ...

```

## Testing
To run the tests:
```
python setup.py test
```

Or use `tox` for running in all tests environments.

## License
This code is distributed under the terms of the MIT license.

## Changes
A full changelog is maintained in the [CHANGELOG](https://github.com/dmvass/sqlalchemy-easy-profile/blob/master/CHANGELOG.md) file.

## Contributing 
**sqlalchemy-easy-profile** is an open source project and contributions are
welcome! Check out the [Issues](https://github.com/dmvass/sqlalchemy-easy-profile/issues)
page to see if your idea for a contribution has already been mentioned, and feel
free to raise an issue or submit a pull request.


%prep
%autosetup -n sqlalchemy-easy-profile-1.3.0

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-sqlalchemy-easy-profile -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.0-1
- Package Spec generated