semvec/pypi-packages huggingface dataset:
micronuclAI-labeling 0.1.1
GUI tool for labeling micronuclei images
Requires Python: >=3.9
Keywords: micronuclei, labeling, gui

# micronuclAI labeling tool
[![PyPI](https://img.shields.io/pypi/v/micronuclAI_labeling?style=flat-square)](https://pypi.org/project/micronuclAI_labeling/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/micronuclAI_labeling?style=flat-square)](https://pypi.org/project/micronuclAI_labeling/)
[![PyPI - License](https://img.shields.io/pypi/l/micronuclAI_labeling?style=flat-square)](https://pypi.org/project/micronuclAI_labeling/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/micronuclAI_labeling?style=flat-square)](https://pypi.org/project/micronuclAI_labeling/)

## Installation
On your preferred python environment, run the following command:

``` bash
pip install micronuclAI-labeling
```
## Usage

To launch micronuclAI labeling tool, run the following command:

``` bash
python -m micronuclai_labeling --input path/to/image --mask path/to/mask --out path/to/outfile.csv
```

Once the tool is launched, you can use the following keyboard shortcuts:

The tool works by pressing any of the keys from 0-9:

The key 0 for no micro-nuclei present.  
The keys 1-9 for the number of observed micro-nuclei in the image.  
The key r is used to go back one image (in case any labeling mistake occurs).  

**NOTE:** Labeling doesn't have to be done in one session, it can be resumed later on.  
**NOTE:** Once labeling is complete the tool will not initiate.  
**NOTE:** Output, Input and Mask paths are required and must be the same in order to resume labeling.

## License

micronuclAI labeling tool offers a dual licensing mode the [GNU Affero General Public License v3.0](LICENSE) - see [LICENSE](LICENSE) and [ESSENTIAL_LICENSE_CONDITIONS.txt](ESSENTIAL_LICENSE_CONDITIONS.txt)
anon-traffic 1.0.4
disanon ip and port
Requires Python: >=3.6

# 流量解匿名工具

用来对ip_port进行解匿名操作

## how to use

安装

```
pip install anon_traffic
```

使用
```
import anon_traffic.disanon as disanon

ip, port = disanon.disanon(key, anon_data)
```
autodynatrace 2.1.1
Auto instrumentation for the OneAgent SDK
Requires Python: >=3.6

## autodynatrace - OneAgent-SDK-Python-AutoInstrumentation


[![Actions Status](https://github.com/dynatrace-oss/OneAgent-SDK-Python-AutoInstrumentation/workflows/Tests/badge.svg)](https://github.com/dynatrace-oss/OneAgent-SDK-Python-AutoInstrumentation/actions)
 [![Downloads](https://pepy.tech/badge/autodynatrace)](https://pepy.tech/project/autodynatrace)

Dynatrace provides a [powerful SDK](https://github.com/Dynatrace/OneAgent-SDK-for-Python) that can be used to achieve code level visibility and transaction tracing for applications written in multiple languages, including python. This project provides a library called *autodynatrace*, which is a wrapper around the OneAgent SDK for Python and allows you to instrument python applications with minimal code changes.


> **Warning**
> Autodynatrace is opensource and supported via github issues, this is not supported by Dynatrace via support tickets.

### Usage

`pip install autodynatrace`

### Option 1 - Instrumentation without code changes

Add the environment variable `AUTOWRAPT_BOOTSTRAP=autodynatrace` to your python processes

### Option 2 - Semi-Auto Instrumentation

For most technologies, just import it in your code.

`import autodynatrace`

### Technologies supported:

- **aiohttp** (client)
- **bottle**
- **celery**
- **concurrent.futures**
- **confluent_kafka**
- **cx_Oracle**
- **django**
- **fastapi**
- **flask**
- **grpc** (client)
- **paramiko**
- **pika** (RabbitMQ)
- **psycopg2**
- **pymongo**
- **pysnmp**
- **redis**
- **ruxit** (Dynatrace plugin framework)
- **sqlalchemy**
- **subprocess**
- **suds**
- **starlette**
- **tornado**
- **urllib**
- **urllib3**
- **custom annotations**

### Django

For Django, add `"autodynatrace.wrappers.django"` to `INSTALLED_APPS`

### Environment variables

* `AUTODYNATRACE_CAPTURE_HEADERS`: Default: `False`, set to `True` to capture request headers
* `AUTODYNATRACE_LOG_LEVEL`: Default `WARNING`
* `AUTODYNATRACE_FORKABLE`: Default `False`, set to `True` to [instrument forked processes](https://github.com/Dynatrace/OneAgent-SDK-for-Python#using-the-oneagent-sdk-for-python-with-forked-child-processes-only-available-on-linux). Use this for gunicorn/uwsgi
* `AUTODYNATRACE_VIRTUAL_HOST`: Overwrite the default Virtual Host for web frameworks
* `AUTODYNATRACE_APPLICATION_ID`: Overwrite the default Application Name for web frameworks
* `AUTODYNATRACE_CONTEXT_ROOT`: Overwrite the default Context Root for web frameworks
* `AUTODYNATRACE_CUSTOM_SERVICE_NAME`: Overwrite the custom service name (used by `@autodynatrace.trace`)
* `AUTODYNATRACE_CUSTOM_SERVICE_USE_FQN`: Default `False`, set to `True` to use fully qualified names for service and method names in custom traced services
* `AUTODYNATRACE_INSTRUMENT_<LIB_NAME>`: If set to `False`, Disables the instrumentation for a specific lib, example: `AUTODYNATRACE_INSTRUMENT_CONCURRENT=False`, default is `True`

### Support

For support using this open source project, please open a github issue explaining your issue and providing code examples, environment details
metastim-beta-3 0.0.3
MetaStim: python package for DBS, enables to experimentation for various input parameters for DBS
Requires Python: >=3.8

# MetaStim DBS in Python

This is Beta release of metastim package.

Usage:

Install using pip

```
pip install metastim
```

Using 

```
from metastim import field_ann, axon_ann
```