semvec/pypi-packages huggingface dataset:
wct 0.0.4
Search and Moderation Wizard for the Computer Tree.
Requires Python: >=3.10

# smwct
### Presentation
*Smwct*, for "*Search and Moderation Wizard for the Computer Tree*",
is, as its name indicates, a program whose mission is to help man in the search and moderation of his computer tree. More
exactly, *Smwct* allows two things: to search from one of the pre-suggested places a sequence of characters in all the folders, sub-folders and 
from the initial directory, chosen by the user, **or**, search and delete after confirmation all the folders, subfolders and
from the initial directory (always chosen by the user). It is a software coded only in Python and only dedicated to
Linux users.
### Cause
*Smwct* was designed to make it easier to find an item in a pre-suggested directory such as `/` or `/home/username/`, especially to
to get rid of all the files/folders left after uninstalling a program. It is also intended to replace `grep` which is a tool that I find
tool in my opinion.
## Technical
### Setting up Smwct on Linux
Before doing the following, make sure you have Python and Git installed correctly.

Once you have Python on your Linux distribution, run the following command at the "root" (`/home/username/`) to avoid 
complications when using *smwct*:
```
git clone https://github.com/b4-b4/smwct.git
```
The installation of the software is finished.
### Search
Theoretically, if you have *smwct* installed at the root of your tree (`/home/username/`), the procedure should be as follows:
```
cd
python smwct/run.py -s --starting your_character_string
```
By entering `python smwct/run.py` you tell the python interpreter to run the `run.py` program which is in the `smwct/` directory. Then, 
the first `-s` flag means that you want to run a search. The second flag `--starting` **must** be replaced by either of the following
following flags:
- `--root`: informs that you want to search at the absolute root of your computer, namely `/`.
- `--session`: informs that you want to search at the root of your "session", i.e. `/home/username/`.
- `--anywhere`: searches the absolute root and the root of your session (`--root` + `--session`). This command can take a long time, really.

Then `your_character_string` **must** be replaced by the element you want to search for in the second flag (`--session`, `--root` or `--anywhere`). Note that `your_character_string` is not the actual item being searched for, it is the item being searched for in the various folders, subfolders and files in the second flag. For example, this command line
```
python smwct/run.py -s --root a
```
might return
```
/etc/gra.o
/var/
/var/test/allocation/
```
because `etc/gra.o` contains an `a` in `gra.o`, `/var/` because `var` contains `a`, etc.
OSTIR50 1.0.6
Open Source Transcription Initiation Rates
Requires Python: >=3.8

# OSTIR (Open Source Translation Initiation Rates)
[![Status](https://github.com/barricklab/ostir/actions/workflows/package_and_test.yml/badge.svg)](https://github.com/barricklab/ostir/actions/workflows/package_and_test.yml) [![status](https://joss.theoj.org/papers/43d02b32408a161e608b886f63e753c1/status.svg)](https://joss.theoj.org/papers/43d02b32408a161e608b886f63e753c1)


`OSTIR` is a
Python package for predicting the rates at which ribosomes will bind to and initiate
translation from different start codons in bacterial mRNAs. It uses the ViennaRNA Package to perform 
the necessary free energy calculations. The code builds on the last open source version of the
[RBS calculator](https://github.com/hsalis/Ribosome-Binding-Site-Calculator-v1.0).

`OSTIR` includes several improvements in usability. It supports multi-FASTA
input with command line parameters or CSV input that can define
parameters on a per-sequence basis. Additionally, `OSTIR` supports multi-threaded
execution, accelerating the analysis of very large sequences.

### [Please see the OSTIR Wiki for full documentation](https://github.com/barricklab/ostir/wiki)

# Quickstart

## Installation
[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/ostir/README.html)

`OSTIR` is a Python module and associated command line script. We recommend installing `OSTIR` using [Bioconda](https://bioconda.github.io/) on Linux or macOS. This will automatically install `OSTIR` and all of its dependencies, including [ViennaRNA](https://www.tbi.univie.ac.at/RNA/) and the required Python modules.

From Bioconda (recommended; Linux, macOS):
- Run `conda install -c bioconda ostir`

From Pip (for experts; Linux, macOS, Windows):
- Download and install ViennaRNA, following the instructions [here](https://www.tbi.univie.ac.at/RNA/).
- Run `pip install ostir`

For information on installing for development see the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Installation).

## Command Line Usage

Print OSTIR help:
```
ostir -h
```

Run OSTIR on a sequence provided at the command line and print output to the console:
```
ostir -i TTCTAGATGAGAATAAGGTTATGGCGAGCTCTGAAGACGTTATCAAAGAGTTCATGCGTTTCAAAGTTCGTATGGAAGGT
```

Run OSTIR on all sequences provided in a FASTA file and print output to a CSV file:
```
ostir -i input.fasta -o output.csv
```

More options and examples are described in the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Command-Line-Usage).

## Python Module Usage

Run OSTIR on a sequence inside of a Python script:

```python3
from ostir.ostir import run_ostir

seq = "ACUUCUAAUUUAUUCUAUUUAUUCGCGGAUAUGCAUAGGAGUGCUUCGAUGUCAU"
results = run_ostir(seq, name="my_sequence", threads=8)
print(results)
```

More options and examples are described in the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Python-Module-Usage).
profane 0.2.4
A library for creating complex experimental pipelines
Requires Python: >=3.6

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black) 
[![Worfklow](https://github.com/andrewyates/profane/workflows/pytest/badge.svg)](https://github.com/andrewyates/profane/actions)
[![PyPI version fury.io](https://badge.fury.io/py/profane.svg)](https://pypi.python.org/pypi/profane/)


# Overview
*Profane* is a library for creating complex experimental pipelines. Profane pipelines are based on two key ideas:
1. An experiment is a *function of its configuration*. In other words, an experiment should be deterministic given a set of experimental parameters (random seed, specific algorithms to run, etc).
2. An experiment is described as a *DAG* representing modules' (nodes') dependencies in which the *state of a node is independent of its parent's state*. That is, a *node's operation is a function of its configuration and the configurations of its children*. This means that a node may not modify the configuration (or state) of its children (or descendants).

These allow for the construction of a flexible pipeline with automatic caching. Each node's configuration can be modified to change experimental parameters, and a node's output can be safely cached in a path derived from its configuration and the configurations of its children. These nodes are called modules.

This library is heavily inspired by the excellent [sacred](https://sacred.readthedocs.io/en/stable/) library. Among other differences, profane imposes a specific structure on the pipeline and leverages this to allow profane modules to be dynamically configured (which would be similar to dynamic sacred ingredients). Profane was developed based on experiences using sacred with a heavily modified pipeline initialization step.

## Example
The `example/` directory contains a module graph similar to that used in Capreolus. Run it with the `run.sh` script.
OSTIR-50 1.0.6
Open Source Transcription Initiation Rates
Requires Python: >=3.8

# OSTIR (Open Source Translation Initiation Rates)
[![Status](https://github.com/barricklab/ostir/actions/workflows/package_and_test.yml/badge.svg)](https://github.com/barricklab/ostir/actions/workflows/package_and_test.yml) [![status](https://joss.theoj.org/papers/43d02b32408a161e608b886f63e753c1/status.svg)](https://joss.theoj.org/papers/43d02b32408a161e608b886f63e753c1)


`OSTIR` is a
Python package for predicting the rates at which ribosomes will bind to and initiate
translation from different start codons in bacterial mRNAs. It uses the ViennaRNA Package to perform 
the necessary free energy calculations. The code builds on the last open source version of the
[RBS calculator](https://github.com/hsalis/Ribosome-Binding-Site-Calculator-v1.0).

`OSTIR` includes several improvements in usability. It supports multi-FASTA
input with command line parameters or CSV input that can define
parameters on a per-sequence basis. Additionally, `OSTIR` supports multi-threaded
execution, accelerating the analysis of very large sequences.

### [Please see the OSTIR Wiki for full documentation](https://github.com/barricklab/ostir/wiki)

# Quickstart

## Installation
[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/ostir/README.html)

`OSTIR` is a Python module and associated command line script. We recommend installing `OSTIR` using [Bioconda](https://bioconda.github.io/) on Linux or macOS. This will automatically install `OSTIR` and all of its dependencies, including [ViennaRNA](https://www.tbi.univie.ac.at/RNA/) and the required Python modules.

From Bioconda (recommended; Linux, macOS):
- Run `conda install -c bioconda ostir`

From Pip (for experts; Linux, macOS, Windows):
- Download and install ViennaRNA, following the instructions [here](https://www.tbi.univie.ac.at/RNA/).
- Run `pip install ostir`

For information on installing for development see the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Installation).

## Command Line Usage

Print OSTIR help:
```
ostir -h
```

Run OSTIR on a sequence provided at the command line and print output to the console:
```
ostir -i TTCTAGATGAGAATAAGGTTATGGCGAGCTCTGAAGACGTTATCAAAGAGTTCATGCGTTTCAAAGTTCGTATGGAAGGT
```

Run OSTIR on all sequences provided in a FASTA file and print output to a CSV file:
```
ostir -i input.fasta -o output.csv
```

More options and examples are described in the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Command-Line-Usage).

## Python Module Usage

Run OSTIR on a sequence inside of a Python script:

```python3
from ostir.ostir import run_ostir

seq = "ACUUCUAAUUUAUUCUAUUUAUUCGCGGAUAUGCAUAGGAGUGCUUCGAUGUCAU"
results = run_ostir(seq, name="my_sequence", threads=8)
print(results)
```

More options and examples are described in the [Wiki Documentation](https://github.com/barricklab/ostir/wiki/Python-Module-Usage).