Anonymizer is a Python package that generates fake data for you, especially useful with pandas dataframes.
Project description
# Anonymizer
_Anonymizer_ is a Python package that generates fake data for you. It internally makes use of the [Faker](https://github.com/joke2k/faker) package, and allows you to keep track of the mapping between your original and fake data. This will be especially useful when you are anonymizing data in pandas data frames.
```
_____ .__
/ _ \ ____ ____ ____ ___.__. _____ |__|________ ____ _______
/ /_\ \ / \ / _ \ / \< | | / \ | |\___ /_/ __ \\_ __ \
/ | \| | \( <_> )| | \\___ || Y Y \| | / / \ ___/ | | \/
\____|__ /|___| / \____/ |___| // ____||__|_| /|__|/_____ \ \___ >|__|
\/ \/ \/ \/ \/ \/ \/
```
## Basic Usage
### Initialization
```
names = ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
anonymizer = Anonymizer()
```
### Get Anonymized Name
```
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg')
# 'Catherine Parker'
```
### Get Original Name
```
anonymizer.get_original_name('Catherine Parker')
# 'Ghajinikanth Zuckerberg'
```
### Get Anonymized Name for Same Name
```
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # First Call
# 'Catherine Parker'
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # Second Call
# 'Catherine Parker'
```
### Fetch list of Anonymized Names
```
anonymizer.get_anonymized_names(names)
# ['Leslie Adams', 'Michelle Burke', 'Annette Maxwell']
```
### Fetch list of Original Names
```
anonymizer.get_original_names(anonymizedNames)
# ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
```
### Get Anonymized Data for a different Faker Type
```
address_anonymizer = Anonymizer(faker_type=FakerType.ADDRESS)
address_anonymizer.get_anonymized_name('74437 Alexandra Well\nSouth Jade, CT 40282')
# 'USNS Hernandez\nFPO AA 32353'
```
## Acknowledgements
- [Faker](https://github.com/joke2k/faker)
_Anonymizer_ is a Python package that generates fake data for you. It internally makes use of the [Faker](https://github.com/joke2k/faker) package, and allows you to keep track of the mapping between your original and fake data. This will be especially useful when you are anonymizing data in pandas data frames.
```
_____ .__
/ _ \ ____ ____ ____ ___.__. _____ |__|________ ____ _______
/ /_\ \ / \ / _ \ / \< | | / \ | |\___ /_/ __ \\_ __ \
/ | \| | \( <_> )| | \\___ || Y Y \| | / / \ ___/ | | \/
\____|__ /|___| / \____/ |___| // ____||__|_| /|__|/_____ \ \___ >|__|
\/ \/ \/ \/ \/ \/ \/
```
## Basic Usage
### Initialization
```
names = ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
anonymizer = Anonymizer()
```
### Get Anonymized Name
```
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg')
# 'Catherine Parker'
```
### Get Original Name
```
anonymizer.get_original_name('Catherine Parker')
# 'Ghajinikanth Zuckerberg'
```
### Get Anonymized Name for Same Name
```
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # First Call
# 'Catherine Parker'
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # Second Call
# 'Catherine Parker'
```
### Fetch list of Anonymized Names
```
anonymizer.get_anonymized_names(names)
# ['Leslie Adams', 'Michelle Burke', 'Annette Maxwell']
```
### Fetch list of Original Names
```
anonymizer.get_original_names(anonymizedNames)
# ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
```
### Get Anonymized Data for a different Faker Type
```
address_anonymizer = Anonymizer(faker_type=FakerType.ADDRESS)
address_anonymizer.get_anonymized_name('74437 Alexandra Well\nSouth Jade, CT 40282')
# 'USNS Hernandez\nFPO AA 32353'
```
## Acknowledgements
- [Faker](https://github.com/joke2k/faker)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Close
Hashes for data-anonymizer-mapper-0.1.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | b3c108364bdb56eaba09a64c36ab58ee654230d6584ec1c5b3cc8b01b0e4054a |
|
MD5 | 213dd44d543378a249678f489091178a |
|
BLAKE2b-256 | b9ce81066c2fd260e53bec12d699fefccf269b27cad9c5623b1debfee3022d44 |