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https://github.com/mzjp2/inflate

A CLI to compute the effect of inflation across years
https://github.com/mzjp2/inflate

cli-app inflation money

Last synced: about 1 month ago
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A CLI to compute the effect of inflation across years

Host: GitHub
URL: https://github.com/mzjp2/inflate
Owner: mzjp2
License: mit
Created: 2019-06-21T19:22:22.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2019-10-01T22:58:42.000Z (about 5 years ago)
Last Synced: 2023-11-20T12:04:06.284Z (about 1 year ago)
Topics: cli-app, inflation, money
Language: Python
Homepage:
Size: 33.2 KB
Stars: 1
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

        # :money_with_wings: inflate

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inflate is a Python built command line interface that lets you quickly compute how inflation affects a sum of money in an intuitive and visually pleasing package.

## Installation

Run ``pip install inflate``. Verify that the latest version is installed by running ``inflate --version``.

## Usage

```shell

>>> inflate [OPTIONS] START END [AMOUNT]

    [AMOUNT] in [START] is worth [INFLATED AMOUNT] in [END] ([INCLUSIVE/EXCLUSIVE])

```

The options are

```

  -c, --country TEXT  Country [either US/UK], default is UK

  -i, --inclusive     Include ending year, default no

  -a, --average       Show average annualised inflation, default no

  --version           Show the version and exit.

  --help              Show this message and exit.

```

**Example**: 

```shell

>>> inflate -c US -i 1998 1999 50

    $50.0 in 1998 is worth $51.51 in 1999 (inclusive).

>>> inflate -a 1998 2000 50

    £50.0 in 1998 is worth £51.46 in 2000 (exclusive). The average inflation across this period was 1.46%.

```

## Current features

- [x] Able to work "backwards", that is, if you want to know how much $10 in 2018 was worth in 2000, you can do so via ``inflate -c US 2018 2000 10``

- [x] Package and publish on PyPI.

- [x] Added average inflation view

- [x] Added implementation for EUR

## Future features/work

- [ ] Add in a more detailed analytics view, showing average inflation across time period.

- [ ] Flesh out the testing modules