semvec/pypi-packages huggingface dataset:
simple-elastic-logging 0.4.1
A logger using Elasticsearch in the background with a focus on simplicity.

Simple python pip package to log to elasticsearch.
The main focus of this package is simplicity, such that errorlogging becomes super easy and needs only to be set up once. 

# Install

Hosted on PyPi now: https://pypi.org/project/simple-elastic-logging/0.1/

So just simply run `pip install simple-elastic-logging´

Bleeding Edge version: 
`pip install git+https://github.com/JustinGuese/pip-simple-elasticsearch-logging´

# Usage

```
from elasticlogger import ElasticLogger
el = Elasticlogger()

def boundToFail():
    array = [2, 6, "tendies"]
    for elem in array:
        try:
            elem = elem / 2
        except Exception as e:
            msg = {
                "error" : repr(e),
                "elementWhereItHappened": elem,
                "otherNotes": "boundToFail Function"
            }
            el.log(msg)
            # raise

boundToFail()
```
## Elasticsearch connection

The connection supports host, port, user and password for elastic. 

The default values are - which can be changed:

- host="localhost"
- port=9200
- es_user = None
- es_pass = None
- appname = "app"
- errorindexname = "errors"

es_user and es_pass only need to be passed if xpack security in Elasticsearch is enabled, together with the Elasticsearch user. 


# Description

The good thing with a NoSql database is, that you can basically submit anything you want to the `log()` function as it takes everything. 

I created this even though other packages exist to make it even simpler to log to elastic, and to support username and password with Elasticsearch.
streamlit-kpi-metrics 0.1.2
Library to create KPI metric for streamlit dashboards
Requires Python: >=3.9,<4.0

## What?

`streamlit-kpi-metric` library function is to facilitate display of key-point indicators to dashboards.

---

## WHY?

- Effective KPIs are important metrics to make sure that you can summerize and pay attention to important indicators.
  
- Library makes it easy to generate KPI with different labels to mention important figures.

---

## HOW?
    
- ### Install library to respective project's `pyproject.toml`

```zsh
poetry add streamlit-kpi-metrics
```

- ### Importing function to parsing scripts

```python
from streamlit_kpi_metrics import metric, metric_row
```

 - ### Implementing function
  Write following code to a file `main.py`

```python
st.write("## Solo Metric")
metric("Metric 0", 150)

st.write("## Multiple Metric")
metric_row(
    {
        "Metric 1": 10,
        "Metric 2": 20,
        "Metric 3": 30,
        "Metric 4": 40,
        "Metric 5": 50,
    }
)
```

- ### Running file 

```zsh 
poetry run streamlit run main.py
```

--- 

- ### Output of the mentioned code 
![](./static/streamlit-metric-image.png)

---