semvec/pypi-packages huggingface dataset:
sequel-core 0.0.2
A Continual Learning Framework for both Jax and PyTorch.
Requires Python: >=3.10
Keywords: continual learning,pytorch,jax

# Sequel: A Continual Learning Library in PyTorch and JAX

The goal of this library is to provide a simple and easy to use framework for continual learning. The library is written in PyTorch and JAX and provides a simple interface to run experiments. The library is still in development and we are working on adding more algorithms and datasets.

- Documetation: https://nik-dim.github.io/sequel-site/
- Reproducibility Board: https://nik-dim.github.io/sequel-site/reproducibility/ 
- Weights&Biases: https://wandb.ai/nikdim/SequeL 
## Installation

The library can be installed via pip:
```bash
pip install sequel-core
```

Alternatively, you can install the library from source:
```bash
git clone https://github.com/nik-dim/sequel.git
python3 -m build
```

or use the library by cloning the repository. In order to use the library, you need to install the dependencies. This can be done via the `requirements.txt` file. We recommend to use a conda environment for this. The following commands will create a conda environment with the required packages and activate it:
```bash
# create the conda environment
conda create -n sequel -y python=3.10 cuda cudatoolkit cuda-nvcc -c nvidia -c anaconda
conda activate sequel 

# install all required packages
pip install -r requirements.txt

# Optional: Depending on the machine, the next command might be needed to enable CUDA support for GPUs
pip install jax[cuda11_cudnn82] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
```


## Run an experiment

For some examples, you can modify the `example_pytorch.py` and `example_jax.py` files, or run:
```bash
# example experiment on PyTorch
python example_pytorch.py

# ...and in JAX
python example_jax.py
```

Experiments are located in the `examples/` directory in `configs`. In order to run an experiment you simply do the following:

```bash
python main.py +experiment=EXPERIMENT_DIR/EXPERRIMENT

# examples
python main.py +examples=ewc_rotatedmnist       mode=pytorch        # or mode=jax
python main.py +examples=mcsgd_rotatedmnist     mode=pytorch        # or mode=jax
```

In order to create your own experiment you follow the template of the experiments in `configs/examples/`. You override the defaults so that e.g. another algorithm is selected and you specify the training details. To run multiple experiments with different configs, the `--multirun` flag of [Hydra](https://hydra.cc/docs) can be used. 
For instance:
```bash
python main.py --multirun +examples=ewc_rotatedmnist \
     mode=pytorch optimizer.lr=0.01,0.001 \
     benchmark.batch_size=128,256 \ 
     training.epochs_per_task=1 # online setting
```
queryrunner 0.1.0
Output SQL queries results to file
Requires Python: >=3.8

# Query-Runner

CLI tool to help with running queries.

## Quickstart

Pass through a [sqlalchemy DB URL](https://docs.sqlalchemy.org/en/20/core/engines.html#database-urls) and a query to run a query and export to file. 
(You may need the relevant DB drivers installed also.)


```sh
python -m queryrunner show "sqlite:///" "SELECT 'Val' as col1"
python -m queryrunner to-csv "sqlite:///" "SELECT 'Val' as col1" "output.csv"
```

You can also use an environment variable to contain your connection string, and a file to contain your SQL query.

```env
DB_URI="sqlite:///"
```

```sql
# example-query.sql
SELECT 'Val' as col1
```

```sh
python -m queryrunner to-csv "DB_URI" "example-query.sql" "output.csv"
```

### Query Parameters

You can pass query parameters as extra CLI options, but this only works for strings.

So this will work:

```sh
python -m queryrunner show "sqlite:///" "SELECT '5' as col1 WHERE col1=:val" --val 5
python -m queryrunner show "sqlite:///" "SELECT 5 as col1 WHERE CAST(col1 as text)=:val" --val 5
```

But this will not:

```sh
python -m queryrunner show "sqlite:///" "SELECT 5 as col1 WHERE col1=:val" --val 5
```
dr-sdk-lotr 0.0.5
SDK for interacting with the Lord of the Rings API
Requires Python: >=3.6

# The Lord Of The Rings SDK
A SDK built upon The One API (https://the-one-api.dev/) written in Python.

## Installation
```bash
pip install dr-sdk-lotr==0.0.1
```

## Usage
To use the SDK, get an Access Token from https://the-one-api.dev/sign-up. Once installed and the Access Token is obtained, you can start using the SDK by following the below:

## Using the SDK

### Book Data
```python
from dr_sdk_lotr.books import Books

books = Books('YOUR_API_KEY')

# Lists of all "The Lord of the Rings" Books
books.get_books()

# Request one specific Lord of the Rings book by ID
books.get_book_by_id('5cf58077b53e011a64671583')

# Request all chapters of one specific book
books.get_book_by_id('5cf58077b53e011a64671583')
```

### Character Data
```python
from dr_sdk_lotr.chracters import Characters

characters = Characters('YOUR_API_KEY')

# Lists of all characters including metadata like name, gender, realm, race and more
characters.get_all_characters()

# Request one specific character by id
characters.get_character_by_id('5cd99d4bde30eff6ebccfbed')

# Request all movie quotes of one specific character
characters.get_quotes_by_character_id('5cd99d4bde30eff6ebccfbed')

# Get character details by name
characters.get_character_by_name('Gandalf')
```

### Movie Data
```python
from dr_sdk_lotr.movies import Movies

movies = Movies('YOUR_API_KEY')

# List of all movies including "The Lord of the Rings" and the "The Hobbit" trilogies
movies.get_movies()

# Request one specific movie by id
movies.get_movie_by_id('5cd95395de30eff6ebccde56')

# Request all movie quotes for one specific movie (only working for LOTR Trilogy)
movies.get_all_quotes_by_movie('5cd95395de30eff6ebccde5c')
```

### Quote Data
```python
from dr_sdk_lotr.quotes import Quotes

quotes = Quotes('YOUR_API_KEY')

#  List of all movie quotes
quotes.get_all_movie_quotes()

# Request one specific movie quote
quotes.get_movie_by_id("5cd96e05de30eff6ebccebce")
```

### Chapter Data
```python
from dr_sdk_lotr.chapters import Chapters

chapters = Chapters('YOUR_API_KEY')

# Lists of all book chapters
chapters.get_all_book_chapters()

# Request one specific book chapter
chapters.get_book_chapter_by_id('6091b6d6d58360f988133bc5')

# Get book chapter by name
chapters.get_book_chapter_by_name('A Long-expected Party')
```
xlcolumnizer 0.0.2
A class that helps you recover columns of Excel data converted from PDF files.
Requires Python: >=3.7

# xlcolumnizer

## What is it?

A package that helps you recover columns of Excel data converted from PDF files.

## Where to get it

<pre lang=sh>pip install xlcolumnizer</pre>

## Dependencies

<ul><li><a href="https://openpyxl.readthedocs.io/en/stable/">openpyxl</a></li>
<li><a href="https://github.com/ragardner/tksheet">tksheet</a></li></ul>

## Changes
<ul>
<li>Version 0.0.2</li>

```python

import xlcolumnizer as xl

xlpath='<full name of your excel file including extension>'
xl.sheet(xlpath)

```

<ul><li>A GUI with tksheet will be opened with the contents of excel file.</li>
<li>Here is a recommending set of actions to try:</li>
<ol><li>Remove unwanted rows (F7)</li>
<li>Remove unwanted columns (F7) or combine columns (F5)</li>
  <li>Click a cell to insert (F1) or delete the cell (F3)</li></ol>
<br>

<li>All action is repeated if the same kind of selected rows/columns is found at other locations.</li>
  <ul><li>Thus, try one action at the top</li></ul>
<li>After every action, the contents will be saved to a file that is the original name with a string "_cleaned".</li>
<li>When a cell is inserted, all the cells at right will be shifted to the right</li>
<li>When a cell is deleted, all the cells at right will be shifted to the left and the cell at the last column will be empty.</li>
  <li>If the action is done by mistake, press function-key F12 to restore the last action</li></ul>
  <br>
<ul><li>To aid your step, some highlights take places</li>
  <ul><li>Some rows will be highlighted in redish, indicating that the rows are least occurance among "patterns". It does not mean you need to delete the rows, but it might be one of them you want to delete.</li>
    <li>When columns are highlighted, the columns are all empty. Thus, you can certainly delete the columns</li></ul>
    
</ul>
<br>