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Merge pull request #247 from visualpython/release
Release v2.5.0
2 parents 058fb35 + 9d93210 commit 175de5f

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‎build.sh

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@@ -11,8 +11,8 @@
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#=============================================================================
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# Set version and replace it
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#=============================================================================
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VP_ORG_VER=2.4.8
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VP_NEW_VER=2.4.9
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VP_ORG_VER=2.4.9
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VP_NEW_VER=2.5.0
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# update version info
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grep -REil "VP_ORG_VER=.+$" colab/build.colab.sh jupyterlab/build.jupyterlab.sh jupyternotebook/build.jupyternotebook.sh | xargs sed -i "s/VP_ORG_VER=.\+$/VP_ORG_VER=${VP_ORG_VER}/g"

‎colab/build.colab.sh

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#=============================================================================
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# Replace Version
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#=============================================================================
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VP_ORG_VER=2.4.8
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VP_NEW_VER=2.4.9
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VP_ORG_VER=2.4.9
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VP_NEW_VER=2.5.0
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# update version info
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# update manifest version with new numbering for new version

‎colab/manifest.json

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{
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"name": "Visual Python for Colab",
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"description": "GUI-based Python code generator for Google Colab as an extension",
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"version": "2.4.9",
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"version": "2.5.0",
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"manifest_version": 3,
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"icons": {
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"48": "icon.png",

‎jupyterlab/build.jupyterlab.sh

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@@ -11,8 +11,8 @@
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#=============================================================================
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# Replace Version and Basic Files
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#=============================================================================
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VP_ORG_VER=2.4.8
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VP_NEW_VER=2.4.9
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VP_ORG_VER=2.4.9
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VP_NEW_VER=2.5.0
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# update version info
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grep -REil "\"version\": \"${VP_ORG_VER}\"" package.json | xargs sed -i "s/\"version\": \"${VP_ORG_VER//\./\\.}\"/\"version\": \"${VP_NEW_VER}\"/g"

‎jupyterlab/package-lock.json

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‎jupyterlab/package.json

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{
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"name": "jupyterlab-visualpython",
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"version": "2.4.9",
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"version": "2.5.0",
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"description": "GUI-based Python code generator for Jupyter Lab as an extension",
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"keywords": [
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"jupyter",

‎jupyterlab/pyproject.toml

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@@ -32,7 +32,7 @@ classifiers = [
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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]
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version = "2.4.9"
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version = "2.5.0"
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[project.license]
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file = "LICENSE"
@@ -92,7 +92,7 @@ file = [
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]
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[tool.tbump.version]
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current = "2.4.9"
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current = "2.5.0"
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regex = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)((?P<channel>a|b|rc|.dev)(?P<release>\\d+))?"
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[tool.tbump.git]

‎jupyternotebook/build.jupyternotebook.sh

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@@ -11,8 +11,8 @@
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#=============================================================================
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# Replace Version and Basic Files
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#=============================================================================
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VP_ORG_VER=2.4.8
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VP_NEW_VER=2.4.9
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VP_ORG_VER=2.4.9
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VP_NEW_VER=2.5.0
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# update version info
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grep -REil ${VP_ORG_VER//\./\\.} setup.py visualpython/js/com/com_Config.js visualpython/js/com/com_Const.js | xargs sed -i --follow-symlinks "s/${VP_ORG_VER//\./\\.}/${VP_NEW_VER}/g"

‎jupyternotebook/setup.py

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setup(
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name = name,
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version = '2.4.9',
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version = '2.5.0',
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packages = find_packages(),
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package_data = {"": ["*"], 'visualpython' : ['visualpython.yaml', 'README.md']},
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scripts = ['visualpython/bin/visualpy', 'visualpython/bin/visualpy.bat'],

‎visualpython/css/component/popupComponent.css

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height: 25px;
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}
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.vp-popup-frame .vp-accordian-box {
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padding: 0px 15px 15px 0px;
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padding: 0px 15px 0px 0px;
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}
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/* resizable handler */

‎visualpython/css/m_apps/frame.css

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top: 0;
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background-color: var(--vp-background-color);
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border-bottom: 1px solid var(--vp-border-gray-color);
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border-right: 1px solid var(--vp-border-gray-color);
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text-align: right;
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text-overflow: ellipsis;
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/* background: var(--vp-light-gray-color); */
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/* background: rgba(66, 165, 245, 0.2); */
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}
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.vp-fe-table-column-isnumeric {
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margin-right: 5px;
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vertical-align: middle;
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height: 15px;
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line-height: 15px;
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}
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/* Row Hover */
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.vp-fe-table tbody tr:hover {
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float: right;
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display: inline-block;
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}
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/* to datetime */
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.vp-inner-popup-todt-addcol-content {
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display: grid;
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row-gap: 5px;
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max-height: 105px;
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}
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.vp-inner-popup-todt-addcol-head,
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.vp-inner-popup-todt-addcol-item {
320+
display: grid;
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grid-template-columns: 160px 160px auto;
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column-gap: 5px;
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}
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/* UDF Editor - CodeMirror */
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.vp-fr-subset-box {

‎visualpython/css/m_visualize/seaborn.css

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height: 100%;
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}
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.vp-tab-page-box.figure {
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height: calc(100% - 30px);
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height: 100%;
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align-content: baseline;
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grid-template-rows: 1fr;
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overflow: hidden;
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}
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.vp-tab-page-box.figure > .vp-tab-page {
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overflow: auto;
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}
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.vp-tab-page-box.plot {
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height: calc(100% - 30px);
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min-height: 352px;
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/* height: calc(100% - 30px);
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min-height: 352px; */
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align-content: baseline;
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height: 100%;
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max-height: 100%;
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overflow: scroll;
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padding: 15px 15px 0px 15px;
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}
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.vp-chart-plot-box {
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height: 100%;
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display: grid;
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grid-template-rows: 30px calc(100% - 30px);
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overflow: auto;
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}
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.vp-chart-body {
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display: grid;
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.vp-chart-left-box,
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.vp-chart-right-box {
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height: 100%;
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display: grid;
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grid-template-rows: 30px calc(100% - 30px);
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}
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.vp-chart-left-box {
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overflow: auto;
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}
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.vp-chart-right-box {
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overflow: hidden;
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}
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.vp-chart-preview-title {
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line-height: 30px;
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.vp-chart-preview-box {
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min-height: 352px;
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width: 100%;
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height: calc(100% - 30px);
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/* height: calc(100% - 30px); */
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height: 100%;
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}
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.vp-chart-preview-content:empty::after {
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content: 'No preview image';

‎visualpython/data/m_library/pandasLibrary.js

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},
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]
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},
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// ***
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"pd_toParquet": {
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"name": "To Parquet",
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"library": "pandas",
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"description": "DataFrame/Series to Parquet file",
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"code": "${i0}.to_parquet(${path}${etc})",
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"options": [
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{
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"name": "i0",
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"label": "DataFrame",
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"required": true,
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"component": [
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"data_select"
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],
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"var_type": [
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"DataFrame",
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"Series"
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]
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},
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{
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"name": "path",
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"label": "File path/variable",
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"required": true,
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"type": "text"
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}
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]
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},
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"pd_readParquet": {
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"name": "Read Parquet",
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"library": "pandas",
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"description": "Parquet to pandas object",
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"code": "${o0} = pd.read_parquet(${i0}${etc})",
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"options": [
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{
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"name": "i0",
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"label": "File path/object",
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"required": true,
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"type": "text",
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"component": [
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"file"
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]
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},
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{
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"name": "o0",
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"label": "Allocate to",
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"output": true,
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"component": [
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"input"
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],
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"value": "vp_df"
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},
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]
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},
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"pa_readCsv": {
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"name": "Read Csv as pyarrow",
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"library": "pyarrow",
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"description": "Csv to pandas object",
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"code": "${o0} = pa.csv.read_csv(${i0}${etc}).to_pandas()",
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"options": [
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{
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"name": "i0",
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"label": "File path/object",
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"required": true,
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"type": "text",
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"component": [
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"file"
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]
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},
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{
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"name": "o0",
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"label": "Allocate to",
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"output": true,
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"component": [
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"input"
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],
6958+
"value": "vp_df"
6959+
}
6960+
]
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},
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"pa_toCsv": {
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"name": "To Csv as pyarrow",
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"library": "pyarrow",
6965+
"description": "DataFrame/Series to csv file",
6966+
"code": "pa.csv.write_csv(${i0}, ${path})",
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"options": [
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{
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"name": "i0",
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"label": "DataFrame",
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"required": true,
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"component": [
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"data_select"
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],
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"var_type": [
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"DataFrame",
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"Series"
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]
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},
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{
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"name": "path",
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"label": "File path/variable",
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"required": true,
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"type": "text"
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}
6986+
]
6987+
},
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"pa_readJson": {
6989+
"name": "Read Json as pyarrow",
6990+
"library": "pyarrow",
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"description": "Json to pyarrow object",
6992+
"code": "${o0} = pa.json.read_json(${i0}${etc}).to_pandas()",
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"options": [
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{
6995+
"name": "i0",
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"label": "File path/object",
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"required": true,
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"type": "text",
6999+
"component": [
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"file"
7001+
]
7002+
},
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{
7004+
"name": "o0",
7005+
"label": "Allocate to",
7006+
"output": true,
7007+
"component": [
7008+
"input"
7009+
],
7010+
"value": "vp_df"
7011+
}
7012+
]
7013+
},
7014+
"pa_readParquet": {
7015+
"name": "Read Parquet as pyarrow",
7016+
"library": "pyarrow",
7017+
"description": "Parquet to pandas object",
7018+
"code": "${o0} = pa.parquet.read_table(${i0}${etc}).to_pandas()",
7019+
"options": [
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{
7021+
"name": "i0",
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"label": "File path/object",
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"required": true,
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"type": "text",
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"component": [
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"file"
7027+
]
7028+
},
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{
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"name": "o0",
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"label": "Allocate to",
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"output": true,
7033+
"component": [
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"input"
7035+
],
7036+
"value": "vp_df"
7037+
}
7038+
]
7039+
},
7040+
"pa_toParquet": {
7041+
"name": "To Parquet as pyarrow",
7042+
"library": "pyarrow",
7043+
"description": "DataFrame/Series to Parquet file",
7044+
"code": "pa.parquet.write_table(${i0}, ${path})",
7045+
"options": [
7046+
{
7047+
"name": "i0",
7048+
"label": "DataFrame",
7049+
"required": true,
7050+
"component": [
7051+
"data_select"
7052+
],
7053+
"var_type": [
7054+
"DataFrame",
7055+
"Series"
7056+
]
7057+
},
7058+
{
7059+
"name": "path",
7060+
"label": "File path/variable",
7061+
"required": true,
7062+
"type": "text"
7063+
}
7064+
]
7065+
},
68837066
}
68847067

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return {

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