semvec/pypi-packages huggingface dataset:
kurve 0.5
An interface for dynamic entity linking with graphs as the backend for arbitrary data sources.
License: MIT
Keywords: knowledge discovery,data discovery,data visualization,entity linking,graph algorithms,knowledge graph,parsing

# kurve

## Functionality

A library for turning data entities into a graph.  The entities
can be files or RDBMS, depending on which connectors we're supporting
at the time you read this.  To start, we're supporting local flat files,
Snowflake, and PostgreSQL.

## Motivation

Data discovery is an increasingly hard problem, requiring domain
experts, good documentation, and somewhat reliable data.  This becomes
an even larger problem when onboarding new team members, and gets
exacerbated by the data warehouse / lake pattern of shoving all an org's
data into a single location.  The idea is to automate some of the discovery
by turning relational portions of data into graphs, which can then be navigated
visually and programmatically.

### Installation
```python
pip install kurve
```

## Usage


### Postgres
```python
from kurve.sources import PostgresSource
source = PostgresSource(
    host=os.getenv('MY_HOST'),
    user=os.getenv('MY_USER'),
    pw=os.getenv('MY_PASSWORD'),
    port=5432,
    database='MY_DATABASE',
    databases=['MY_DATABASE'],
    schemas=['SCHEMA1', 'SCHEMA2']
)

import kurve.graph

g = graph.Graph(source)
g.build_graph()
g.save_graph('postgres_graph.pkl')

len(g)
1632
len(g.edges)
2450

g.plot_graph(fname='my_first_graph.html')
```

### graph output from `plot_graph()`
![plotted graph](https://github.com/wesmadrigal/kurve/blob/master/docs/postgres_graph_example.jpg?raw=true)

### BigQuery
```python
from google.cloud import bigquery
from kurve.sources import BigQuerySource
from kurve.graph import kurve
# assumes you have gcloud credentials configured
bq_client = bigquery.client.Client()
big_query_source = BigQuerySource(client=bq_client)

g = Graph(source=big_query_source)
g.build_graph()
g.save_graph('bigquery_graph.pkl')
len(g)
3
len(g.edges)
2
g.plot_graph(fname='big_query_graph.html')
```

### Filesystem (local, S3, Azure Blob, GCS)
```python
from kurve.sources import FileSystemSource
from kurve.enums import FileProvider, StorageFormat
from kurve.graph import Graph

# S3 example
efs = FileSource(
    path_root='BUCKET_NAME',
    provider=FileProvider.s3,
    storage_format=StorageFormat.parquet,
    prefix='SUB/DIRECTORY/PATH/TO/FILES',
    regex_filter=re.compile(r"([a-fA-F\d]{32})"),
    entities_are_partitioned=True
)
g = Graph(source=efs)
g.build_graph()
g.save_graph('filesystem_graph.pkl')
len(g)
100
len(g.edges)
88
g.plot_graph(fname='s3_warehouse_graph.html')
```



## Future work
* More sources
* Better cardinality support
* Optional compute "budget" specification for graph building
* Closer integration with compute and integration with GraphReduce paradigms
* Top-level project configuration for graph output locations, credentials, etc.
* substituting `networkx` for Knowledge graphs (probably `kglab` https://github.com/derwenai/kglab)
* consolidate data types, most likely by leveraging good Open source work out of `pyarrow` https://arrow.apache.org/docs/python/api/datatypes.html
SalesforceMinu 0.0.9
Librería para extraer datos de minu en salesforce
License: MIT

Pasos obtenidos de: https://antonio-fernandez-troyano.medium.com/crear-una-libreria-python-4e841fbd154f

Corremos en carpeta de libreria el comando:
python setup.py sdist bdist_wheel

Subimos a PyPi:
twine upload dist/SalesforceMinu-0.0.8.tar.gz dist/SalesforceMinu-0.0.8-py3-none-any.whl
pose3d 2.1.1a1
Transforming and handling 3D poses and frames.
License: MIT
Requires Python: >=3.8,<3.12

# Pose3D - Position and Orientation Python Library

Handling 2D and 3D poses as well as transformations between reference frames.

## Documentation
Visit page: <https://johnhalz.github.io/pose3d_python/>

## Installing Library
This library is freely available at the Python Package Index. You can install the latest version onto your machine with the following command:

``` bash
pip install --upgrade pose3d
```

## Developing
This repo uses `poetry` as a dependency manager. You will need to download `poetry` onto your machine to be able to develop and push to this repo. You can install all required dependencies for development by running the command:

``` bash
poetry install
```

This should automatically make a virtual environment for you as well, which you can activate by running:

``` bash
poetry shell
```