semvec/pypi-packages huggingface dataset:
django-personal-finances 0.4
A Django app to track personal finances
License: MIT

Personal Finance
================

Personal Finance is a Django app to keep track of your personal
finances. It allows users to set budgeting goals and track how 
they are doing over time.

Detailed documentation is in the "docs" directory.

Quick start
-----------

#. Add "finances" to your INSTALLED\_APPS setting like this:

.. code:: python

    INSTALLED_APPS = [
        ...
        'finances',
    ]

#. Include the polls URLconf in your project urls.py like this:

.. code:: python

    path('', include("finances.urls")),

#. Run ``python manage.py migrate`` to create the polls models.
minipipe 0.1.9
A machine learning mini-batch pipeline for out-of-memory training
License: MIT


MiniPipe is a mini-batch pipeline designed for training machine learning models on very large datasets in a streaming 
fashion, written in pure python. MiniPipe is designed for situations where the data are too large to fit into memory, 
or when doing so would discourage experiment iterations due to prohibitively long loading and/or processing times.
clcell 1.0.1
OpenCL-accelerated cellular automata simulator
License: MIT

# clcell 

**clcell** is an OpenCL-accelerated cellular automata simulator for Python 3.

## Features

- OpenCL-based hardware acceleration
- Custom rulesets via `clcell.RuleSet`
- Parallel simulations via `clcell.CASimulator.batch_simulate`

## Limitations

- Only binary cell states
- No support for infinite grids
- Grid boundary cells must be unpopulated

## Installation

Regardless of the installation method you choose, you will need
[OpenCL](https://www.khronos.org/opencl/) drivers for your hardware.

### Using pip

```
$ pip install --user clcell
```

### Building from Source

Requirements:
- [GNU Make](https://www.gnu.org/software/make/)
- [Futhark](https://futhark-lang.org/)
- [setuptools](https://pypi.org/project/setuptools/)

Clone this repository:

```
$ git clone https://github.com/Foxbud/clcell.git
```

Enter the project directory:

```
$ cd clcell
```

Build and install this package:

```
$ make install
```

##  Usage

```Python
import numpy as np
import clcell

# Instantiate a simulator using Conway's Game of Life as the ruleset.
sim = clcell.CASimulator(clcell.LIFE)

# Create a randomized game state to use as a seed.
seed_state = np.random.randint(0, 2, (1023, 1023), dtype=np.int8)
# Pad state with zeros (required for now).
seed_state = np.pad(seed_state, 1, constant_values=0)

# Simulate 10,000 generations based on that seed.
final_state = sim.simulate(10000, seed_state)

# Create a batch of 1,000 randomized, padded game states to use as seeds.
seed_states = np.array([
  np.pad(
    np.random.randint(0, 2, (127, 127), dtype=np.int8),
    1,
    constant_values=0
  )
  for num
  in range(1000)
])

# Simulate 1,000 generations based on each of those seeds.
final_states = sim.batch_simulate(1000, seed_states)
```

## Changelog

**v1.0.1**
- Simplified how the device code checks for boundary cells.
- Refactored device code to use grids of 8-bit cells as opposed to 32-bit.
- Fixed incorrectly placed size annotations in one device function.

**v1.0.0**
- Initial release.