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Package update
feat: Improve error handling and user experience This update enhances the Python package to better match the Stata package's behavior and improve user experience: Key Changes: - Improved error handling with user-friendly messages - Removed traceback output for invalid inputs - Added consistent header display for all error messages - Matched error message format with Stata package - Updated .gitignore for cleaner repository structure Error Handling Improvements: - Invalid variables now show clean error messages with usage instructions - Invalid country codes display available options - Version errors include current and available versions - Raw data errors provide clear usage guidelines - Download errors show user-friendly messages Repository Structure: - Kept essential package files - Removed unnecessary build artifacts and cache - Preserved package metadata - Maintained test suite and documentation Testing: - All 16 test cases passing - Verified error handling behavior - Tested all user interaction scenarios
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‎.gitignore‎

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*$py.class
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# Distribution / packaging
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*.egg-info/
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dist/
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build/
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*.egg
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# Virtual environments
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venv/
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env/
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.env
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.venv
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ENV/
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# Test cache
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.pytest_cache/
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.coverage
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htmlcov/
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# IDE related
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.idea/
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*.swo
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# OS related
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.DS_Store
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.DS_Store
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Thumbs.db
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# Keep egg-info for package metadata
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!global_macro_data.egg-info/

‎README.md‎

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```python
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from global_macro_data import gmd
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# Get preview data (Singapore 2000-2020)
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df = gmd()
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# Get data from latest available version
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df = gmd(show_preview=False)
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df = gmd()
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# Get data from a specific version
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df = gmd(version="2025_01")
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# Get specific variables
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df = gmd(variables=["rGDP", "infl", "unemp"])
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# Get raw data for a single variable
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df = gmd(variables="rGDP", raw=True)
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# List available variables and their descriptions
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gmd(vars=True)
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# List available countries and their ISO codes
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gmd(iso=True)
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# Combine parameters
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df = gmd(version="2025_01", country=["USA", "CHN"], variables=["rGDP", "unemp", "CPI"])
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df = gmd(
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version="2025_01",
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country=["USA", "CHN"],
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variables=["rGDP", "unemp", "CPI"]
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)
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```
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## Parameters
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- **version (str)**: Dataset version in format 'YYYY_MM' (e.g., '2025_01'). If None, the latest dataset is used.
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- **country (str or list)**: ISO3 country code(s) (e.g., "SGP" or ["MRT", "SGP"]). If None, returns all countries.
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- **variables (list)**: List of variable codes to include (e.g., ["rGDP", "unemp"]). If None, all variables are included.
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- **show_preview (bool)**: If True and no other parameters are provided, shows a preview.
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- **variables (str or list)**: Variable code(s) to include (e.g., "rGDP" or ["rGDP", "unemp"])
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- **country (str or list)**: ISO3 country code(s) (e.g., "SGP" or ["MRT", "SGP"])
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- **version (str)**: Dataset version in format 'YYYY_MM' (e.g., '2025_01'). If None or "current", uses the latest version
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- **raw (bool)**: If True, download raw data for a single variable
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- **iso (bool)**: If True, display list of available countries
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- **vars (bool)**: If True, display list of available variables
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## Release schedule
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| Release Date | Details |

‎global_macro_data.egg-info/PKG-INFO‎

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Metadata-Version: 2.4
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Name: global-macro-data
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Version: 0.3.1
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Summary: Global Macro Database by Karsten Müller, Chenzi Xu, Mohamed Lehbib and Ziliang Chen (2025)
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Home-page: https://github.com/KMueller-Lab/Global-Macro-Database-Python
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Author: Yangbo Wang
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Author-email: wangyangbo@ruc.edu.cn
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Classifier: Programming Language :: Python :: 3
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: OS Independent
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Requires-Python: >=3.6
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Description-Content-Type: text/markdown
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Requires-Dist: requests
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Requires-Dist: pandas
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Dynamic: author
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Dynamic: author-email
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Dynamic: classifier
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Dynamic: description
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Dynamic: description-content-type
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Dynamic: home-page
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Dynamic: requires-dist
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Dynamic: requires-python
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Dynamic: summary
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# The Global Macro Database (Python Package)
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<a href="https://www.globalmacrodata.com" target="_blank" rel="noopener noreferrer">
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<img src="https://img.shields.io/badge/Website-Visit-blue?style=flat&logo=google-chrome" alt="Website Badge">
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</a>
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
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[Link to paper 📄](https://www.globalmacrodata.com/research-paper.html)
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This repository complements paper, **Müller, Xu, Lehbib, and Chen (2025)**, which introduces a panel dataset of **46 macroeconomic variables across 243 countries** from historical records beginning in the year **1086** until **2024**, including projections through the year **2030**.
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## Features
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- **Unparalleled Coverage**: Combines data from **32 contemporary sources** (e.g., IMF, World Bank, OECD) with **78 historical datasets**.
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- **Extensive Variables**: GDP, inflation, government finance, trade, employment, interest rates, and more.
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- **Harmonized Data**: Resolves inconsistencies and splices all available data together.
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- **Scheduled Updates**: Regular releases ensure data reliability.
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- **Full Transparency**: All code is open source and available in this repository.
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- **Accessible Formats**: Provided in `.dta`, `.csv` and as **<a href="https://github.com/KMueller-Lab/Global-Macro-Database" target="_blank" rel="noopener noreferrer">Stata</a>
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/<a href="https://github.com/KMueller-Lab/Global-Macro-Database-Python" target="_blank" rel="noopener noreferrer">Python</a>/<a href="https://github.com/KMueller-Lab/Global-Macro-Database-R" target="_blank" rel="noopener noreferrer">R</a> package**.
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## Data access
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<a href="https://www.globalmacrodata.com/data.html" target="_blank" rel="noopener noreferrer">Download via website</a>
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**Python package:**
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```
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pip install global_macro_data
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```
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**How to use (examples)**
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```python
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from global_macro_data import gmd
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# Get data from latest available version
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df = gmd()
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# Get data from a specific version
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df = gmd(version="2025_01")
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# Get data for a specific country
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df = gmd(country="USA")
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# Get data for multiple countries
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df = gmd(country=["USA", "CHN", "DEU"])
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# Get specific variables
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df = gmd(variables=["rGDP", "infl", "unemp"])
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# Get raw data for a single variable
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df = gmd(variables="rGDP", raw=True)
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# List available variables and their descriptions
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gmd(vars=True)
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# List available countries and their ISO codes
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gmd(iso=True)
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# Combine parameters
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df = gmd(
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version="2025_01",
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country=["USA", "CHN"],
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variables=["rGDP", "unemp", "CPI"]
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)
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```
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## Parameters
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- **variables (str or list)**: Variable code(s) to include (e.g., "rGDP" or ["rGDP", "unemp"])
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- **country (str or list)**: ISO3 country code(s) (e.g., "SGP" or ["MRT", "SGP"])
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- **version (str)**: Dataset version in format 'YYYY_MM' (e.g., '2025_01'). If None or "current", uses the latest version
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- **raw (bool)**: If True, download raw data for a single variable
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- **iso (bool)**: If True, display list of available countries
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- **vars (bool)**: If True, display list of available variables
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## Release schedule
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| Release Date | Details |
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|--------------|-----------------|
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| 2025-01-30 | Initial release: 2025_01 |
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| 2025-04-01 | 2025_03 |
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| 2025-07-01 | 2025_06 |
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| 2025-10-01 | 2025_09 |
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| 2026-01-01 | 2025_12 |
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## Citation
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To cite this dataset, please use the following reference:
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```bibtex
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@techreport{mueller2025global,
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title = {The Global Macro Database: A New International Macroeconomic Dataset},
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author = {Müller, Karsten and Xu, Chenzi and Lehbib, Mohamed and Chen, Ziliang},
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year = {2025},
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type = {Working Paper}
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}
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```
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## Acknowledgments
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The development of the Global Macro Database would not have been possible without the generous funding provided by the Singapore Ministry of Education (MOE) through the PYP grants (WBS A-0003319-01-00 and A-0003319-02-00), a Tier 1 grant (A-8001749- 00-00), and the NUS Risk Management Institute (A-8002360-00-00). This financial support laid the foundation for the successful completion of this extensive project.

‎global_macro_data.egg-info/SOURCES.txt‎

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README.md
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setup.py
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global_macro_data/__init__.py
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global_macro_data/gmd.py
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global_macro_data.egg-info/PKG-INFO
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global_macro_data.egg-info/SOURCES.txt
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global_macro_data.egg-info/dependency_links.txt
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global_macro_data.egg-info/requires.txt
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global_macro_data.egg-info/top_level.txt
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tests/test_gmd.py

‎global_macro_data.egg-info/dependency_links.txt‎

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‎global_macro_data.egg-info/requires.txt‎

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requests
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pandas

‎global_macro_data.egg-info/top_level.txt‎

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global_macro_data

‎global_macro_data/__init__.py‎

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import os
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import requests
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import pandas as pd
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from .gmd import (
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gmd,
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get_available_versions,
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get_current_version,
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list_variables,
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list_countries,
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VALID_VARIABLES
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)
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# Allowed quarters
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VALID_QUARTERS = ["01", "03", "06", "09", "12"]
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from .gmd import gmd, find_latest_data
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__all__ = ["gmd", "find_latest_data", "VALID_QUARTERS"]
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__all__ = [
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"gmd",
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"get_available_versions",
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"get_current_version",
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"list_variables",
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"list_countries",
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"VALID_VARIABLES"
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]

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