semvec/pypi-packages huggingface dataset:
macroeconomy 0.1.2
An realism economic analysis package.
Requires Python: >=3.10
Keywords: Jerry Skywolf, Jerry_Skywolf, macroeconomy, economy, economic analysis, New Classical Macro Theory, China's Economy

# Macroeconomy  _0.1.2_

A macroeconomic analysis package followed the philosophy and methods of the New Classical Macro Theory.

### Model Introduction

New Classical Economy

This basic macroeconomic model is adapted from a dynamically multiple Ramsey Model, which could be extended into many occasions.
It follows the philosophy and methods of the New Classical Macro Theory where macroeconomic model must have micro-foundation,
and thus basic assumptions in the theory, for instance, Say's Law, Inda Conditions and CRS, are accepted here.
For the perspective of production, the model adopts the traditional choice: Cobb Douglas Production Function,
while Logarithmic form is chosen as the utility function.
In order to simplify calculation, labor is normalized into 1, and TFP(A) is assumed as a const 1.
All variables below are counted by consumer goods, reflecting the real economy.
Therefore, monetary factors are neglected in this very brief model.
As a result of the New Classical Macro Assumptions, this model has it structural limitation,
which means it is absolutely a terrible idea to apply this model to analyze an economy with Insufficient Aggregate Demand, such as China's.

China's Economy

Aimed to describe a realer economy with Insufficient Consumption, or Excess Savings in otherwise,
such as China's economy since the visionary policy Reform and Opening-up was implemented in 1978，
this adapted new classical model assumes that theta precents of firms in the economy are state-owned,
which means their operational target is to maximize their scales, and they are rigid savers,
observing China's reality.

### User Guide
Call the classes directly is quite a practical method, for instance,

`from macroenonmy.base import *`

`state = NewClassicalEconomy(1.0, 0.0085, 0.6, 20)`

`state = ChinaEconomy(1.0, 0.01, 0.4, 0.6, 20)`

Detailed introduction of every class is available in their own code areas, and a brief example is available in the `if __name__=='__main__'` part at the end of some main files.

### Download

Here is my website:
* https://github.com/JerrySkywolf

This package could be downloaded through PyPi by:

`pip install macroeconomy`

View at the webpage
* https://pypi.org/project/macroeconomy
scrapy-contrib-bigexporters 1.0.0
Scrapy exporter for Big Data formats
Requires Python: >=3.12

===========================
scrapy-contrib-bigexporters
===========================


Overview
========

scrapy-contrib-bigexporters provides additional exporters for the web crawling and scraping framework Scrapy (https://scrapy.org).

The following big data formats are supported:

* Avro: https://avro.apache.org/
* Iceberg: https://iceberg.apache.org/
* Parquet: https://parquet.apache.org/
* Orc: https://orc.apache.org

The library is published using `pypi trusted publishers <https://docs.pypi.org/trusted-publishers/>`_

Requirements
============

* Python 3.12+
* Scrapy 2.13+
* Works on Linux, Windows, macOS, BSD
* Parquet export requires pyarrow 22.00+ and pandas
* Avro export requires fastavro 1.12+
* ORC export requires pyarrow 22.00+ and pandas
* Iceberg export requires pyiceberg 0.10+, pyarrow 22.00+ and pandas

Install
=======

The quick way (pip)::

    pip install scrapy-contrib-bigexporters

Alternatively, you can install it from `conda-forge <https://anaconda.org/conda-forge/scrapy-contrib-bigexporters>`_::

    conda install -c conda-forge scrapy-contrib-bigexporters

Depending on which format you want to use you need to install one or more of the following libraries.

Avro::

    pip install fastavro
    
Avro is a file format.

Iceberg::

    pip install pyiceberg pyarrow pandas

Iceberg is an open table format.

Note: Most likely you will need to add specific dependencies so that Iceberg works for you. See `pyiceberg installation <https://py.iceberg.apache.org/#installation>`_

ORC::

    pip install pyarrow pandas

ORC is a file format.

Parquet::

    pip install pyarrow pandas

Parquet is a file format.

Additional libraries may be needed for specific compression algorithms. The open table format may require additional libraries also to use different filesystems, catalogs and compression formats. See "Use".

Use
====

Use of the library is simple. Install it with your Scrapy project as described above.You only need to configure the exporter in the Scrapy settings, run your scraper and the data will be exported into your desired format. There is no development needed.

See here for configuring the exporter in settings:

* `Avro <https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters/src/branch/main/docs/avro.rst>`_
* `Iceberg <https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters/src/branch/main/docs/iceberg.rst>`_
* `Parquet <https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters/src/branch/main/docs/parquet.rst>`_
* `ORC <https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters/src/branch/main/docs/orc.rst>`_

Source
======

The source is available at:

* Codeberg (a non-commercial European hosted Git for Open Source): https://codeberg.org/ZuInnoTe/scrapy-contrib-bigexporters
* Github (an US hosted commercial Git platform): https://github.com/ZuInnoTe/scrapy-contrib-bigexporters