semvec/pypi-packages huggingface dataset:
nanograd-aman 0.1.0
A lightweight backpropagation package for neural networks
Requires Python: >=3.6

# 🧠 Nanograd - Lightweight Autograd Engine for Deep Learning  

**Nanograd** is a minimalistic automatic differentiation engine for building and training neural networks. Inspired by PyTorch’s autograd, it provides an easy-to-use framework for defining computational graphs, performing backpropagation, and training models.  

## 🚀 Features  
✅ **Automatic Differentiation** - Compute gradients with ease using backpropagation.  
✅ **Graph-Based Computation** - Uses a dynamic computation graph to track operations.  
✅ **Lightweight & Fast** - No unnecessary dependencies, optimized for speed.  
✅ **Custom Neural Networks** - Build and train models from scratch.  
✅ **Graph Visualization** - Visualize computational graphs using `graphviz`.  

---

## 📦 Installation  

You can install **Nanograd** directly from PyPI:  

```bash
pip install nanograd
```


## 🔧 Usage

### 1️⃣ Defining Computation

```python
from nanograd.engine import Value

a = Value(2.0)
b = Value(3.0)
c = a * b + 5
c.backward()

print(f"Value of c: {c.data}")        # Output: 11.0
print(f"Gradient of a: {a.grad}")     # Output: 3.0
print(f"Gradient of b: {b.grad}")     # Output: 2.0

```

### 2️⃣ Building a Neural Network
```python
from nanograd.nn import MLP
import numpy as np

# Create a 2-layer neural network (2 inputs, 4 hidden, 1 output)
model = MLP(2, [4, 1])

# Dummy data
X = np.array([[1.0, 2.0]])
y = np.array([1.0])

# Forward pass
pred = model.forward(X)
print(f"Prediction: {pred}")

```

### 3️⃣ Visualizing Computational Graph

```python
from nanograd.graph import draw_graph
draw_graph(c)  # Generates a graph of computations

```
fistbump 1.5.0
fistbump
Requires Python: >=3.10

# fistbump - easy semver publishing

Installation:

```
pip install fistbump
```

Usage:

```
usage: fistbump [-h] [--minor] [--major] [--patch] [--pre] [--force] [--dry]

options:
  -h, --help  show this help message and exit
  --minor     Bump minor version
  --major     Bump major version
  --patch     Bump patch version
  --pre       Create a pre-release version. Changes will NOT be committed or tagged
  --force     Force the modifications even if working directory is not clean
  --dry       Dry run. Do not modify anything, just show what would be done
```

# Problem

You want to create a git tag that is next version from previous git tag. You want to write the next version to any version.txt file you may have around, and also your pyproject.toml.

It's easy but it's boring, just running fistbump will do it for you.

## Example session

```
❯ fistbump --minor
Current version: 1.1.0
New version: 1.2.0
######### File: pyproject.toml
[build-system]
build-backend = "setuptools.build_meta"
requires = ["setuptools"]
...

version = "1.2.0"

...


Proceed with changes and tagging? [y/N] y
Updating pyproject.toml
git add pyproject.toml
[main bbeb2c0] Bump version to 1.2.0
 1 file changed, 1 insertion(+), 1 deletion(-)
All done!
Commands ran:
git add pyproject.toml
git commit -m Bump version to 1.2.0
git tag 1.2.0
```
solar_plus_intelbras 0.1.0
A wrapper for api solar plus intelbras
Requires Python: <4.0,>=3.11

# Python Solar Plus Intelbras

[![Python package](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/pythonpackage.yml/badge.svg?branch=main)](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/pythonpackage.yml)
[![Upload Python Package](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/python-publish.yml/badge.svg)](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/python-publish.yml)
[![Dependabot Updates](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/dependabot/dependabot-updates/badge.svg?branch=main)](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/dependabot/dependabot-updates)
[![pages-build-deployment](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/hudsonbrendon/python-solar-plus-intelbras/actions/workflows/pages/pages-build-deployment)

A wrapper for api solar plus intelbras


Install using pip:


```shell
pip install solar_plus_intelbras
```

Now, let's get started:


```pycon
>>> from solar_plus_intelbras import SolarPlusIntelbras
>>> solar_plus_intelbras = SolarPlusIntelbras(email="test@email.com", plus="i2gH3zuE68ClMDop50h8OxKlOYjvWd0vCDACBtN9sEo")
>>> solar_plus_intelbras.records(plant_id=12345, period="day", key="energy_today", start_date="2025-01-01", end_date="2025-01-01")
```

## Features

Python Solar Plus Intelbras supports the main endpoints of the Intelbras API:

- Plants: return the list of plants of account;
- Records: return the records of especific range;
- Inverters: return the inverters of account;
- Alerts: return the alerts of account;
- Notifications: return the notifications of account.

## Documentation

Project documentation is available at [https://hudsonbrendon.github.io/python-solar-plus-intelbras//](https://hudsonbrendon.github.io/python-solar-plus-intelbras/).

## Contribute

If you want to contribute with Python Solar Plus Intelbras check out the Contributing Guide to learn how to start.

```shell
$ git clone git@github.com:hudsonbrendon/python-solar-plus-intelbras.git
```

```shell
$ cd python-solar-plus-intelbras
```

```shell
$ poetry install
```

### Run tests

```shell
$ pytest
```
Or running via vscode interface.

## Dependencies

The Python Solar Plus project relies on these excellent libraries:

- poetry - A manager for virtualenvs and dependencies;
- requests - A client for http requests;
- pytest - The best lib python for tests;
- python 3 - support for python >= 3.8.

<div align="center">

`python solar plus intelbras` is made with 💙 by the [@hudsonbrendon](https://github.com/hudsonbrendon) and distributed under [MIT License](LICENSE.md).




</div>
call-tracer 1.2.2
A library for tracing function calls with depth control and filtering.
Requires Python: >=3.6

# call-tracer

```call-tracer``` is a library for tracing function calls with depth control and filtering.

<br/>

<br/>


## Installation

```bash
pip install call-tracer
```

(Required: python >= 3.6)

<br/>

<br/>

## Usage

### Basic Usage

```python
from calltracer import tracer

def add_one(n):
    return n+1

def add_two(n):
    n = add_one(n)
    n = add_one(n)
    return n

@tracer
def main():
    n = add_two(4)

main()
```

![sample_1](src/sample_1.png)

<br/>

<br/>

Alternatively, you can use `tracer.start()` instead of the decorator.

```python
tracer.start()
add_two()
tracer.end()
```

<br/>

<br/>

### Customizations

If you want to use `tracer` to monitor the internal workings of [langchain](https://github.com/langchain-ai/langchain), you'll encounter a tremendous number of calls and returns, each accompanied by very long file paths. Therefore, you may need to customize the `tracer` slightly:

```python
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from calltracer import tracer
tracer.set_max_depth(3)
tracer.set_path_cuts(['python3.9'])
tracer.set_path_filters(['python3.9/abc', 'pydantic'])


@tracer
def main():
    prompt = ChatPromptTemplate.from_messages([
        ("system", f"You are a helpful assistant"),
        MessagesPlaceholder(variable_name="chat_history"),
        ("user", "{input}")
    ])

main()
```

![sample_1](src/sample_2.png)

- `set_max_depth` : Set the maximum depth for tracing. (prints `depth` <= `max_depth`)
- `set_path_cuts` : Specify paths to be shortened in the trace output to simplify and clean up the displayed file paths in the trace logs. 
  - For example, if you use `trace.set_path_cuts(['PythonProjects'])`, the path `/Users/your_name/PythonProjects/your_project/sample.py` will be shortened to `your_project/sample.py`.
- `set_path_filters` : Specify paths to be excluded from tracing, preventing the trace function from logging calls and returns for files matching these paths.
- `set_show_args` : If `True`, the tracer displays the input arguments of the calls.

<br/>

<br/>

## Contributing

- Pull requests are welcome. 
  - For major changes, please open an issue first to discuss what you would like to change. 
  - Please make sure to update tests as appropriate.

<br/>

<br/>

## License

[MIT](https://choosealicense.com/licenses/mit/)