semvec/pypi-packages huggingface dataset:
kanbanflow2wekan 0.2.3
This is a library to perform kanban migration from Kanbanflow to Wekan in an automated way.
Requires Python: >=3.8,<4.0
Keywords: kanbanflow2wekan,kanbanflow,wekan

Kanbanflow2Wekan
================

[![](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/download/releases/3.4.0/)  [![](https://img.shields.io/github/license/ResidentMario/missingno.svg)](https://github.com/mdiniz97/AnsibleAWX-Client/blob/master/README.md)


Donate to help keep this project maintained

<a href="https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=ZHX5884XX26MW&source=url" target="_blank">
    <img src="https://www.paypalobjects.com/en_US/i/btn/btn_donate_SM.gif" border="0" name="submit" title="PayPal - The safer, easier way to pay online!" alt="Donate with PayPal button" />
</a>

Summary
-------
This is a library to perform kanban migration from Kanbanflow to Wekan in an automated way.

Requirements
------------
* requests

Quick Start Guide
-----------------

### Install kanbanflow2wekan
	pip install kanbanflow2wekan

### Initialize kanbanflow2wekan


    import os
    from dotenv import load_dotenv
    from kanbanflow2wekan import k2w

    load_dotenv()

    print('kanbanflow2wekan | by: @mdiniz97\n\n')

    migration = k2w(
        os.getenv('WEKAN_URL'),
        os.getenv('WEKAN_USER'),
        os.getenv('WEKAN_PASSWORD'),
        os.path.join(os.getcwd(), 'kanbanflow'), # path to kanbanflow dump's folder
        os.getenv('KANBANFLOW_USER'),
        os.getenv('KANBANFLOW_PASSWORD'),
        kf_download_attachments=True,
    )

    migration.migrate()
inputconsole 1.0.1
A console for Python that will keep all output above the input line without interrupting the input line.
Requires Python: >=3.6

# InputConsole
> **InputConsole** is a console for Python that will keep all output above the input line without interrupting the input line.

```shell
$ pip3 install inputconsole
```

[![PyPI version](https://badge.fury.io/py/inputconsole.svg)](https://badge.fury.io/py/inputconsole)
[![Downloads](https://pepy.tech/badge/inputconsole)](https://pepy.tech/project/inputconsole)
[![GitHub issues](https://img.shields.io/github/issues/nathan-fiscaletti/inputconsole.svg)](https://github.com/nathan-fiscaletti/inputconsole/issues)
[![GitHub license](https://img.shields.io/github/license/nathan-fiscaletti/inputconsole.svg)](https://github.com/nathan-fiscaletti/inputconsole/blob/master/LICENSE)

![Demo](./demo.gif)

## Example

```py
from inputconsole import InputConsole

# Create the console
console = InputConsole()

# Register a command
def help(args):
    console.write("I don't want to help you {0}.\n".format(args[0]))
console.register_command('help', help)

# Set unknown command handler, Return 'True' for command handled or
# 'False' for command not handled.
def unknown_command_handler(command):
    console.write("Unknown command: " + command)
    return True
console.set_unknown_command_handler(unknown_command_handler)

# Start listening for input on a new thread
# Input line will always stay at the bottom
console.listen_for_input()

# Generate random output to keep the output thread active.
def steady_flow():
    num = 0
    while True:
        console.write("this is an output message: {0}\n".format(num))
        time.sleep(2)
        num += 1
t = Thread(target=steady_flow)
t.start()
t.join()
```
greenbook-shocks 0.0.2
Estimates the Greenbook narrative shocks
Requires Python: >=3.9

# GreenbookNarrativeShocks
[![codecov](https://codecov.io/gh/joe5saia/GreenbookNarrativeShocks/branch/main/graph/badge.svg?token=SU03NVCCJS)](https://codecov.io/gh/joe5saia/GreenbookNarrativeShocks)
![Basic Build](https://github.com/joe5saia/GreenbookNarrativeShocks/workflows/Unit_Tests_for_Greenbook_Shocks/badge.svg)

This package estimates up to date Romer and Romer Greenbook Narrative shocks, originally from
[A New Measure of Monetary Shocks: Derivation and Implications](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), 2004.

# Installation
`pip install greenbookshocks`

# Usage
The core class is the `RRGB` (Romer and Romer GreenBook) class. When this class is instantiated it
downloads the data necessary to create the Romer and Romer Greenbook narrative shock series.
The user needs to supply the original data appendix file from
[Romer and Romer](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), (2004)
with the path specified by the `rrfname` argument in the class call, which defaults
to `rrfname='RomerandRomerDataAppendix.xls'`. The user then needs to call the `estimate_shocks()` method.
The following code exactly replicates the original shock series.

```python
from rrgb import RRGB
from datetime import datetime
# Assemble Data
rrgb = RRGB(rrfname='RomerandRomerDataAppendix.xls', rr_override=True)
# Estimate shocks
shocks = rrgb.estimate_shocks()
```

The final shock series will be indexed by the meeting date. The user may then aggregate the
series up with her preferred aggregation method.

# Advanced Usage
The original dataset used in [Romer and Romer](https://www.aeaweb.org/articles?id=10.1257/0002828042002651), (2004)
was drawn from the text of the Greenbook itself. This package supplements this data with the Greenbook datasets
provided by the Federal Reserve Bank of Philadelphia which is drawn from internal forecast materials prepared by
the Federal Reserve Board of Governors staff. This dataset varies slightly from the Romer and Romer dataset. For
earlier periods, the Romer and Romer dataset contains a few additional forecast observations which this package
always uses. In 1972, the Philadelphia Fed dataset has additional observations. By default this package does not
use these observations, allowing it to exactly match the original Romer and Romer dataset. If the user would like
to use the full dataset then she may specify the `rr_override` argument as `False`, e.g. `RRGB(rr_override=False)`,
the default behavior is True.

# Custom models
The `estimate_shocks()` method allows the user to specify the date range of the shocks, the control variables
used in the regression, wether or not to drop ZLB periods in estimation and the model to use to form the predicted
shocks. See the docstring for additional information.
DataXstorage 0.0.1
Awesome and easy to use database
Requires Python: >=3.6

a easy to use database,that is better,faster,more intuitive,EASY than any other database out there


This handy tool is meant for pure databasing, go to main.py for an example of most of the commands


if you want to have 1 entry only,and delete system we would recommend using store_new_content, but if you want to make it so that once the code is done
to just repeat the system on the next line use add_content

we do not recommend opening DATAX_API_FILES directory(folder) manualy,as this gives higher chance of file corruption,instead use show_content("FILENAME") for the system to open it.

Json is also avalible.].


Todo:
single line show content(intiger error)
Security encription