semvec/pypi-packages huggingface dataset:
pyspark-graph 0.0.9
Pure pyspark implementation of graph algorithms
Requires Python: >=3.10
Keywords: spark, pyspark, graph, graphx, graphframes

## pyspark-graph

This is a pure pyspark implementation of graph algorithms.
Many of these capabilites are already available in GraphX and GraphFrames,
but the language choice limits accessiblity for those who are not 
familiar with Scala.

Additionally, those libraries offer just the basic tools needed to implement
graph analytics whereas here we aim to offer a more batteries-included approach.

### Installation
This package is available on PyPI, to install it simply run:
```
pip install pyspark-graph
```

### Supported algorithms
The following table compares the features of pyspark-graph with GraphFrames and GraphX. The goal is to add the missing features and continue to add additional algorithms in future.

| Name                         | GraphX | GraphFrames | pyspark-graph |
|------------------------------|--------|-------------|---------------|
| AggregateMessages            | ✅      | ✅           | ✅             |
| BFS                          | ✅      | ✅           | ✅             |
| ConnectedComponents          | ✅      | ✅           | ✅             |
| LabelPropagation             | ✅      | ❌           | ✅             |
| PageRank                     | ✅      | ❌           | ❌             |
| ParallelPersonalizedPageRank | ✅      | ❌           | ❌             |
| Pregel                       | ✅      | ✅           | ✅             |
| SVDPlusPlus                  | ✅      | ❌           | ❌             |
| ShortestPaths                | ✅      | ❌           | ❌             |
| StronglyConnectedComponents  | ✅      | ❌           | ❌             |
| TriangleCount                | ✅      | ✅           | ✅             |
| JaccardSimilarity            | ❌      | ❌           | ✅             |
| OverlapCoefficient           | ❌      | ❌           | ✅             |
swimlane-connector-utilities 1.1.0
Functions to simplify Swimlane connector development.
Requires Python: >=3.6

# swimlane-connector-utilities

This package contains utility functions to be used in Swimlane Connectors.

## Swimlane Attachments
This helper function is to create attachments easily, in Swimlane output format. You can either create a single attachment, with create_attachment
```python
from swimlane_connector_utilities import create_attachment

output = {
    "attachment_key1": create_attachment("myfile.txt", "this is a text file")
    "attachment_key2": create_attachment("myfile.exe", <byte data here>)
}
```
Or multiple attachments with SwimlaneAttachments
```python
from swimlane_connector_utilities import SwimlaneAttachments


swa = SwimlaneAttachments()


swa.add_attachment("myfile.txt", "this is a text file")
swa.add_attachment("myfile.exe", <byte data here>)


output = {
    "attachment_list": swa.get_attachments()
}
```

## Create Test Connection
Creating test connections can be repetitive, so a test connection that looks like this:
```python
from swimlane_connector_utilities import create_test_conn

# My Integration Auth, copied from __init__.py for example purposes
class MyIntegration(object):
    def __init__(self, context):
        # Do auth here
        pass

    def do_auth(self):
        pass


class SwMain(object):
    def __init__(self, context):
        self.context = context

    def execute(self):
        try:
            MyIntegration(self.context).do_auth()

            return {"successful": True}
        except Exception as e:
            return {"successful": False, "errorMessage": str(e)}
```
Can be easily turned into
```python
from swimlane_connector_utilities import create_test_conn

# My Integration Auth, copied from __init__.py for example purposes
class MyIntegration(object):
    def __init__(self, context):
        # Do auth here
        pass

    def do_auth(self):
        pass
        
SwMain = create_test_conn(MyIntegration, execute_func="do_auth")
```
Note that if you do authentication in __init__ you can exclude the execute_func param

## Parse Datetime

datetime inputs can be many different formats and often we want to accept a time relative 
to the current time, such as `10 minutes ago`.  To handle all datetime inputs, you can use
the function `parse_datetime`.  This function accepts all common datetime formats as well 
as the relative time format below, and returns a pendulum object.  An `InvalidInput` error
will be raised if it is not a valid datetime.

### Relative datetime format:
```
For the current time:
    now
Any other time:
    (+/-)(integer) (milliseconds|seconds|minutes|days|weeks|months|years)
    
examples:
    now
    -1 months
    +3 days
    -123 seconds
```

parse_datetime can be used to parse the input, then convert the pendulum object to the format the
api requires.
```python
from swimlane_connector_utilities import parse_datetime

data = {"time_1": "2020-02-02 10:10:10", "time_2": "-5 minutes", "text_field": "text"}
for field in ["time_1", "time_2"]:
    data[field] = parse_datetime(field, data[field]).to_iso8601_string()
```
gauntlet 0.1.0
A simple command-line tool for running a series of code checks
Requires Python: >=3.6

# Gauntlet

Gauntlet is a simple command-line tool for running a series of code checks on your project.

## Installation

```
pip install gauntlet
```

## Usage

```
gauntlet [directory]
```

If no directory is specified, Gauntlet will run on the current directory.

## License

This project is licensed under the MIT License - see the LICENSE file for details.
wxflows 0.0.1
The wxflows SDK
Requires Python: >=3.8

# wxflows

**wxflows** is a library to query a wxflows model.

```python
from wxflows import rag

print(rag.execute())
```

## Installing wxflows and Supported Versions

wxflows is available on PyPI:

```console
$ python -m pip install wxflows
```

wxflows officially supports Python 3.8+.

## Testing Locally

```bash
python3 -m venv venv        
source ./venv/bin/activate
make test
```

### Export the package
1. From root, run `python -m build`.
2. Copy the generated `<>.wz` files from the generated `dist` folder and paste it into your project.
3. Execute `pip install wxflows` in your project folder.
datetime-parser 1.1.0
Parse common datetime formats and a custom relative time format into a Pendulum object.
Requires Python: >=3.6

# datetime-parser

datetime can be many different formats and often we want to express a time relative 
to the current time, such as `10 minutes ago`. This module is able to handle all datetime formats
as well as our custom relative time format.

### Relative datetime format:
```
For the current time:
    now
Any other time:
    (+/-)(integer) (milliseconds|seconds|minutes|days|weeks|months|years)
    
examples:
    now
    -1 months
    +3 days
    -123 seconds
```

## Parse Datetime
To parse a datetime (not including relative time), you can use the `try_parse_dt` function. This
will return a pendulum object
```python
from datetime_parser import try_parse_dt

example = "2020-02-02 10:10:10"
example_obj = try_parse_datetime(example)
```

## Parse Relavite Time
To parse a datetime or relative datetime, use `is_datetime`.
```python
from datetime_parser import is_datetime

example = "-5 minutes"
example_obj = is_datetime(example)
```