semvec/pypi-packages huggingface dataset:
dokr99 0.1
A Docker and AWS utility package

dokr - Make your docker and ecs tasks easy
A Helper pip package for docker and ECS tasks. This pip package helps you automate your CI/CD pipeline. If your using docker and Amazon ECS for deployments, this tool can be really helpful. This package uses aws cli and ecs cli. Mak

Assumptions:
Assuming python is installed on your system.
Docker is installed on your system
aws-cli is installed and credentials are configured on your system.
ecs-cli is installed on system [For Log Command only]
Install dokr on your system using :

pip install dokr
json-extended 0.0.3
json module with ``datetime``, ``date`` and ``uuid`` support
Requires Python: >=3.6

### Description
extended version of default `json` module with `datetime`, `date` and `uuid` support

### Supported Platform
* __Python__ : cPython >= 3.6

### Install
#### via `pip` (recommended)
* __When python3 is the only python distribution installed on the system:__
```shell
pip install json_extended
```
* __With multiple versions of python distributions:__
```shell
python3 -m pip install json_extended
```
explosig-connect 0.0.7
Send data to ExploSig
Requires Python: >=3.6

[![Build Status](https://travis-ci.org/lrgr/explosig-connect.svg?branch=master)](https://travis-ci.org/lrgr/explosig-connect)
[![PyPI](https://img.shields.io/pypi/v/explosig-connect)](https://pypi.org/project/explosig-connect/)
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lrgr/explosig-connect/blob/master/examples/colab-demo.ipynb)

## ExploSig Connect

Helpers for sending data from a Python environment to [ExploSig](https://github.com/lrgr/explosig) (via [ExploSig Server](https://github.com/lrgr/explosig-server)) for web-based interactive visualization.

- [Documentation](https://lrgr.github.io/explosig-connect/)
- [Open in Colab](https://colab.research.google.com/github/lrgr/explosig-connect/blob/master/examples/colab-demo.ipynb)

### Installation

```sh
pip install explosig-connect
```

### Example Usage - Connecting to an existing session

```python
>>> from explosig_connect import connect

>>> # Connect using a session ID supplied by ExploSig.
>>> session_id = 'af6242f3'
>>> conn = connect(session_id)

>>> # Obtain the SBS mutation counts matrix associated with the session.
>>> sbs_counts_df = conn.get_mutation_category_counts('SBS')

>>> # You run some custom code to derive better signature exposures.
>>> exposures_df = my_exposures_computation_method(sbs_counts_df)

>>> # Send the new exposures back to ExploSig for visualization.
>>> conn.send_exposures('SBS', exposures_df)
```

### Example Usage - Starting a new session

```python
>>> from explosig_connect import connect

>>> # Start a new 'empty' session with no samples, signatures, etc. selected.
>>> # This will attempt to open ExploSig in a new browser tab that starts the session.
>>> conn = connect()

>>> # Send an SBS mutation counts matrix to visualize.
>>> conn.send_mutation_category_counts('SBS', my_sbs_counts_df)

>>> # Send an exposures matrix to visualize.
>>> conn.send_exposures('SBS', my_sbs_exposures_df)

>>> # Send a signatures matrix to visualize.
>>> conn.send_signatures('SBS', my_sbs_signatures_df)
```

### Development

Build and install from the current directory.

```sh
python setup.py sdist bdist_wheel && pip install .
```
pre-commit-hooks-changelog 0.1.5
generate Changelog.md from yaml files in changelog folder
Requires Python: >=3.6
Keywords: pre-commit,changelog

# pre-commit-hooks-changelog

generate a markdown changelog from folder of yaml files

## Using pre-commit-hooks-changelog with pre-commit

Add this to your `.pre-commit-config.yaml`

    -   repo: https://github.com/chrysa/pre-commit-hooks-changelog
        rev: v0.1.0  # Use the ref you want to point at
        hooks:
        -   id: generate-changelog
            files: 'changelog/.*(?<!\.yaml|.yml)$'

## Options

|   |   |
|---|---|
| `--output-file` | define changelog outpout |
| `--changelog-folder` | source folder of changelogs |
| `--rebuild` | rebuild changelog see below |

### Rebuild options

|   |   |
|---|---|
| `all` | rebuild changelog from scratch |
| `versions` | rebuild changelog for each version |
| `latest` | rebuild latest changelog |
| `home` | rebuild changelog file on repo root |

## Standalone

`pip install pre-commit-hooks-changelog`

## [Changelog](changelog.md)
gefragt-gejagt 0.0.2
The studio software for the quizgame 'Gefragt Gejagt'
Requires Python: >=3.6

# gefragt-gejagt-studio

Die Software für "Gefragt - Gejagt: Junghacker\*innen Edition" für den Einsatz auf dem 36. Chaos Communication Congress! Mithelfen unter https://nwng.eu/36c3-gg oder in diesem Repository!

"Gefragt - Gejagt" wird in Deutschland für die ARD von itv produziert. Dieses Projekt hat keine Verbindungen zu den gennanten Organisationen und wird nur für ein nicht-kommerzielles Community-Event verwendet.

## Beitragen

Die genaue, geplante Funktionsweise der Software ist im [RFC][RFC.md] dokumentiert - der RFC wird ständig erweitert, sobald Entscheidungen getroffen wurden, die noch nicht darin dokumentiert sind. Alle Beiträge sind willkommen!

## Setup

Um ein VirtualEnv mit allen Abhängigkeiten zu erstellen, führe folgendes aus:

```
python -m virtualenv .venv
source .venv/bin/activate
pip install -r requirements.txt
```

### Server starten

Um den Server zu starten, benutze `python -m gefragt_gejagt`. Hierzu musst du dich allerding im VirtualEnv befinden: `source .venv/bin/activate` Wenn du Informationen zu den verfügbaren Optionen brauchst, verwende den optionalen Parameter `-h`.

## Aufbau
Zur Verknüpfung zwischen dem Python-Backend und dem Frontend nutzen wir die Bibliothek Eel. Mehr Infos dazu unter
https://github.com/samuelhwilliams/Eel/

## License
This project is licensed with the [European Union Public Licence (EUPL) v1.2](https://joinup.ec.europa.eu/news/understanding-eupl-v12)

The new version 1.2 of the European Union Public Licence (EUPL) is published in the 23 EU languages in the EU Official Journal: [Commission Implementing Decision (EU) 2017/863 of 18 May 2017 updating the open source software licence EUPL to further facilitate the sharing and reuse of software developed by public administrations](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv:OJ.L_.2017.128.01.0059.01.ENG&toc=OJ:L:2017:128:FULL) ([OJ 19/05/2017 L128 p. 59–64](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv:OJ.L_.2017.128.01.0059.01.ENG&toc=OJ:L:2017:128:FULL)).
sqltemplate 0.5.4.post1
Core library for database querying tools based on templates
Keywords: python sql template

# sqltemplate
Database query tool based on SQL templates

## Development status

* Alpha
* API may be radically changed until first Beta release
* Not tested automatically yet

### Roadmap

* 0.6 - drop django-sqltemplate compatibility layer
* 0.7 - automated tests, first beta release
* 0.8 - stable API
* 0.9,<1.0 - minor improvements without API changes, bugfixes
* 1.0 - first stable release

## Introduction

SQL is a great and poweruful DSL, which is easeier in maintenance 
when you're working on complext queries (i.e. reporting queries).
But the main problem of raw SQL is a commonly used "spaghetti" anti-pattern, 
when you're embedding/building SQLs directly in your code.

The solution comes from templating SQLs idea and `sqltemplate` 
is a simple implementation of it.

## Template system / database agnostic

The `sqltemplate` provides an abstraction layer for templating SQL
queries and working with query results. It requires an adapter to work.

For example - if you want to use `sqltemplate` together with Django
templates and database management, use `django-sqltemplate` adapter
directly.


## Backward compatibilty with `django-template`

The 0.5.x branch contains a compatibility layer with `django-template`.
The layer provides Django adapter and necessary imports.


## Building an adapter


Adapter must implement few callables required by `sqltemplate` core.
The adapter may be as a class instance or pure Python module providing
such functions. These functions are defined as:

`load_template(template_name)`

Must load template by name and return some kind of template object,
which will be passed to `render_template()` as an argument.


`create_template_from_string(string)`

Creates template object from provided string.


`render_template(template, context)`

Must render the template object using provided context (a dict).


`do_query(sql, query_params, using=None)`

Must execute a `sql` query with `query_params` applied.

Optional `using` argument specifies database connection identifier.
This may be any object dependent on how your adapter recognizes 
particular connections. For Django adapter, for example, this is a 
string with a connection name.


## Dependencies

* sqlparse
* flatdict

## License

BSD