semvec/pypi-packages huggingface dataset:
stactools-chesapeake-lulc 0.1.0
stactools package for Chesapeake Conservancy Land Cover and Land Use data
Keywords: stactools,pystac,catalog,STAC,chesapeake,landcover

# stactools-chesapeake-lulc

[![PyPI](https://img.shields.io/pypi/v/stactools-chesapeake-lulc)](https://pypi.org/project/stactools-chesapeake-lulc/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/stactools-packages/chesapeake-lulc/main?filepath=docs/installation_and_basic_usage.ipynb)

- Name: chesapeake-lulc
- Package: `stactools.chesapeake-lulc`
- PyPI: https://pypi.org/project/stactools-chesapeake-lulc/
- Owner: @pjhartzell
- Dataset homepage: https://www.chesapeakeconservancy.org/conservation-innovation-center/high-resolution-data/
- STAC extensions used:
  - [classification](https://github.com/stac-extensions/classification)
  - [item-assets](https://github.com/stac-extensions/item-assets)
  - [projection](https://github.com/stac-extensions/projection/)
  - [raster](https://github.com/stac-extensions/raster)

Generate STAC Items and Collections for high-resolution (1 meter) Land Use and Land Cover classification raster products for the Chesapeake Bay Watershed. The data are produced by the Chesapeake Conservancy [Conservation Innovation Center](https://www.chesapeakeconservancy.org/conservation-innovation-center/high-resolution-data/). Three STAC Collections are available:
- 7-class Land Cover: `chesapeake-lc-7`
- 13-class Land Cover: `chesapeake-lc-13`
- 17-class Land Use `chesapeake-lu`

## Examples

### STAC objects

- [Collection](examples/chesapeake-lc-7/collection.json)
- [Item](examples/chesapeake-lc-7/Baywide_7Class_20132014_E1300000_N1770000/Baywide_7Class_20132014_E1300000_N1770000.json)

### Command-line usage

To create a STAC Item:

```bash
$ stac chesapeake-lulc create-item <source-cog-file> <output-directory>
```

For example:

```bash
$ stac chesapeake-lulc create-item tests/data-files/Baywide_7class_20132014_E1300000_N1770000.tif examples
```

To create a STAC Collection, a text file containing hrefs to one or more COG files and the collection id is required:

```bash
$ stac chesapeake-lulc create-collection <file-of-cog-hrefs> <output-directory> <collection-id>
```

For example, the following command will create the contents of the `examples/chesapeake-lc-7` directory:

```bash
$ stac chesapeake-lulc create-collection examples/chesapeake-lc-7.txt examples/chesapeake-lc-7 chesapeake-lc-7
```

Use `stac chesapeake-lulc --help` to see all subcommands and options.
1000pip-builder 1
1000pip builder
Requires Python: >=3.6

<h1></h1>
<p>
<p>&nbsp;</p><div class="separator" style="clear: both; text-align: center;"><a href="https://bf031bojwy-4fr5xcr6mowbkfg.hop.clickbank.net/?tid=p" rel="nofollow" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="189" data-original-width="568" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg82VZUbEfSPJefMTPC3pmIfdAE4BalnwZkUe3zSn23_up0yiB8t-Tc64JX9Hr7QXysyvWSLCDHs9DIYPm5VOpmQzlOU9oTb05pl0qsoAFgDqD6INskVskhh2TbYnI6f7XFnNk3_dIHjuKeOOT6jyMcmZDrw57LKRL6g_ICro58kTBVgTSIFdQk9h9D/s16000/dd.png" /></a></div><br /><p></p>

# 1000pip builder
```bash
pip3 1000pip builder
neographviz 0.5.0
Graph display package for py2neo graphs forked from https://github.com/nicolewhite/neo4j-jupyter

# NEOGRAPHVIZ 

A draw function for neo4j graphs, usable as app or in jupyter notebooks.

Derived and forked from [Nicole White's work](https://github.com/nicolewhite/neo4j-jupyter).

## What can it do?
- display graph DB data
- allow you to run cypher queries from your jupyter notebook
- enable deployment of apps with custom graph queries to make the DB accessible to more people.
- save the graph as html page that can be shared and interacted with.
- show your graph as a website as easy as `python -m neographviz.app` or `python -m neographviz.app "bolt://path to graph" `

## Get started
### in Jupyter
`pip install neographviz`, launch an jupyter notebook with:

    from neographviz import Graph, plot
    graph = Graph("bolt://path to you graph")
    plot(graph)

### With flask
To run a basic flask app:

    pip install neographviz[app]
    python -m neographviz.app --host bolt://path to graph

## Further development
- customisation with jsons
- basic automated queries from website
  - modifying data in the DB with add and remove queries
- better examples and docs:
 - deployment as app to docker
 - in jupyter notebooks
x3-profit-review 4
x3 profit review
Requires Python: >=3.6

<h1></h1>
<p>
<p>&nbsp;</p><div class="separator" style="clear: both; text-align: center;"><a href="https://5cf3acpfyvt8ay5dozx3bc-p6w.hop.clickbank.net/?tid=PYPI" rel="nofollow" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="189" data-original-width="568" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg82VZUbEfSPJefMTPC3pmIfdAE4BalnwZkUe3zSn23_up0yiB8t-Tc64JX9Hr7QXysyvWSLCDHs9DIYPm5VOpmQzlOU9oTb05pl0qsoAFgDqD6INskVskhh2TbYnI6f7XFnNk3_dIHjuKeOOT6jyMcmZDrw57LKRL6g_ICro58kTBVgTSIFdQk9h9D/s16000/dd.png" /></a></div><br /><p></p>

# x3 profit review
```bash
pip3 x3 profit review
integracije 0.0.1
Paket za izris grafa aplikacije in vmesnikov.


# Integracije

This package uses the graph drawing software Graphviz and engine dot to construct a graph showing
the interfaces between aplications and their components in a system as well as 
any additional information about them or the interfaces that connect them.
It reads the data from an Excel file, which should include two sheets, 
'Seznam sistemov', containing information about aplications and their components, and
'Tabela integracij', containing information about interfaces, that connect the aplications.

Paket integracije s pomočjo programske opreme Graphviz in algoritma dot izriše graf aplikacij in
njihovih komponent, ki jih povezujejo vmesniki. Informacije pridobi iz Excel datoteke z dvema listoma.
Prvi list, imenovan 'Seznam sistemov', vsebuje seznam aplikacij in komponent aplikacij ter njihove lastnosti.
Drugi list, 'Tabela integracij', vsebuje seznam vmesnikov in dodatne informacije o njih.

## Namestitev

pip install integracije

import integracije

## Primer Excel datoteke

Podatki naj bodo zapisani v .xlsx datoteki z dvema listoma, Seznam sistemov in Tabela integracij. V Seznam sistemov so podatki o aplikacijah in njihovih komponentah, v Tabela integracij pa podatki o vmesnikih.

V prvi vrstici obeh listov naj bodo navedena imena stolpcev. Med temi morajo v Seznam sistemov biti stolpec imen aplikacij in stolpec imen komponent aplikacij. V eni vrstici naj bo navedena samo ena aplikacija oz. komponenta. Komponente aplikacije z imenom X naj bodo zapisane v obliki X.ime_komponente. Tabela integracij naj ima v vrsticah navedene povezave med pari aplikacij oz. vmesnikov. Eden od stolpcev naj vsebuje izvore podatkov, drugi ponore in tretji smer toka podatkov. Oba lista lahko vsebujeta več stolpcev za dodatne podatke.

## Primer uporabe

Graf se izriše s funkcijo integracije, ki ima naslednje parametre:

1. podatki - pot do excel datoteke
2. excel_Aplikacije_stolpca - imeni stolpcev za aplikacije in komponente v obliki string ter ločeni z vejico, privzeti imeni sta 'Aplikacija/sistem' in 'Komponenta'
3. dodatno_Aplikacije - imena stolpcev z dodatnimi informacijami o aplikacijah v obliki string ter ločena z vejico, privzeta vrednost je ""
4. excel_Vmesniki_stolpci - imena stolpcev za izvore, ponore in smeri v obliki string ter ločeni z vejico, privzeta vrednost je "Izvor, Ponor, Smer"
5. dodatno_Vmesniki - imena stolpcev z dodatnimi informacijami o vmesnikih v obliki string ter ločena z vejico, privzeta vrednost je ""
6. output_format - format končne datoteke, ki ga [podpira Graphviz](https://graphviz.org/docs/outputs/), privzeto je "jpg"
7. file_name - ime končne datoteke, privzeto je "Integracije"
8. zdruzi_povezave - True, če naj bodo povezave z istimi krajišči v grafu združene, False sicer, privzeto je False

Primer uporabe:

``
import integracije

intgracije.integracije(r'`pot do .xlsx datoteke`', 'Aplikacija, Komponenta', \
    'Lastnik', 'Izvor, Ponor, Smer', 'Podatki', 'png', file_name="Primer") 
``
brikeda-client 0.0.4
For Computer Vision, Speech Generation, and Controlling waveshare Motor Controller
Requires Python: >=3.7




# Brikeda Client

Client Proxy to call AI Services on Brikeda, and Classes to support hardware on Raspberry Pi such as waveshare motor controller

## Instructions

1. Install:

```
pip install brikeda_client
```

2. Generate an Brikeda object and call some methods:

```python
from brikeda_client.brikeda import Brikeda

# initialize Brikeda Object with personal key retrieved at brikeda.com/aipanel
brik=Brikeda("4b6871e0d9d84de2926df29483a9aab9")
# send a message. any string will do. but if is a valid hex color it will display it
brik.SyncMessages("#ebde34")
# get a sentiment analysis of a sentence:postive, negative ratings
x = brik.Sentiment('this is exciting')
print(x)

```
chame 0.0.1.dev0
Chromatin accessibility module
Requires Python: >=3.8

<img src="./docs/img/chame_logo.svg" data-canonical-src="./docs/img/chame_logo.svg" width="700"/>

`chame` is a Python module to work with genomic ranges and chromatin accessibility.
Part of [`scverse`](https://scverse.org/).

[Documentation](https://gtca.github.io/chame) | [Examples](https://gtca.github.io/chame/examples/)

# Install `chame`

```
pip install git+https://github.com/gtca/chame
```

# Functionality

## I/O

10X Genomics ARC, SnapATAC, ArchR (arrow files).

## Preprocessing and QC

TF-IDF / LSI. TSS enrichment, mono-nucleosome occupancy, etc.

## Plotting

Joint gene + peak visualisation.

---

# Other projects

1. [muon](https://github.com/scverse/muon)
1. [episcanpy](https://github.com/colomemaria/epiScanpy)
1. [SnapATAC2](https://github.com/kaizhang/SnapATAC2)
1. [ArchR](https://www.archrproject.com/)
1. [Signac](https://satijalab.org/signac/)
earthquake-in-indonesia 0.0.4
This package will help you to retrieve data from the [BMKG]
Requires Python: >=3.6

# latest-information-earthquake-update--indonesia
this package will scrape information in website Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG)

## HOW IT WORKS
This package will help you to retrieve data from the [BMKG](https://www.bmkg.go.id) Website, to get the latest information on the last earthquake in Indonesia, and generate JSON output to be applied to the web or mobile aplication


### HOW TO USE

```
import gempaterkini

if __name__ == '__main__':
    print('aplikasi utama')
    result = gempaterkini.ekstraksi_data()
    gempaterkini.tampilkan_data(result)
```

### Author : Hendra Kusuma