semvec/pypi-packages huggingface dataset:
dpimport_test_2 1.0.6
DPdash importer

DPimport: A command line glob importer for DPdash
=================================================
DPimport is a command line tool for importing files into DPdash using a
simple [`glob`](https://en.wikipedia.org/wiki/Glob_(programming)) expression.

## Table of contents
1. [Installation](#installation)
2. [Configuration](#configuration)
3. [Usage](#usage)
4. [MongoDB](#mongodb)

## Installation
Just use `pip`

```bash
pip install https://github.com/AMP-SCZ/dpimport.git
```

## Configuration
DPimport requires a configuration file in YAML format, passed as a command
line argument with `-c|--config`, for establishing a MongoDB database 
connection. You will find an example configuration file in the `examples` 
directory within this repository.

## Usage
The main command line tool is `import.py`. You can use this tool to import any
DPdash-compatible CSV files or metadata files using the direct path to a file 
or a glob expression (use single quotes to avoid shell expansion)

```bash
import.py -c config.yml '/PHOENIX/GENERAL/STUDY_A/SUB_001/DATA_TYPE/processed/*.csv'
```

You may also now use the `**` recursive glob expression, for example:

```bash
import.py -c config.yml '/PHOENIX/**/*.csv'
```

or

```bash
import.py -c config.yml '/PHOENIX/GENERAL/**/processed/*.csv'
```

and so on.

<details>
<summary>Details about the pattern /**/</summary>
<br>

`directory/*/*.csv` matches only `directory/[subdirectory]/[filename].csv`. With a [recursive glob pattern](https://docs.python.org/3/library/glob.html#glob.glob), `directory/**/*.csv` will additionally match:

* `directory/[filename].csv` (no subdirectory)
* `directory/[subdirectory1]/[subdirectory2]/[filename].csv` (sub-subdirectory)

and so on, for as many levels deep as exist in the directory tree.

</details>



## MongoDB

This tool requires MongoDB to be running and accessible with the credentials you
supply in the `config.yml` file. For tips on MongoDB as it is used in DPdash and DPimport,
see [the DPdash wiki](https://github.com/PREDICT-DPACC/dpdash/wiki/MongoDB-Tips).
dpimport-test-2 1.0.5
DPdash importer

DPimport: A command line glob importer for DPdash
=================================================
DPimport is a command line tool for importing files into DPdash using a
simple [`glob`](https://en.wikipedia.org/wiki/Glob_(programming)) expression.

## Table of contents
1. [Installation](#installation)
2. [Configuration](#configuration)
3. [Usage](#usage)
4. [MongoDB](#mongodb)

## Installation
Just use `pip`

```bash
pip install https://github.com/AMP-SCZ/dpimport.git
```

## Configuration
DPimport requires a configuration file in YAML format, passed as a command
line argument with `-c|--config`, for establishing a MongoDB database 
connection. You will find an example configuration file in the `examples` 
directory within this repository.

## Usage
The main command line tool is `import.py`. You can use this tool to import any
DPdash-compatible CSV files or metadata files using the direct path to a file 
or a glob expression (use single quotes to avoid shell expansion)

```bash
import.py -c config.yml '/PHOENIX/GENERAL/STUDY_A/SUB_001/DATA_TYPE/processed/*.csv'
```

You may also now use the `**` recursive glob expression, for example:

```bash
import.py -c config.yml '/PHOENIX/**/*.csv'
```

or

```bash
import.py -c config.yml '/PHOENIX/GENERAL/**/processed/*.csv'
```

and so on.

<details>
<summary>Details about the pattern /**/</summary>
<br>

`directory/*/*.csv` matches only `directory/[subdirectory]/[filename].csv`. With a [recursive glob pattern](https://docs.python.org/3/library/glob.html#glob.glob), `directory/**/*.csv` will additionally match:

* `directory/[filename].csv` (no subdirectory)
* `directory/[subdirectory1]/[subdirectory2]/[filename].csv` (sub-subdirectory)

and so on, for as many levels deep as exist in the directory tree.

</details>



## MongoDB

This tool requires MongoDB to be running and accessible with the credentials you
supply in the `config.yml` file. For tips on MongoDB as it is used in DPdash and DPimport,
see [the DPdash wiki](https://github.com/PREDICT-DPACC/dpdash/wiki/MongoDB-Tips).
cbs-hist-downloader 1.0.2
A python program for downloading images from CBS historisch.
Requires Python: >=3.6

# cbs_hist_downloader

A Python-based tool using Selenium to download books to your harddrive rather than accessing the pictures through the API at historisch.cbs.nl

## Dependencies

Selenium (`pip install selenium`), time, os, webdriver-manager (`pip install webdriver-manager`)

## Example how to use:

In the console:

```
pip install cbs_hist_downloader
```

After installation, in a python environment, you start off with the first URL of the book/volume you want to download:

```{python}
import cbs_hist_downloader as chd

url = "https://historisch.cbs.nl/detail.php?nav_id=2-1&index=10&id=395291474"

chd.scrape_book(url)
```

The files will be downloaded to your Downloads folder. 


## Suggestions / Comments

a dot h dot machielsen at uu dot nl
transport-cba 0.1.2
A Python package for cost-benefit analysis of infrastructure projects
Requires Python: >=3
Keywords: cost benefit analysis

# transport-cba

A Python module for cost-benefit analysis of infrastructure projects.

Provides a consistent way to evaluate economic efficiency
of road projects with well-defined inputs and parameters.

Main benefits compared to traiditional Excel-based approach:
- several orders of magnitude faster and cheaper
- wider options for analysis of alternative scenarios
- significantly lower margin for error


## Installation
From pip:
```
pip install transport-cba
```
Or directly from git:
```
pip install git+https://github.com/transport-cba/transport-cba.git
```

## Inputs
Load project inputs as an Excel file with following sheet names:
  `road_params, capex, intensities_0, intensities_1, velocities_0, velocities_1`

Meaning of required inputs:
* capital expenditures (CAPEX) with pre-defined items
* parameters of road sections (length, width, number of lanes etc)
* vehicle intensities in variant 0 and 1 (without and with the project) by road segment
* vehicle velocities in variant 0 and 1 by segment

For illustration, please download the sample input (see below).


## Outputs
* Dataframe of costs and benefits
* Economic indicators:
  - economic net present value (ENPV)
  - economic internal rate of return (ERR)
  - benefit to cost ratio (BCR)
  - dataframes with breakdown of relevant benefits by years


## Example
NB: Values might differ slightly.

```python
>>> from transport_cba import RoadCBA
>>> from transport_cba.sample_projects import load_sample_bypass

>>> bypass = load_sample_bypass()

>>> cba = RoadCBA(2020, "svk")
>>> cba.read_project_inputs(
...     bypass["road_params"],
...     bypass["capex"],
...     bypass["intensities_0"],
...     bypass["intensities_1"],
...     bypass["velocities_0"],
...     bypass["velocities_1"]
... )
>>> cba.economic_analysis()
>>> cba.economic_indicators
```
|    | Quantity   | Unit   |   Value |
|---:|:-----------|:-------|--------:|
|  0 | ENPV       | M EUR  |   3.336 |
|  1 | ERR        | %      |   5.62  |
|  2 | BCR        |        |   1.076 |
```