semvec/pypi-packages huggingface dataset:
lenuxtranslate 1.25.3
Argos Translate Tabanlı Türkçe Destekli Çeviri Kütüphanesi
Requires Python: >=3.7

# 🌍 lenuxtranslate - Otomatik Çeviri Kütüphanesi

**lenuxtranslate**, Argos Translate tabanlı bir Python kütüphanesidir.
Tüm dilleri destekler, çevirileri **konsolda görüntüler** ve **dosyaya kaydeder**.

## 🚀 Özellikler

- **Tüm dilleri destekler** (Argos Translate tüm dil paketlerini indirir).
- **Sürekli çeviri yapabilir** (Çeviri sonrası tekrar çeviri isteyip istemediğinizi sorar).
- **Çeviri geçmişini dosyaya kaydeder** (`translated_text.txt`).
- **Renkli Konsol Çıktısı** (Bilgilendirme, uyarı ve hata mesajları).

## 📦 Kurulum

Python 3.7+ kullanmanız önerilir.

### 1️⃣ Ortamınızı oluşturun ve etkinleştirin:

```bash
python -m venv myenv
source myenv/bin/activate  # Mac/Linux
myenv\Scripts\activate     # Windows
```
simplemseed-obspy-plugin 0.4.4
obspy plugin for miniseed3 in pure python
Requires Python: >=3.9
Keywords: fdsn, miniseed3, obspy, seed, sourceid, steim1, steim2

# simplemseed_obspy_plugin
Obspy plugin for reading miniseed3 files.

See https://pypi.org/project/simplemseed/ for details.


## Installation

Install ObsPy, then

```bash
pip install simplemseed_obspy_plugin
```


## Usage

It will hook into ObsPy's normal I/O handling and you just use it as you would
use any format:

```
>>> import obspy
>>> st = obspy.read("src/simplemseed_obspy_plugin/tests/data/bird_jsc.ms3")
>>> for t in st:
...   print(t)
...
CO.BIRD.00.HHE | 2024-02-06T11:30:00.009998Z - 2024-02-06T11:30:29.999998Z | 100.0 Hz, 3000 samples
CO.BIRD.00.HHN | 2024-02-06T11:30:00.009998Z - 2024-02-06T11:30:29.999998Z | 100.0 Hz, 3000 samples
CO.BIRD.00.HHZ | 2024-02-06T11:30:00.009998Z - 2024-02-06T11:30:29.999998Z | 100.0 Hz, 3000 samples
CO.JSC.00.HHE | 2024-02-06T11:30:00.008392Z - 2024-02-06T11:30:29.998392Z | 100.0 Hz, 3000 samples
CO.JSC.00.HHN | 2024-02-06T11:30:00.008392Z - 2024-02-06T11:30:29.998392Z | 100.0 Hz, 3000 samples
CO.JSC.00.HHZ | 2024-02-06T11:30:00.008392Z - 2024-02-06T11:30:29.998392Z | 100.0 Hz, 3000 samples
>>> st.write("out.ms3", format="mseed3")
```
rebis 0.1.0
Rebis client for Python
Requires Python: >=3.6

### Rebis python client
An example of how to use Rebis client in python.
```python
from rebis import RebisClient, RebisQuery
client = RebisClient("localhost", 6666)
rebis = RebisQuery(client)
rebis.set("key", "value")
rebis.get("key")
rebis.delete("key")
rebis.reset()
```
ipld-car 0.0.1
Content Addressable aRchive format reader and writer.
Requires Python: >=3.9

# py-ipld-car

Content Addressable aRchive format reader and writer.

## Install

```sh
pip install ipld_car
```

## Usage

```py
import ipld_car
from multiformats import multihash, CID

data = bytes([1, 2, 3])
digest = multihash.digest(data, "sha2-256")
cid = CID("base32", 1, "raw", digest)
block = (cid, data)

# encode a CAR file
car = ipld_car.encode([block[0]], [block])
print("CAR: ")
print("  " + str(car.tobytes()))

# decode a CAR file
roots, blocks = ipld_car.decode(car)

print("===")
print("Roots:")
for r in roots:
    print("  " + r.encode("base32"))

print("Blocks:")
for b in blocks:
    print("  CID: " + b[0].encode("base32"))
    print("  Bytes: " + str(b[1].tobytes()))

# Output:
#
# CAR: 
#   b":\xa2eroots\x81\xd8*X%\x00\x01U\x12 \x03\x90X\xc6\xf2\xc0\xcbI,S;\nM\x14\xefw\xcc\x0fx\xab\xcc\xce\xd5(}\x84\xa1\xa2\x01\x1c\xfb\x81gversion\x01'\x01U\x12 \x03\x90X\xc6\xf2\xc0\xcbI,S;\nM\x14\xefw\xcc\x0fx\xab\xcc\xce\xd5(}\x84\xa1\xa2\x01\x1c\xfb\x81\x01\x02\x03"
# ===
# Roots:
#   bafkreiadsbmmn4waznesyuz3bjgrj33xzqhxrk6mz3ksq7meugrachh3qe
# Blocks:
#   CID: bafkreiadsbmmn4waznesyuz3bjgrj33xzqhxrk6mz3ksq7meugrachh3qe
#   Bytes: b'\x01\x02\x03'
```

## Contributing

All welcome! storacha.network is open-source.

## License

Dual-licensed under [Apache-2.0 OR MIT](LICENSE.md)
kalpaa 1.2.0
Groups up and runs full run.
Requires Python: <3.10,>=3.8.1

# kalpaa

Need to have a dots.json, indexes.json, the other jsons get generated.


# sources of truth
dots.json
indexes.json

costs
10.0 5.0 1.0 0.5 0.1 0.06
02-run_gen.sh



# Ideas
- can calculate some calibration curves for successes? and maybe some brier scores? but probably not 

# Variables to change
- count: 1 or 10, also use that for ddog
- Frequency range?
	- We may require some additional work to get automatic merging of multiple time series a la Connors paper
- Measurement type?
	- Let's do Ex field for now and maybe try potential later in a sd4 run

# Procedure
- `run.sh`
- `clean.sh` to clean things

# style

Note we prefer tabs to spaces, but our autoformatter can handle that for us.
crimson-copilot-init-client 0.1.0
crimson-copilot-init-client.
Requires Python: >=3.9

**Template README.md**\
This file is from the [template repository](https://github.com/crimson206/template/blob/main/README.md).
Rewrite it for your own package.

## Python Package Setup

### Setup Base

To install required pip modules for `generate_toml.py`, run
``` bash
source scripts/setup_base.sh
```

### User Setup

- go to `generate_toml.py` file, and complete the setup in the `User Setup` session.

```python
options = Options(
    # Will you use the discussion session in your repo?
    discussion=False
)

# Define the general information of your package
kwargs = Kwargs(
    name_space="None",
    module_name="None",
    description="None",
)
```

If you wrote all the information, run
```
python generate_toml.py
```

#### Template

If you want to understand the generation process, check the `template` variable in `generate_toml.py`.

### Setup Env

#### Prerequisite

Finish [User Setup](#user-setup) first.
Of course, conda command must be available.

#### Setup Env

Run
``` bash
source scripts/setup_env.sh
```

steps
- create an conda environment named as your $MODULE_NAME
- activate the environment.
- install requirements.txt

#### Generate Private Env
Generate a private repository in this repo.
I recommend you to write all the unstructured codes in this repo.

``` bash
source scripts/generate_dev_repo.sh
```

It will ask you the name of your repo, and then, generate a repo named f'{your_repo_name}-dev'.

**Usage Tip**

If you wrote your codes in a wrong branch,
- backup the files to the dev repo
- remove changes in your main(not main branch) repo
- move to your correct branch
- place back the backup codes


## Workflows

I currently setup test and release workflows.

**Test**

If you make a PR with the patterns [ main, develop, 'release/*', 'feature/*' ],

It will perform your unittest in ["3.9", "3.10", "3.11"]

**Release**

required secret : PYPI_API_TOKEN

I usually make PRs only when I start release branches.
release workflow is not conducted automatically. If you think your branch is ready to be published, 

- go to https://github.com/{github_id}/{repo_name}/actions/workflows/release.yaml
- find the button, 'Run workflow'
- select the branch to publish. In my case, release/x.x.x
pruna-launch-party 1.0.0
A fun package celebrating Pruna's open-source launch!
Requires Python: >=3.7

# 🎉 Pruna Launch Party

Celebrate Pruna's open-source launch with this fun package!

## Installation

```bash
pip install pruna-launch-party --extra-index-url "<Event Location>"
```

## What's this?

Pruna is now open-source, and we're throwing a party to celebrate our most public commit yet! This package brings the party to your terminal.

When you install this package, you'll see:
- Launch confirmation
- AI jokes (compressed, of course)
- High-energy vibes
- And more surprises!

## Features

- 🚀 Simulated launch sequence
- 🤖 AI-powered party vibes
- 🎵 Terminal celebrations
- 🎨 Colorful output

## Usage

After installation, just run:

```bash
launch_open_source
```

And watch the celebration unfold!

## Note

We've spent months pruning, quantizing, distilling... Now it's time to decompress (for once, that means us! Don't worry, we're still compressing models.)

Come for the `pip install pruna`, stay for the `pip install fun`. 🎉