Rename iopy to iotables; revive package

.github/workflows/ci.yml

@@ -0,0 +1,44 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  test:
+    name: Offline tests (Python ${{ matrix.python-version }})
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install package with dev deps
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e ".[dev]"
+      - name: Run offline tests
+        # Network tests download hundreds of MB of real data; they are excluded from CI
+        # and run manually. Everything else must pass on every supported Python version.
+        run: pytest -m "not network"
+
+  build:
+    name: Build & check distribution
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+      - name: Build sdist and wheel
+        run: |
+          python -m pip install --upgrade pip build twine
+          python -m build
+      - name: Validate metadata and README rendering
+        run: twine check dist/*

.github/workflows/deploy.yml

@@ -0,0 +1,33 @@
+name: deploy
+
+on: workflow_dispatch
+
+jobs:
+  deploy:
+    environment: Deploy
+    runs-on: ubuntu-latest
+    permissions:
+      # Required for PyPI Trusted Publishing (OIDC); no API token/secret needed.
+      id-token: write
+      contents: read
+    steps:
+      - run: echo "Starting deployment to PyPi"
+      - uses: actions/checkout@v5
+      - name: Set up Python 3.10
+        uses: actions/setup-python@v6
+        with:
+          python-version: "3.10"
+      - name: Install helpers
+        run: |
+          python -m pip install --upgrade pip
+          pip install build twine
+      - name: Build
+        # This project uses a pyproject.toml build backend (no setup.py), so build
+        # with the PEP 517 frontend rather than `setup.py sdist bdist_wheel`.
+        run: python -m build
+      - name: Check distribution metadata
+        run: twine check dist/*
+      - name: Deploy to PyPi
+        # Trusted Publishing: PyPI verifies this repo/workflow/environment via OIDC.
+        uses: pypa/gh-action-pypi-publish@release/v1
+      - run: echo "Successfully deployed to PyPi"

.gitignore

@@ -9,4 +9,16 @@
 .pip/
 **/__pycache__/
 **/.temp_data/
+test.py
+.DS_Store
+**/.DS_Store
 
+# packaging build artifacts
+build/
+dist/
+*.egg-info/
+src/*.egg-info/
+
+# editor / tooling
+.vscode/
+CLAUDE.md

CHANGELOG.MD

@@ -4,13 +4,30 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/)
 and this project adheres to [Semantic Versioning](http://semver.org/).
 
-## [Unreleased] - yyyy-mm-dd
+## [0.1.0] - 2026-06-06
 
 ### Added
 - Introduce structure for different dataset-specific tools
-- ...
+- `proxy` and `verify` options on the loaders for downloading behind a proxy / custom TLS
+- `Matrix.to_pandas()` to convert a matrix to a labelled DataFrame
+- OECD ICIO 2025 edition (`2025-regular`, `2025-extended`) and Eurostat Figaro 2025 edition (`2025`, years 2010-2023)
 ### Changed
+- Renamed the package from `iopy` to `iotables` and adopted a `src/` layout with `pyproject.toml`
+- Downloads now use `curl_cffi` (browser TLS impersonation) so Cloudflare-protected OECD files work
+- Re-pointed OECD/Figaro download URLs to current hosts (OECD `webfs`, Figaro CIRCABC)
+- Cached downloads now live in a user cache dir (`~/.cache/iotables`, override with `IOTABLES_DATA`)
+- User-facing argument validation now raises `ValueError` instead of `assert` (so it survives `python -O`)
 ### Fixed
+- OECD `2025-regular` file-id regex and in-zip CSV filenames; cross-edition cache-id collisions
+- `remove_downloaded_files(database=...)` deleted the wrong database's files
+- `ExioBase` download-failure handler raised `AttributeError` instead of the intended warning
+- Loader `db_name` derivation used `str.rstrip('.py')` (a character set, not a suffix)
+- Dropped `lru_cache` on `_load_data`, which pinned every loader instance (and its data) in memory
+- Downloads are now atomic (written to a `.part` file and moved into place on completion), so an interrupted download no longer leaves a truncated file in the cache
+- `download_file` now verifies the downloaded size against `Content-Length` (when advertised and unencoded) and raises on a truncated body
+### Other
+- Added a `py.typed` marker, `[project.urls]`, Python-version classifiers, and a GitHub Actions CI (offline tests across Python 3.9-3.13 + build/twine check)
+- Network tests are marked `network` and moved into fixtures, so the suite collects and the offline tests run without a connection (`pytest -m "not network"`)
 ___
 
 

README.md

@@ -1,4 +1,4 @@
-# iopy
+# iotables
 
 ## Description
 
@@ -14,14 +14,15 @@ Currently the following databases are supported:
 
 ## Installation
 ```bash
-pip install git+https://github.com/WWakker/iopy.git
+pip install iotables
 ```
 
 ## Structure of input-output data
 
 Input-data model the economy in matrix form. Here, we explain input-output data using OECD data as an example.
-THE OECD input-output tables contain inputs and outputs in current million USD for 45 sectors and 66 countries as well 
-as rest-of-world. China and Mexico data are split into CN1, CN2, MX1, and MX2.
+The OECD input-output tables contain inputs and outputs in current million USD for a set of sectors and countries (the
+exact counts depend on the edition; see `config.py`) as well as rest-of-world. China and Mexico data are split into CN1,
+CN2, MX1, and MX2.
 
 ![OECD sctructure](res/OECD_structure.png)
 *Source*: OECD
@@ -173,19 +174,20 @@ This is the Ghosh equation, which defines the relation between production output
 ### Create an instance of the OECD class
 
 Creating an instance of the OECD class loads the OECD data and gives access to convenient attributes and methods. 
-An instance can be create as follows, specifiying a year between 1995 and 2018.
+An instance can be created as follows, specifying an available year for the chosen version (e.g. 1995-2018 for the
+`2021` version, up to 2022 for the `2025` versions).
 
 ```python
-import iopy 
-oecd = iopy.OECD(version='2021', year=2018, refresh=False)
+import iotables 
+oecd = iotables.OECD(version='2021', year=2018, refresh=False)
 ```
 
 Similary, an instance can be created for other data, for example Figaro and ExioBase as
 
 ```python
-import iopy 
-figaro = iopy.Figaro(version='2022', year=2020, kind='industry-by-industry')
-exio = iopy.ExioBase(version='3.81', year=2022, kind='industry-by-industry')
+import iotables 
+figaro = iotables.Figaro(version='2025', year=2020, kind='industry-by-industry')
+exio = iotables.ExioBase(version='3.81', year=2022, kind='industry-by-industry')
 ```
 
 Creating an instance of a database class downloads and loads the data into memory, creates standard input-output matrices, and gives access to the following attributes and methods:
@@ -223,11 +225,11 @@ All matrices are extended `numpy.ndarray`'s with attributes `info`, `rows` and `
 
 When running a Leontief or Ghosh shock, the percentage shock to final demand/primary inputs in countries and sectors can be specified as
 ```python
-import iopy
+import iotables
 
-oecd = iopy.OECD(version='2021', year=2018)
+oecd = iotables.OECD(version='2021', year=2018)
 
-df_l = oecd.leontief_demand_shock(shock=-10, regions=['FR', 'DE], sectors=['01T02', '35'])
+df_l = oecd.leontief_demand_shock(shock=-10, regions=['FR', 'DE'], sectors=['01T02', '35'])
 df_g = oecd.ghosh_supply_shock(shock=-10, regions=['FR', 'DE'], sectors=['01T02', '35'])
 ```