semvec/pypi-packages huggingface dataset:
causal-inference-population-dynamics 1.0.2
Library to conduct experiments in population dynamics.
License: MIT
Requires Python: >=3.7



# Causal-inference-population-dynamics

Causal-inference-population-dynamics is a library to simulate and infer population dynamics models.

The currently imlemented population dynamics models are
+ Lotka-Volterra model

## Running the code

You can run the simulator directly from terminal by running

```(bash)
python causal/base/lotka_volterra.py
```

The simulation statistics will be saved in the `repo/results` directory.
seq-uuid 1.0.1
A library to generate sequential uuid based on RFC4122
License: MIT
Requires Python: >=3.6, <4
Keywords: uuid,uuidv6,sequential uuid

# seq-uuid

A Python library to generate UUID version 4 and 5, based on [RFC4122](https://datatracker.ietf.org/doc/html/rfc4122)
and version 6 based
on [RFC4122 2021 draft edition](https://datatracker.ietf.org/doc/html/draft-peabody-dispatch-new-uuid-format).

# Examples

```python
import seq_uuid

identifier = seq_uuid.uuid6()

print(identifier)
```

```python
import seq_uuid

id1 = seq_uuid.uuid6()
id2 = seq_uuid.uuid6()

print(id1)
print(id2)

assert (id1 < id2)
assert (id1.version == 6)
```
ddbapi 0.1.2
Library for querying DDB infrastructure
License: MIT
Requires Python: >=3.8.5

# Wrapper for the DDB API

- Query the DDB API for Newspapers
- returns a Pandas Dataframe Object

Usage:

```
from ddbapi import zp_issues, zp_pages, list_column, filter

df = zp_issues(publication_date='[1600-09-01T12:00:00Z TO 1699-12-31T12:00:00Z]')
print(df)
```

## `zp_issues`

- Returns a DataFrame containing Data on Newspaper-Issues.
- Use any combination of these keyword arguments:
  - `language`: Use ISO Codes, currently `ger`, `eng`, `fre`, `spa`, `ita`
  - `place_of_distribution`: Search inside "Verbreitungsort", use a list for multiple search-words
  - `publication_date`: Get newspapers by publication date. Use the following format: `1900-12-31T12:00:00Z` for a specific date, use square brackets and `TO` between two dates to get a daterange like so: `publication_date='[1935-09-01T12:00:00Z TO 1935-09-22T12:00:00Z]'` - time is always `12:00:00Z`.
  - `zdb_id`: Search by ZDB-ID
  - `provider`: Search by Data Provider
  - `paper_title`: Search inside the title of the Newspaper

## `zp_pages`

- Returns a DataFrame containing Data on Newspaper-Pages.
- Use any combination of these keyword arguments:
  - `plainpagefulltext`: Search inside the OCR Fulltext (Use a list for multiple search-words)
  - `language`: Use ISO Codes, currently `ger`, `eng`, `fre`, `spa`, `ita`
  - `place_of_distribution`: Search inside "Verbreitungsort", use a list for multiple search-words
  - `publication_date`: Get newspapers by publication date. Use the following format: `1900-12-31T12:00:00Z` for a specific date, use square brackets and `TO` between two dates to get a daterange like so: `publication_date='[1935-09-01T12:00:00Z TO 1935-09-22T12:00:00Z]'` - time is always `12:00:00Z`.
  - `zdb_id`: Search by ZDB-ID
  - `provider`: Search by Data Provider
  - `paper_title`: Search inside the title of the Newspaper

--- 

- Values of keyword arguments may contain lists to combine queries.
- Use `list_column` and `filter` to perform usual Pandas Operations on list-containing Columns (eg. `list_column(df['place_of_distribution']).value_counts()` or `filter('Altona', 'place_of_distribution', df)`)