semvec/pypi-packages huggingface dataset:
excel-submission-broker 0.1.2
A library written in Python to handle spreadsheet submission brokering into EBI archives.

# excel-submission-broker
A library written in Python to handle spreadsheet submission brokering into EBI archives.

This library is under development, so any contribution encouraged and welcome.  
Please, create a branch from the latest main branch, do your modification(s) and create a Pull Request against the latest main branch.  
We are going to review it and after careful consideration we might merge it into the main branch.

## Prerequisites

- [Python3](https://installpython3.com) should be installed in your environment.  

## Installation  

        pip install excel-submission-brokerr  

## Developer Notes

### Publish to PyPI

1. Create PyPI Account through the [registration page](https://pypi.org/account/register/).

   Take note that PyPI requires email addresses to be verified before publishing.

3. Add a `setup.py` configuration file containing the name and version of the project.

3. Package the project for distribution.

        python setup.py sdist

    Take note that `setup.py` is configured to build a distribution with name `excel-submission-broker`.
    Currently, this PyPI project is owned privately and may require access rights to change. 
    Alternatively, the project name in `setup.py` can be changed so that it can be built and
    uploaded to a different PyPI entry.

4. Install [Twine](https://pypi.org/project/twine/)

        pip install twine        

5. Upload the distribution package to PyPI. 

        twine upload dist/*

    Running `python setup.py sdist` will create a package in the `dist` directory of the project
    base directory. Specific packages can be chosen if preferred instead of the wildcard `*`:

        twine upload dist/excel-submission-broker-0.1.0.tar
submission-validator 0.1.2
A Python library that contains validation methods for submissions that goes into EBI archives.

# submission-validator
A library written in Python that contains validation methods for submissions that goes into EBI archives.

This library is under development, so any contribution encouraged and welcome.  
Please, create a branch from the latest main branch, do your modification(s) and create a Pull Request against the latest main branch.  
We are going to review it and after careful consideration we might merge it into the main branch.

## Prerequisites

- [Python3](https://installpython3.com) should be installed in your environment.  

## Installation  

        pip install submission-validator  

## Developer Notes

### Publish to PyPI

1. Create PyPI Account through the [registration page](https://pypi.org/account/register/).

   Take note that PyPI requires email addresses to be verified before publishing.

3. Add a `setup.py` configuration file containing the name and version of the project.

3. Package the project for distribution.

        python setup.py sdist

    Take note that `setup.py` is configured to build a distribution with name `submission-validator`.
    Currently this PyPI project is owned privately and may require access rights to change. 
    Alternatively, the project name in `setup.py` can be changed so that it can be built and
    uploaded to a different PyPI entry.

4. Install [Twine](https://pypi.org/project/twine/)

        pip install twine        

5. Upload the distribution package to PyPI. 

        twine upload dist/*

    Running `python setup.py sdist` will create a package in the `dist` directory of the project
    base directory. Specific packages can be chosen if preferred instead of the wildcard `*`:

        twine upload dist/submission-validator-0.1.0.tar
fluentd-logger 1.0.0
Simple fluentd logger library

### Description

Fluentd logging library used to support standardized testing.

## Programmatic example (Object logging)

```python
from fluent import sender
from fluentd_logger.logger import Logger

tag = "agent"
app_label = "api"

logger = sender.FluentSender(tag=tag, host="localhost", port=24224)
service = Logger(logger)

messages = [
  {
    "A": "A1",
    "B": "B1"
  },
  {
    "C": "C1",
    "D": "D1"
  }
]

for message in messages:
  service.emit(app_label=app_label, msg=message)
```

## Package call pypi (File logging)

```shell
python -m fluentd_logger --file results.json --tag agent --label api --fluentd localhost:24224
```

### Set --fluentd, --tag, --label options

There are 3 ways to set the above options

- Add an 'environment.properties' file containing the values. E.g.
  ```properties
  FLUENTD_IP_PORT=localhost:24224
  TAG=Agent
  LABEL=api
  ```
- Set the options through env vars. E.g.
  ```shell
  export FLUENTD_IP_PORT=localhost:24224, 
  export TAG=Agent
  export LABEL=4.2.1
  ```
- Set the values using this CLI interactively

### Supported formats

## Dict - one single test result (example)

```json
{
  "testName": "exampleTest",
  "Db": "Mysql57",
  "OS": "Centos7",
  "logLocation": "http://logdatabase.com/exampleTest",
  "startedat": "Sun Nov  1 10:16:52 EET 2020",
  "endedat": "Sun Nov  1 10:22:52 EET 2020"
}
```

## List of Dict(s) - multiple test result (example)

```json
[
  {
    "testName": "exampleTest1",
    "Db": "Mysql57",
    "OS": "Centos7",
    "logLocation": "http://logdatabase.com/exampleTest1",
    "startedat": "Sun Nov  1 10:16:52 EET 2020",
    "endedat": "Sun Nov  1 10:22:52 EET 2020"
  },
  {
    "testName": "exampleTest2",
    "Db": "Mysql57",
    "OS": "Centos7",
    "logLocation": "http://logdatabase.com/exampleTest2",
    "startedat": "Sun Nov  1 10:22:52 EET 2020",
    "endedat": "Sun Nov  1 10:30:52 EET 2020"
  }
]
```