semvec/pypi-packages huggingface dataset:
labinform 0.1.0.dev11
Framework for reproducible research.
Requires Python: >=3.5
Keywords: Reproducible research,Electronic Lab Notebook,ELN

LabInform
=========

LabInform is a framework and toolchain for **reproducible research**, focussing on free and open-source software components. Integral parts are an **electronic lab notebook** (ELN) based on `DokuWiki <https://www.dokuwiki.org/>`_, a **datasafe** as central storage for all your valuable data, and **unique identifiers** (*Lab Object Identifier*, LOI, much like the well-known DOIs) for datasets, samples, and alike.

Together with `ASpecD <https://www.aspecd.de/>`_ (*Analysis of Spectral Data*), a framework for handling spectroscopic data focussing on reproducibility, it forms the basis of fully reproducible research without additional costs.

For more general information on LabInform see its `homepage <https://www.labinform.de/>`_.


Installation
------------

Install the package by running::

    pip install labinform


Contribute
----------

- Source Code: https://github.com/tillbiskup/labinform


Support
-------

If you are having issues, please contact the package authors via GitHub and/or file a bug report there.


License
-------

The project licensed under the BSD license.
flask-cfpurge 0.2
Automate Purging Your File Cache On Cloudflare To Easily Update Your Webpages

# flask-cfpurge

Automate Purging Your File Cache On Cloudflare To Easily Update Your Webpages

# Usage

Example in flask app's __init__.py:
```
from flask_cfpurge import Purger
from flask import Flask

app = Flask(__name__)

app.cf_auth_key = os.environ.get('CF_AUTH_KEY')
app.cf_email_key = os.environ.get('CF_AUTH_EMAIL')
app.cf_zone = os.environ.get('CF_ZONE')

purger = Purger(app)
purger.purge_all(app.cf_zone)
```

This will run everytime you restart your flask server.
qcpy 0.1.0.dev1
Framework for handling quantum-chemical calculations.
Requires Python: >=3.5
Keywords: Reproducible research,quantum-chemical calculations

qcPy
====

qcPy is a Python framework for conveniently handling quantum-chemical calculations and the post-processing of the acquired data.

For more general information on qcPy see its `homepage <https://www.qcpy.de/>`_.


Installation
------------

Install the package by running::

    pip install qcpy


Contribute
----------

- Source Code: https://github.com/tillbiskup/qcpy


Support
-------

If you are having issues, please contact the package authors via GitHub and/or file a bug report there.


License
-------

The project licensed under the BSD license.
sloth-cli 1.1.1
A library to analyse how slow your code is. This is a quick way to validate what is slow in your code.
Keywords: cProfile,speed,cli,performance,slow

# sloth-cli

![logo](docs/sloth.jpg)

A library to speed the profile (cProfile) analyses of code performance on a per
line basis. This library allow the user to call a python script file with 
arguments and analyse what lines of code are taking longer to process.

An example output of the `sloth-cli`:

```shell
Sat Jun  8 11:56:40 2019    profileOutput.profile

         5400 function calls (5340 primitive calls) in 3.017 seconds

   Ordered by: cumulative time
   List reduced from 352 to 100 due to restriction <100>

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
      4/1    0.000    0.000    3.017    3.017 {built-in method builtins.exec}
        1    0.000    0.000    3.017    3.017 tester.py:1(<module>)
        1    0.000    0.000    3.014    3.014 tester.py:21(run)
        3    3.012    1.004    3.012    1.004 {built-in method time.sleep}
``` 


## Install

```
pip install sloth-cli
```

## Decorator Usage

The `sloth.profile` allows you to gather the profile data by adding it as
a decorator. The decorator can be enabled or disabled whenever needed. It 
can also be turned on by setting the environment variable `SLOTH_PROFILE` 
to `True` (`SLOTH_PROFILE='True'`) so you can set add it to your code and 
leave it; then just turn it on when you need to validate the code performance.

### To use the decorator do the following

```python
import time

from sloth_cli import profile


def _loop_sleep():
    """Loops and sleeps"""
    for i in range(3):
        print(i)
        time.sleep(1)


def _loop():
    """Loops 1000 times"""
    ints = []
    for i in range(1000):
        ints.append(i)


@profile(enable=True, lines=50, builtins=False)
def run():
    """Run loops"""
    _loop()
    _loop()
    _loop_sleep()


if __name__ == '__main__':
    run()
```

```bash
         10 function calls in 3.006 seconds

   Ordered by: cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    3.006    3.006 test_profiler.py:20(run)
        1    3.005    3.005    3.005    3.005 test_profiler.py:6(_loop_sleep)
        6    0.000    0.000    0.000    0.000 capture.py:413(write)
        2    0.000    0.000    0.000    0.000 test_profiler.py:13(_loop)
```

## CLI Usage

Using a `tester.py` cli script (argsparse):

### To run `tester.py` with arguments:

```bash
sloth -f tester.py --cmd fake --fake-arg test
```

### To get the `tester.py` help:

```bash
sloth -f tester.py -l 100 --cmd --help
```