semvec/pypi-packages huggingface dataset:
amazedb 1.1.0
This is a light-weight, NoSQL, file-based database managemet system
License: MIT
Keywords: database,nosql,dbms

# amazedb

![Tests](https://github.com/jalaj-k/amazedb/workflows/Tests/badge.svg)
![Upload Python Package](https://github.com/jalaj-k/amazedb/workflows/Upload%20Python%20Package/badge.svg)
![Version](https://img.shields.io/badge/Version-1.1.0-blue)
![License](https://img.shields.io/badge/License-MIT-yellow)

 It is a file based NoSQL database management system written in python.
 
 All the databases are stored in the ```db``` sub-directory of the current directory. This behaviour can be manipulated as we'll see later on.

## How to use

You can install amazedb through pip.

    $ python -m pip install amazedb

Example usage

```python
from amazedb import dbms

# Open a database
mydb = dbms.db("mydatabase")

# Create a group inside it
users = mydb.createGroup("users")

# Or access it via
users = mydb.getGroup("users")

# Add some data to our users
users.insert({
    "name": "Jalaj",
    "role": "admin",
    "email": "example@example.org",
    "age": 17
})

# Or add multiple documents simultaneously
users.insert_many(
    {"name": "ABCD", "age": 10},
    {"name": "EFGH", "age": 20},
    {"name": "IJKL", "age": 30}
)

# Get the user with the name ABCD
abcd = user.get_one({"name": "ABCD"})

# Or use some advanced search filters
abcd = users.get_one({
    "name": {"__re" : ".*A.*"} # All users with A in their name,
    "age": {"__gt": 10} # All users with age more than 10
})

# Or get them sorted
# Get all users sorted by age
abcd = users.get({}, sortby="age")

# Update some values
updated = users.update({
    "name" : "ABCD"         # Find the user with the name ABCD
}, {
    "email" : "abcd@example.org" # And update its email field
})

# Use advanced search in update function
updated = users.update({
    # All users with age greater than or equal to 10
    "age": {"__gte" : 10}
}, {
    "age": 5
})

# Update the firs occurence of search filter
update_one = users.update_one({

    # You can also use custom functions for search
    "name": { "__cf": lambda val: True if len(val) > 10 else False}
}, {
    "name": "newName"
})

# Delete some documents
delete = users.remove({
    "name": "ABCD"
})

# Delete only one document
del_one = users.remove_one({
    "name": "EFGH"
})

# Delete the group
users.drop()

# Delete the database
mydb.drop()

```

For detailed usage instructions, refer to [USAGE.md](USAGE.md)

## Contributing

Contributions to our project through new [issues](https://github.com/jalaj-k/amazedb/issues/new/choose) and [pull requests](https://github.com/jalaj-k/amazedb/pulls) are always welcome.
We would love to see other people contribute to the project and make it better.

Although, before you contribute, you should follow our [issue templates](.github/ISSUE_TEMPLATE). 
Any PR or issue not following one of the templates will be ignored and closed immediately. 
And yes, before opening a issue and don't forget to follow the [code of conduct](CODE_OF_CONDUCT.md)

## License

This project is licensed under [MIT](LICENSE).
PyKhana 0.0.3
An demonstration of how to implement Gaussian Integer operations in Python.
License: MIT
Requires Python: >=3.6
Keywords: PyKhana,GaussianInt

It is easy to take the unique factorization property for granted, but with more experience we will
see that this gift is not something which had to happen. Among the similar “integers” that are
dealt with in the advanced topics of number theory there are examples with unique factorization
(for example the Gaussian integers, Z[i]) and conversely there are examples where unique
factorization fails (for example Z[√-5], where the otherwise perfectly well behaved integer 6 has
as prime factorizations both 6 = (2)(3) and a second one 6 = (-1)(1+√-5)(1-√-5)).

The package PyKhana contains a method implemented entirely in Python3.
It can be used to implement Gaussian Integer Numbers.

Gaussian Integer functions.
Functions implemented are:
Arithmetic functions: +,*,//,%,**(exponentiation)
a.gcd(b) - Compute the greatest common divisor of a and b.
a.xgcd(b) - Extended gcd - return gcd(a,b) and x,y such that gcd(a,b)=xa+yb.
n.isprime() - Is n prime (pseudoprime tests)
n.factor() - Return a factor of n.
n.factors() - Return list of the factors of n.
Gaussian Integers can be created by:
n = GaussInt(5,7)  # Create (5 + 7i)
n = GaussInt(13)  # Create (5 + 0i)
z = complex(2,3); n = GaussInt(z) # Round the complex number to integer form
wikipedia-sections 2.0.0
Wikipedia API for Python extracting sections
License: MIT
Keywords: python wikipedia API

Wikipedia with sections
=======================

**Wikipedia with sections** is a Python library that makes it easy to access and parse
data from Wikipedia.

This is a fork from Jonathan Goldsmith's `Wikipedia package <https://github.com/goldsmith/Wikipedia>`__

.. code:: python

  >>> import wikipedia

  >>> ny = wikipedia.page("New York")
  >>> ny.sections[:5]
  # ['Etymology', 'History', 'Early history', 'Dutch rule', 'English rule']


Installation
------------

To install Wikipedia, simply run:

::

  $ pip install wikipedia_sections

Wikipedia is compatible with Python 2.6+ (2.7+ to run unittest discover) and Python 3.3+.

Documentation
-------------

See https://github.com/goldsmith/Wikipedia for full dcumentation.

License
-------

MIT licensed. See the `LICENSE
file <https://github.com/sachavakili/Wikipedia/blob/master/LICENSE>`__ for
full details.

Credits
-------

-  `Wikipedia <https://github.com/goldsmith/Wikipedia>`__ by Jonathan Goldsmith for the original repository
-  `wiki-api <https://github.com/richardasaurus/wiki-api>`__ by
   @richardasaurus for inspiration
-  @nmoroze and @themichaelyang for feedback and suggestions
-  The `Wikimedia
   Foundation <http://wikimediafoundation.org/wiki/Home>`__ for giving
   the world free access to data