release: 0.0.1
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README.md
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README.md
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@ -100,6 +100,56 @@ pip install pandas numpy scipy scikit-learn matplotlib seaborn openpyxl xlrd
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pip install black autopep8 basedpyright
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pip install black autopep8 basedpyright
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```
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```
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### 1.6 打包 Qfunctions + Qtorch 为 Conda 包
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项目已提供可直接构建的打包文件：
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- `pyproject.toml`
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- `conda_env/recipe/meta.yaml`
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构建步骤：
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```bash
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conda activate Deeplearning
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conda install -n Deeplearning -y conda-build anaconda-client
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cd /home/newbie/Project/MachineLearning/Deeplearning
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conda-build conda_env/recipe
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```
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本地安装（从本机 conda-bld）：
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```bash
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conda activate Deeplearning
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conda install -n Deeplearning -y -c local deeplearning-qtools
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```
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安装后即可使用：
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```bash
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python -c "import Qfunctions, Qtorch; print('ok')"
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```
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发布到 Anaconda.org 后，其他项目（如 GestureRecognition）可直接安装：
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```bash
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conda install -c <your-channel> deeplearning-qtools
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```
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一键发布到 Gitea（自动构建 + 打 tag + push + 可选创建 Release）：
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```bash
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cd /home/newbie/Project/MachineLearning/Deeplearning
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chmod +x Scripts/publish_to_gitea.sh
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./Scripts/publish_to_gitea.sh
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```
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如果希望脚本自动在 Gitea 创建 Release 并上传 conda 包，请先设置：
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```bash
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export GITEA_TOKEN=<your_gitea_token>
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./Scripts/publish_to_gitea.sh
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```
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## 2. 项目约定
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## 2. 项目约定
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### 2.1 输入数据格式
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### 2.1 输入数据格式
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@ -0,0 +1,145 @@
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#!/usr/bin/env bash
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set -euo pipefail
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# One-command publish flow:
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# 1) Build conda package
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# 2) Commit current changes (if any)
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# 3) Tag as v<version>
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# 4) Push branch + tag to origin (your Gitea remote)
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# 5) Optionally create Gitea Release and upload built package when GITEA_TOKEN is set
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ROOT_DIR="$(cd "$(dirname "$0")/.." && pwd)"
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cd "$ROOT_DIR"
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if ! command -v python >/dev/null 2>&1; then
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echo "python not found in PATH"
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exit 1
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fi
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if ! command -v conda >/dev/null 2>&1; then
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echo "conda not found in PATH"
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exit 1
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fi
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if ! command -v conda-build >/dev/null 2>&1; then
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echo "conda-build is not installed in current environment."
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echo "Run: conda install -n Deeplearning -y conda-build"
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exit 1
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fi
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VERSION="$(python - <<'PY'
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import pathlib
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import re
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text = pathlib.Path('pyproject.toml').read_text(encoding='utf-8')
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m = re.search(r'^version\s*=\s*"([^"]+)"', text, flags=re.M)
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if not m:
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raise SystemExit('Could not read version from pyproject.toml')
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print(m.group(1))
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PY
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)"
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TAG="v${VERSION}"
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echo "Building conda package for version: ${VERSION}"
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PKG_PATH="$(conda-build conda_env/recipe --output)"
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conda-build conda_env/recipe
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if git diff --quiet && git diff --cached --quiet; then
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echo "No local file changes to commit."
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else
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git add pyproject.toml conda_env/recipe/meta.yaml conda_env/recipe/README.md Scripts/publish_to_gitea.sh README.md
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git commit -m "release: ${VERSION}" || true
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fi
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if git rev-parse "${TAG}" >/dev/null 2>&1; then
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echo "Tag ${TAG} already exists locally."
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else
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git tag -a "${TAG}" -m "Release ${TAG}"
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fi
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echo "Pushing current branch and tag to origin"
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git push origin HEAD
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git push origin "${TAG}"
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echo "Pushed to origin."
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if [[ -z "${GITEA_TOKEN:-}" ]]; then
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echo "GITEA_TOKEN not set. Skip creating Gitea Release."
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echo "Built package: ${PKG_PATH}"
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exit 0
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fi
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ORIGIN_URL="$(git remote get-url origin)"
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parse_owner_repo() {
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local url="$1"
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if [[ "$url" =~ ^git@([^:]+):(.+)\.git$ ]]; then
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echo "${BASH_REMATCH[1]}|${BASH_REMATCH[2]}"
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return
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fi
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if [[ "$url" =~ ^https?://([^/]+)/(.+)\.git$ ]]; then
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echo "${BASH_REMATCH[1]}|${BASH_REMATCH[2]}"
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return
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fi
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echo ""
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}
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PARSED="$(parse_owner_repo "$ORIGIN_URL")"
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if [[ -z "$PARSED" ]]; then
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echo "Cannot parse origin URL: $ORIGIN_URL"
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exit 1
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fi
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GITEA_HOST="${PARSED%%|*}"
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OWNER_REPO="${PARSED#*|}"
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API_BASE="https://${GITEA_HOST}/api/v1/repos/${OWNER_REPO}"
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echo "Creating or updating Gitea release ${TAG} on ${OWNER_REPO}"
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RELEASE_JSON="$(curl -sS -X POST "${API_BASE}/releases" \
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-H "Authorization: token ${GITEA_TOKEN}" \
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-H "Content-Type: application/json" \
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-d "{\"tag_name\":\"${TAG}\",\"name\":\"${TAG}\",\"draft\":false,\"prerelease\":false}" || true)"
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RELEASE_ID="$(printf '%s' "$RELEASE_JSON" | python - <<'PY'
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import json,sys
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text=sys.stdin.read().strip()
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if not text:
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print('')
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raise SystemExit
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try:
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obj=json.loads(text)
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except Exception:
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print('')
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raise SystemExit
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print(obj.get('id',''))
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PY
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)"
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if [[ -z "$RELEASE_ID" ]]; then
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RELEASE_ID="$(curl -sS -H "Authorization: token ${GITEA_TOKEN}" "${API_BASE}/releases/tags/${TAG}" | python - <<'PY'
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import json,sys
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text=sys.stdin.read().strip()
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try:
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obj=json.loads(text)
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except Exception:
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print('')
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raise SystemExit
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print(obj.get('id',''))
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PY
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)"
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fi
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if [[ -z "$RELEASE_ID" ]]; then
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echo "Failed to get release id for tag ${TAG}"
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exit 1
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fi
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PKG_FILE="$(basename "$PKG_PATH")"
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echo "Uploading asset ${PKG_FILE}"
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curl -sS -X POST "${API_BASE}/releases/${RELEASE_ID}/assets?name=${PKG_FILE}" \
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-H "Authorization: token ${GITEA_TOKEN}" \
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-H "Content-Type: application/octet-stream" \
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--data-binary "@${PKG_PATH}" >/dev/null
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echo "Release published: ${TAG}"
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echo "Asset uploaded: ${PKG_FILE}"
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@ -0,0 +1,44 @@
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# Build and install Deeplearning conda package
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This recipe packages both `Qfunctions` and `Qtorch` into one conda package:
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- Package name: `deeplearning-qtools`
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- Import names after install: `Qfunctions`, `Qtorch`
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## 1) Build package
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```bash
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conda activate Deeplearning
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conda install -n Deeplearning -y conda-build anaconda-client
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cd /home/newbie/Project/MachineLearning/Deeplearning
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conda-build conda_env/recipe
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```
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## 2) Install from local build output
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```bash
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conda activate Deeplearning
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conda install -n Deeplearning -y -c local deeplearning-qtools
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```
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## 3) Verify imports
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```bash
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python -c "import Qfunctions, Qtorch; print('ok')"
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```
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## 4) Upload to Anaconda.org (optional)
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```bash
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# Login once
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anaconda login
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# Upload generated package (linux-64/noarch path depends on build output)
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anaconda upload /home/<USER>/miniconda3/conda-bld/noarch/deeplearning-qtools-0.0.1-py_0.conda
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```
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After upload, others can install with:
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```bash
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conda install -c <your-channel> deeplearning-qtools
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```
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{% set name = "deeplearning-qtools" %}
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{% set version = "0.0.1" %}
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package:
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name: {{ name|lower }}
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version: {{ version }}
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source:
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path: ../..
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build:
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noarch: python
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number: 0
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script: "{{ PYTHON }} -m pip install . --no-deps --no-build-isolation -vv"
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requirements:
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host:
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- python >=3.10
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- pip
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- setuptools >=68
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- wheel
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run:
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- python >=3.10
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- numpy >=1.24
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- pandas >=2.0
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- matplotlib >=3.7
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- scikit-learn >=1.3
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- openpyxl >=3.1
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- pytorch >=2.0
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test:
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imports:
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- Qfunctions
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- Qtorch
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about:
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summary: Reusable Qfunctions and Qtorch modules from Deeplearning
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license: Proprietary
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extra:
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recipe-maintainers:
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- deeplearning-team
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@ -0,0 +1,26 @@
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[build-system]
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requires = ["setuptools>=68", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "deeplearning-qtools"
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version = "0.0.1"
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description = "Reusable Qfunctions and Qtorch modules from Deeplearning"
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readme = "README.md"
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requires-python = ">=3.10"
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authors = [{ name = "Deeplearning Team" }]
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dependencies = [
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"numpy>=1.24",
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"pandas>=2.0",
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"matplotlib>=3.7",
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"scikit-learn>=1.3",
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"openpyxl>=3.1",
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"torch>=2.0",
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]
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[tool.setuptools]
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include-package-data = true
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[tool.setuptools.packages.find]
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include = ["Qfunctions*", "Qtorch*"]
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exclude = ["Result*", "Static*", "Scripts*", "conda_env*"]
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