semvec/pypi-packages huggingface dataset:
pyotm 0.0.3
Python connector for OTM
Requires Python: >=3.7

OTM is a platform for simulating vehicular traffic scenarios. It offers multiple models that can be arbitrarily combined in a single simulation. You can use one of the native OTM models (CTM, 2Q, Newell), or you can create a plugin for your own model. You can similarly implement new controllers as plugins.

Learn more [here.](https://ggomes.github.io/otm-sim/)

# Python API

Most users will interact with OTM through its Python API, which can be installed with pip:

```
pip install pyotm
```
The `pyotm` package contains a single class called `OTMWrapper`. Below we see how to use `OTMWrapper` to run a step-by-step simulation.

```python 
from pyotm.OTMWrapper import OTMWrapper

# in case there is a lingering open gateway
if "otm" in locals():
	del otm
	
# load the configuration file
otm = OTMWrapper("intersection.xml")

# initialize (prepare/rewind the simulation)
otm.initialize(start_time=0.0)

# run step-by-step using the 'advance' method
time = 0.0  # in seconds
advance_time = 10.0
while(time<3600.0 ):
	otm.advance(advance_time)   # seconds, should be a multiple of sim_dt
	print(otm.get_current_time())
	time += advance_time;

# deleting the wrapper to shut down the gateway
del otm
```

Use `run` to run an entire simulation. 
``` python 
from pyotm.OTMWrapper import OTMWrapper
import numpy as np

if "otm" in locals():
	del otm

otm = OTMWrapper("intersection.xml")
otm.run(start_time=0,duration=2500,output_dt=10)
Y = otm.get_state_trajectory()
print(Y.keys())
del otm
```

Here `get_state_trajectory` has been used to retrieve the state trajectory. This is a dictionary containing various state profiles. 

A comprehensive API is available via the `otm` attribute of `OTMWrapper`. This API provides access to most of the internal state of OTM and should be used with care. The javadoc can be found [here](https://ggomes.github.io/otm-sim/apidocs/index.html).
report-monaco-road 0.0.9
Package count unique chars in file or string
Requires Python: >=3.8

# Report of Monaco 2018 Racing
This module read data from 3 files, order racers by time and print report that shows the top 15 racers and the rest after underline.

	
#### abbreviations.txt ->
````
SVF_Sebastian Vettel_FERRARI
LHM_Lewis Hamilton_MERCEDES
KRF_Kimi Räikkönen_FERRARI
````
#### end.log ->
````
SVF2018-05-24_12:04:03.332
LHM2018-05-24_12:11:32.585
KRF2018-05-24_12:04:13.889
````

#### start.log -> 
````
SVF2018-05-24_12:02:58.917
LHM2018-05-24_12:18:20.125
KRF2018-05-24_12:03:01.250
````
## Examples:
#### Shows list of drivers and by asc:
```bash
python3.8 -m report_monaco --files road_data/ --asc
```
#### Return:
```
1. Sebastian Vettel  | FERRARI  | 0:01:04.415000
2. Valtteri Bottas  | MERCEDES  | 0:01:12.434000
3. Stoffel Vandoorne  | MCLAREN RENAULT  | 0:01:12.463000
.......
```
#### Shows list of drivers order by desc:
```bash
python3.8 -m report_monaco --files road_data/ --desc
```
#### Return:
```
1. Kevin Magnussen  | HAAS FERRARI  | 0:01:13.393000
2. Lance Stroll  | WILLIAMS MERCEDES  | 0:01:13.323000
3. Marcus Ericsson  | SAUBER FERRARI  | 0:01:13.265000
.......
```

#### Shows statistic about driver:
```bash
python3.8 -m report_monaco --files road_data/ --driver "Kevin Magnussen"
```
#### Return:
```
1. Kevin Magnussen  | HAAS FERRARI  | 0:01:13.393000
```
uz-en-dictionary 0.0.4
Simple Uzbek-English Dictionary

# UZ-EN Dictionary

UZ-EN Dictionary is a Python library for translate words (uz-en; en-uz).

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install uz_en_dictionary.

```bash
pip install uz-en-dictionary
```

## Usage

```python
from uz_en_dictionary import Translator
d = Translator(from_lang='en', to='uz') # EN-UZ
print(d.translate("believe"))
# vt, vi 1) ishonmoq; 2) imon keltirmoq; 3) o`ylamoq
```
```python
from uz_en_dictionary import Translator
d = Translator(from_lang='uz', to='en') # UZ-EN
print(d.translate("maqsad"))
# (Arabic) intent, purpose, aim. ~ida for the purpose of, in order to.
```
```python
from uz_en_dictionary import Dictionary
d = Dictionary(lang='en')
print(d.search("gramm")) # Search mode
# {'grammar': ' n [U] grammatika', 'grammatical': ' adj. grammatikaga oid','gramme': ' n [C] misqol, gram'}
```
```python
from uz_en_dictionary import Dictionary
d = Dictionary(lang='uz')
print(d.getwords_by_letter("q")) # Get words from letter
# <Words (q)>
```
## Author

Firdavs Matyoqubov (11.20.2021)

## License

[MIT](https://choosealicense.com/licenses/mit/)