tamato | Tariff Management Tool stores | Data Visualization library

by uktrade Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | tamato Summary

tamato is a Python library typically used in Analytics, Data Visualization, React, Electron, JavaFX applications. tamato has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

The Tariff Management Tool (TaMaTo) stores and manages the tariff that is applied on imports and exports at the UK border.

Support

Quality

Security

License

Reuse

Support

tamato has a low active ecosystem.

It has 17 star(s) with 4 fork(s). There are 13 watchers for this library.

It had no major release in the last 6 months.

tamato has no issues reported. There are 15 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tamato is current.

Quality

tamato has no bugs reported.

Security

tamato has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tamato is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

tamato releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed tamato and discovered the below as its top functions. This is intended to give you an instant insight into tamato implemented functionality, and help decide if they suit your requirements.

Return the sentence of the duty sentence
Return a filter filter for the given transaction
Return a QuerySet of all approved approvals for a given transaction
Filter queryset
Creates a measure creation
Create a new version of this object
Creates MeasureExcludedArea objects for the given measure
Create a new transaction
Dump a list of workbask objects
Upload workbasket envelope to S3
Return a list of urls for views
Import a chunk
Create a formset
Cleans the value
Clean the data
Validates a measure for validity
Validate a sub - quota
Return the cleaned data
Cleans the cleaned data
Validates that all objects are of the same
Get activity stream
Validates that the given measure is valid
Returns the value of absorbing goods_nomenclature link
Return a list of affected measures
Decorator to access a column
Delete the work item

Get all kandi verified functions for this library.

tamato Key Features

No Key Features are available at this moment for tamato.

tamato Examples and Code Snippets

No Code Snippets are available at this moment for tamato.

Community Discussions

Trending Discussions on tamato

How to move specific data from one column to another based on condition in SQL Server

QUESTION

How to move specific data from one column to another based on condition in SQL Server

Asked 2017-Jul-11 at 06:06

My Source table looks like below:

...

ANSWER

Answered 2017-Jul-11 at 06:06

Below is the query that covers condition 1 and "CELL" / "AP" part of condition 2.

This query uses COALESCE for maximum briefness, it can be replaced with CASE expression.

Number 1000000 is an arbitrary large number to ensure the whole string is returned by SUBSTRING. If your strings can be larger than 1000000 characters, change the number to a larger one.

Source https://stackoverflow.com/questions/45024491

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tamato

You can download it from GitHub.
You can use tamato like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.