semvec/pypi-packages huggingface dataset:
taxfinder 0.0.1
Helper function to work with NCBI taxonomy ids
Requires Python: >=3.6

TaxFinder
=========

The TaxFinder module is a library to help with NCBI taxonomy ids.

Install it using `pip`, preferable into a virtual environment:

```sh
$ pip install taxfinder ### TODO: This is not working for now!
### TODO: Use for now:
$ cd path/to/taxfinder
$ pip install -e .
```

To do this, TaxFinder needs to download and create a databse with taxonomy information. This database needs in the order of 300 MB disc space. To create the database, run

```sh
$ taxfinder_update
```

By default, TaxFinder tries to create the database in the installation directory. If you experience problems or you want to save the database to another path, set the environment variable `TFPATH` to the desired path. This path must be readable and writable for TaxFinder.

To use TaxFinder, you need to import it and instanciate the main class. This will open the database and also cache your queries so repeated queries are answered faster.

```python
from taxfinder import TaxFinder

TF = TaxFinder()

print(TF.getLineage(9606))
```

In an interactive session, you can also get help on the TaxFinder methods:

```python
>>> from taxfinder import TaxFinder
>>> help(TaxFinder)
```
liveramp_clean_room 0.0.3
This is a python client that provides high level functions for interacting with liveramp's clean room.
Requires Python: >=3.8,<4.0

# Liveramp clean room
This library provides high level functions for interacting with liveramp's clean room API. Whilst users can directly interact with the API, we highly recommend the use of this client as it provides the following benefits:
- Automatic fetching and efficient caching of access token
- Automatic fetching of query status with exponential backoff
- Provides a simple interface for fetching query result as a pandas dataframe
- Provides user friendly interfaces for interacting with assets and associated permissions
- Provides clear and intuitive error messages


## Pre-Requisites


### Credentials File


Use of the client requires an account configured with access to an organization within Data Hub. LiveRamp customers must use a service account for that purpose. A service account credential, in the form of a JSON file, can be generated by a LiveRamp employee and shared securely.


### Installation


The Client is hosted on https://pypi.org/project/liveramp-clean-room/ and thus can be installed via


```bash
pip install liveramp_clean_room
```


Once installed the client be instantiated and added to your code as the example below shows:


```python
from liveramp_clean_room import datahub


## Initialize a client
org_id = "00XXX0XXX0XXX00X0XXX000XXX"
credentials_file = "Path to service account file"
client = datahub.Client(org_id, credentials_file)
```
Where `org_id` is the id of an organization within DataHub and `credentials_file` is the JSON file location of your service account


## Running Queries


To run a query utilize the run_query function. DataHub supports the following query types:


- Data Manipulation Language (DML)


    `SELECT query`


- Data Definition Language (DDL)


    `CREATE OR REPLACE FUNCTION/DROP FUNCTION)`, used to create or drop UDFs, a createdAssetID will be returned in the response. 


Example: Run a query and get results
---
```python
from liveramp_clean_room import datahub


org_id = "00XXX0XXX0XXX00X0XXX000XXX"
credentials_file = "Path to service account file"
client = datahub.Client(org_id, credentials_file)
query_id = client.run_query("select * from schema.mytable")


## Fetch result as a pandas dataframe
dataframe = client.get_result(query_id)
```


> Note that the client returns a Pandas Dataframe
seEvo1D 1.7.5
Software for simulating slightly effect mutations impact on population evolution in tau leap version.
Requires Python: >=3.7
Keywords: clonal evolution,microbial,numerical modelling

# Installation

seEvo1D is python based lib available at pypi
```
python -m pip install seEvo1D
```
dependecies will be installed with program

# Usage

To run program simply type in command line
```
python -m seEvo1D
```
basicly seEvo is standalone program which provides possibility to simulate slighlty effect evolution in one dimension - slightly advantegous, slightly deleterious

# Instructions

Program contains 4 main views and main status UI

![Screenshot 2023-01-21 221838](https://user-images.githubusercontent.com/110567171/213887717-d77b2c92-37ec-46e0-974a-23aec88f0338.jpg)
![Screenshot 2023-01-21 221912](https://user-images.githubusercontent.com/110567171/213887739-cb461642-3300-4692-b326-96494b5223cc.jpg)

Output buttons provides possibility to draw images from saved files. Each file should have extension '.npz' as default from program. User can create multiple figures from multiple files. Each picture will be save to same directory from which file is loaded, in folder 'Figures'. 

population growth plot demands selection of multiple files to track population size.
combined mutation wave plot provides possibility to draw both analytic and simulated mutation wave on one plot. multiple files can be selected to draw on one figure.

![Screenshot 2023-01-21 221925](https://user-images.githubusercontent.com/110567171/213887744-cb66086b-56e8-4a57-b9ef-68d498ca4458.jpg)
![Screenshot 2023-01-21 221939](https://user-images.githubusercontent.com/110567171/213887745-0524bb73-77cf-4366-9140-f0191e2c28af.jpg)
![Screenshot 2023-01-21 221956](https://user-images.githubusercontent.com/110567171/213887746-efbc3573-9bd3-404c-a656-400e2e9b2c8d.jpg)

# License
  
GNU GENERAL PUBLIC LICENSE  Version 3, 29 June 2007

 Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
 Everyone is permitted to copy and distribute verbatim copies
 of this license document, but changing it is not allowed.
 
 ## Disclaimer
 
 seEvo - slighltly effect evolution simulator basing on Gillespie algorithm.
    Copyright (C) 2022 by Jarosław Gil

  This program is free software: you can redistribute it and/or modify
  it under the terms of the GNU General Public License as published by
  the Free Software Foundation, either version 3 of the License, or
  (at your option) any later version.

  This program is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  GNU General Public License for more details.

  You should have received a copy of the GNU General Public License
  along with this program.  If not, see <https://www.gnu.org/licenses/>.

# Author

Jarosław Gil, Silesian Univeristy of Technology, Department of Computer Graphics, Vision and Digital Systems.