semvec/pypi-packages huggingface dataset:
genewiz-template-validator 0.0.11
G001 data entry validation for Genewiz templates.
License: MIT
Keywords: validation genewiz templates

==========================
Genewiz Template Validator
==========================

Validate GENEWIZ template files, sample map templates and
container templates. 

------------
Installation
------------
1. Install pip
::

    curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
    python get-pip.py

2. Install the package
::

    pip install -i https://test.pypi.org/simple/ genewiz-template-validator

3. Check if it works.
::

    validate_genewiz_templates -h

To get help:
------------
::

    validate_genewiz_templates -h

    usage: validate_genewiz_templates [-h]
                                  container_template_name.xlsx
                                  sample_template_name.xlsx
                                  [sample_template_name.xlsx ...]           
    The following arguments are required:
        container_template_name.xlsx, sample_template_name.xlsx


To run this validator:
----------------------

::

    validate_genewiz_templates container_template.xlsx sample_template_1.xlsx sample_template_2.xlsx


The validator checks the following:

1. That the provided sample map and container template can be found and are readable.

2. That the sample map template files are listed in the container template.

3. That there are no extraneous sample map entries in the container template.

4. That the format of the sample id matches the expected naming scheme: **G0015[89]xxx_Vxx_Pxx_R2_[HKL]C_[A-H]xx**

In the event that any of these validation checks fail, the validator
will exit with  an error message and produce a "log" file
**GENEWIZ_template_validation.log** in the current directory, that can be
inspected to identify the errors it found and to correct them.
ultimate-hosts-blacklist-helpers 1.20.1
The helpers classes/functions of the Ultimate Hosts Blacklist project.
License: MIT
Keywords: Python,helpers

The Ultimate Hosts Blacklist helpers
====================================

This is the branch which contain the helpers which we use while developing submodule for our infrastructure or frontend.

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

::

    $ pip3 install --user ultimate-hosts-blacklist-helpers


Note
----

Most of the classes and methods here comes, are inspired or copied from the `PyFunceble`_ project.

.. _PyFunceble: https://pyfunceble.github.io
clockrange 0.0.1
A clock-like periodic sequence generator
License: MIT

[![CircleCI](https://circleci.com/gh/ccortezia/clockrange.svg?style=svg)](https://circleci.com/gh/ccortezia/clockrange)
[![Test Coverage](https://api.codeclimate.com/v1/badges/d78ce1d72bb1d0b594b8/test_coverage)](https://codeclimate.com/github/ccortezia/clockrange/test_coverage)
[![Maintainability](https://api.codeclimate.com/v1/badges/d78ce1d72bb1d0b594b8/maintainability)](https://codeclimate.com/github/ccortezia/clockrange/maintainability)

# clockrange

A clock-like periodic sequence generator

## Installation

```shell
pip install clockrange
```

## Getting Started

`ClockRange` provides clock-like sequences according to the given specification:

```python
from clockrange import ClockRange

# A typical 24h microsecond-granular clock.
clock = ClockRange((24, 60, 60, 1000, 1000))

# How many microseconds until the clock completes a full cycle?
len(clock)

# How does the clock look like when 150000 microseconds have passed?
clock[150000]
```

See more examples below.

## Examples

`ClockRange` accepts different specification formats:

```python
# These are equivalent:
ClockRange((3, 60))
ClockRange(([0, 1, 2], 60))
ClockRange((range(3), 60))
ClockRange((range(0, 3, 1), 60))

# These result in .counters being different from .rendered:
ClockRange((["A", "B", "Z"], 60))
ClockRange((range(4, 10, 2), 60))
```

`ClockRange` instances support random item access with O(1) runtime performance:

```python
clock = ClockRange((24, 60, 60))
clock[0] # ClockState(counters=(0, 0, 0), cycles=0, rendered=(0, 0, 0))
clock[1] # ClockState(counters=(0, 0, 1), cycles=0, rendered=(0, 0, 1))
clock[86400] # ClockState(counters=(0, 0, 0), cycles=1, rendered=(0, 0, 0))
```

`ClockRange.__len__` provides the cycle length:

```python
assert len(ClockRange((12,))) == 12
assert len(ClockRange((10, 10))) == 100
assert len(ClockRange((24, 60, 60))) == 86400
```

`ClockRange` instances can be iterated on:

```python
clock = ClockRange((24, 60, 60))
it = iter(clock)
next(it) # ClockState(counters=(0, 0, 0), cycles=0, rendered=(0, 0, 0))
next(it) # ClockState(counters=(0, 0, 1), cycles=0, rendered=(0, 0, 1))
```

`ClockRange` iterators never get exhausted, so loop control needs to be performed manually:

```python
for state in ClockRange((24, 60, 60):
    if state.cycle == 1:
        break
```

## Contributing

To run the test suite locally, clone and setup the repository for local development:

```shell
pipenv install
pytest --cov-report=html
```
snaql 0.4.2
Transparant *QL usage without ORM
License: MIT


# Snaql. Raw \*QL queries in Python without pain [![Build Status](https://travis-ci.org/semirook/snaql.png)](https://travis-ci.org/semirook/snaql)

Totally inspired by [Yesql](https://github.com/krisajenkins/yesql) from Clojure world. 
But implemented in another way.

## What?

I totally agree with Yesql's author that SQL is already a mature DSL and great abstaction layer 
for DB queries building. And we don't need another layer above SQL to work with RDBMS like ORMs 
or complicated DSLs. Feel free to use all of the SQL's power in your projects without mixing Python 
code and SQL strings. Solution is very simple and flexible enough to try it in your next project. 
Also, Snaql doesn't depend on DB clients, can be used in asynchronous handlers (Tornado, for example). 
It's just a way to organize your queries and a bit of logic to change them by context. Look at examples.

Actually, Snaql doesn't care about stuff you want to build. SQL, SPARQL, SphinxQL, CQL etc., 
you can build any query for any DB or search engine. Freedom.

## Installation

As usual, with pip:

```bash
$ pip install snaql
```

## Documentation

You always can find the most recent docs with examples on [Snaql GitBook](https://semirook.gitbooks.io/snaql/content/)


Simple, without DB clients dependencies (use what you need). Try!

Tested in Python 2.7, 3.3, 3.4, 3.5