semvec/pypi-packages huggingface dataset:
eth-hentai 0.6.1
Common Ethereum smart contracts, and related utilities, for developing automated test suites, backend integration and trading bots for EVM based blockchains.
License: MIT
Requires Python: >=3.8,<4.0
Keywords: ethereum,cryptocurrency,uniswap,erc-20,pancakeswap,sushiswap,polygon,web3,blockchain

[This package has been renamed to Web3 Ethereum Defi](https://github.com/tradingstrategy-ai/web3-ethereum-defi).
contig-tools 0.3.9
Utility package to parse multi fasta files resulting from de novo assembly
License: MIT
Requires Python: >=3.7

# Contig Tools
## Installation
```
pip3 install contig-tools
```

source code: https://gitlab.com/antunderwood/contig_tools

## Usage
```
usage: contig-tools [-h] [-v] {filter,metrics,check_metrics,co_located} ...

    A package to maniuplate and assess contigs arising from de novo assemblies


positional arguments:
  {filter,metrics,check_metrics,co_located}
                        The following commands are available. Type
                        contig_tools <COMMAND> -h for more help on a specific
                        commands
    filter              Filter contigs based on either length and/or coverage
    metrics             Print contig metrics
    check_metrics       check contig metrics
    co_located          check to see if two or more loci are found on the same
                        contig.

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         display the version number
```

## Examples
### filter contigs

```
contig-tools filter -l 500 -c 3 -f contigs.fasta
```

### print contig metrics

```
contig-tools metrics -f contig_tools/tests/test_data/contigs_for_checks.fas
contig-tools metrics -f contig_tools/tests/test_data/contigs_for_checks.fas -o json
```
### check if contigs meet conditions based on conditions enoded in a yaml file

example yaml file
```
N50 score:
  condition_type: gt
  condition_value: 10
Largest contig:
  condition_type: gt
  condition_value: 15
Total length:
  condition_type: lt_gt
  condition_value:
    - 100
    - 50
```
example command
```
contig-tools check_metrics -f contigs.fasta -y conditions.yml
```
metrics that can be checked are
 - Number of contigs
 - Number of contigs > 500bp
 - Total length
 - %GC
 - Largest contig
 - N50 score

 conditions that can be used are 
 - gt => greater than
 - lt => less than
 - lt_gt => less than and greater than

### check if a two or more loci are co-located

Make a fasta query file with the 2 or more loci you want to see if they are co-located e.g
```
>gene1
GCAGCTAGCGACTGCGAC.....
>gene2
CTACGTAGGACACGACTA....
```

There are two options

1. Search a single genome file for the co-location of loci

    ```
    contig-tools co_located -q queries.fas -f /path/to/single/genome/contigs.fas
    ```
or

2. Search a list of genomes for the co-location of loci
  Make a text file with paths to genomes e.g
  
    ```
    /path/to/single/genome1.fas
    /path/to/single/genome1.fas
    ....
    ```

    and then run the command
    ```
    contig-tools co_located -q queries.fas -l /path/to/single/genome_list_file.txt
    ```

    If you have muliple cores on the computer you are running this on you can process the search in parallel using the `-n <NUMBER PARALLEL PROCESSES>`.

    If you only want to write out genomes where the queries are co-located use the `-y` options
## code
Code can be found [here](https://gitlab.com/antunderwood/contig_tools)
jupyter-dash 0.4.2
Dash support for the Jupyter notebook interface
License: MIT
Requires Python: >=3.5

# Jupyter Dash
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/plotly/jupyter-dash/master?urlpath=tree/notebooks/getting_started.ipynb)

This library makes it easy to develop Plotly Dash apps interactively from within Jupyter environments (e.g. classic Notebook, JupyterLab, Visual Studio Code notebooks, nteract, PyCharm notebooks, etc.).

![jupterlab example](https://user-images.githubusercontent.com/15064365/82324108-150d4200-99a7-11ea-8d22-5c1bb8acaadb.gif)

See the [notebooks/getting_started.ipynb](https://github.com/plotly/jupyter-dash/blob/master/notebooks/getting_started.ipynb) for more information and example usage.

# Installation
You can install the JupyterDash Python package using pip...
```
$ pip install jupyter-dash
```
or conda
```
$ conda install -c conda-forge -c plotly jupyter-dash
```

## JupyterLab support
When used in JupyterLab, JupyterDash depends on the [`jupyterlab-dash`](https://www.npmjs.com/package/jupyterlab-dash) JupyterLab extension, which requires JupyterLab version 2.0 or above.
 
This extension is included with the Python package, but in order to activate it JupyterLab must be rebuilt. JupyterLab should automatically produce a popup dialog asking for permission to rebuild, but the rebuild can also be performed manually from the command line using:
 
 ```
$ jupyter lab build
```

To check that the extension is installed properly, call `jupyter labextension list`.

## Colab support
As of version 0.3.0, `JupyterDash` works in Colab with no additional configuration. Just install `jupyter-dash` using pip in a Colab notebook cell
```
!pip install jupyter-dash
```

# Features
To learn more about the features of JupyterDash, check out the [announcement post](https://medium.com/plotly/introducing-jupyterdash-811f1f57c02e).

# Development
To develop JupyterDash, first create and activate a virtual environment using virtualenv or conda.

Then clone the repository and change directory to the repository root:
```
$ git clone https://github.com/plotly/jupyter-dash.git
$ cd jupyter-dash
```

Then install the dependencies:
```
$ pip install -r requirements.txt -r requirements-dev.txt 
```

Then install the Python package in editable mode. Note: this will require [nodejs](https://nodejs.org/en/) to be installed.
```
$ pip install -e .
```

Then install the classic notebook extension in development mode:
```
$ jupyter nbextension install --sys-prefix --symlink --py jupyter_dash
$ jupyter nbextension enable --py jupyter_dash
```

Then install the JupyterLab extension in development mode:
```
$ jupyter labextension link extensions/jupyterlab
```

For release, build the JupyterLab extension to bundle with the Python package (see [RELEASE.md](https://github.com/plotly/jupyter-dash/blob/master/RELEASE.md) for the full process):

```
$ python setup.py build_js
```