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Excel tool im Browser

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jonasgaudian
2026-02-21 02:01:12 +01:00
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# Git
.git
.gitignore
# Python
__pycache__
*.py[cod]
*$py.class
*.so
.Python
venv/
env/
.venv/
ENV/
*.egg-info/
dist/
build/
# IDE
.vscode/
.idea/
*.swp
*.swo
# Tests
excel_filter/tests/
pytest.ini
*.test.py
# Documentation
README.md
# Build artifacts
excel_filter/build/
excel_filter/*.spec
excel_filter/*.exe
excel_filter/*.bat
# Development files
*.log
.env
presets.json
# Temporary files
*.tmp
*.temp
.cache/

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*.vscode
excel_filter/build/
excel_filter/dist/
venv/

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[server]
port = 8501
address = "0.0.0.0"
headless = true
enableXsrfProtection = true
enableWebsocketCompression = true
[browser]
gatherUsageStats = false
[theme]
primaryColor = "#F03E3E"
backgroundColor = "#0F1115"
secondaryBackgroundColor = "#1E2028"
textColor = "#FFFFFF"
font = "sans serif"

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# Excel Filter Tool - Streamlit Docker Image
# Optimized for Coolify deployment
FROM python:3.11-slim
# Set working directory
WORKDIR /app
# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
PIP_NO_CACHE_DIR=1 \
PIP_DISABLE_PIP_VERSION_CHECK=1
# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements first for better caching
COPY excel_filter/requirements.txt ./requirements.txt
# Install Python dependencies
RUN pip install --upgrade pip && \
pip install -r requirements.txt && \
pip install streamlit
# Copy application code
COPY excel_filter/ ./excel_filter/
COPY streamlit_app.py .
COPY .streamlit/ .streamlit/
# Create a non-root user for security
RUN useradd --create-home --shell /bin/bash appuser && \
chown -R appuser:appuser /app
USER appuser
# Expose Streamlit port
EXPOSE 8501
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD curl --fail http://localhost:8501/_stcore/health || exit 1
# Run Streamlit
ENTRYPOINT ["streamlit", "run", "streamlit_app.py"]

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# Excel Filter Tool - Streamlit Web Application
A modern web-based Excel filtering tool built with Streamlit. This application allows you to filter Excel files using regex patterns, numeric filters, and column selection - all from your browser without installing any software.
## Features
- 📁 **Easy File Upload**: Drag and drop Excel files (.xlsx, .xls)
- 🔍 **Regex Filtering**: Filter rows using powerful regex patterns
- 🔢 **Numeric Filters**: Filter by numeric comparisons (>, <, >=, <=, =)
- 📊 **Column Selection**: Choose specific columns for output
- 🌐 **Multi-language Support**: German and English interface
- 📈 **Statistics**: View filtering statistics and retention rates
- 💾 **Configuration**: Save and load filter configurations
## Quick Start
### Run Locally (Windows)
```bash
run_streamlit.bat
```
### Run Locally (Linux/Mac)
```bash
chmod +x run_streamlit.sh
./run_streamlit.sh
```
### Run with Docker
```bash
docker build -t excel-filter .
docker run -p 8501:8501 excel-filter
```
### Run with Docker Compose
```bash
docker-compose up -d
```
## Coolify Deployment
### Option 1: Docker Compose
1. Push this repository to your Git server
2. In Coolify, create a new resource and select "Docker Compose"
3. Point to your repository
4. Deploy!
### Option 2: Dockerfile
1. In Coolify, create a new resource and select "Dockerfile"
2. Point to your repository
3. Set the port to `8501`
4. Deploy!
### Environment Variables (Optional)
No environment variables are required, but you can set:
- `TZ` - Timezone (default: UTC)
## Usage
1. **Upload**: Drag and drop an Excel file or click to browse
2. **Select Sheet**: Choose the worksheet to filter
3. **Configure Filters**:
- **Regex Tab**: Enable regex filtering and enter a pattern
- **Numeric Tab**: Set up numeric comparisons
- **Columns Tab**: Select which columns to include
4. **Apply**: Click "Apply Filters" to process
5. **Download**: Click "Download Filtered File" to get results
## File Structure
```
├── streamlit_app.py # Main Streamlit application
├── Dockerfile # Docker configuration
├── docker-compose.yml # Docker Compose configuration
├── .dockerignore # Docker ignore file
├── .streamlit/
│ └── config.toml # Streamlit configuration
├── run_streamlit.bat # Windows runner script
├── run_streamlit.sh # Linux/Mac runner script
└── excel_filter/ # Core filter module
├── filter.py # Main filter logic
├── requirements.txt # Python dependencies
└── locales/ # Translations
├── de.json
└── en.json
```
## Regex Examples
| Pattern | Description |
|---------|-------------|
| `error\|warning` | Find rows with "error" OR "warning" |
| `[0-9]{4}` | Find 4-digit numbers |
| `[a-z]+@[a-z]+\.[a-z]{2,}` | Find email addresses |
| `\d{4}-\d{2}-\d{2}` | Find dates (YYYY-MM-DD) |
| `error.*critical` | Find "error" followed by "critical" |
## Development
### Prerequisites
- Python 3.11+
- pip
### Installation
```bash
python -m venv venv
source venv/bin/activate # Linux/Mac
# or
venv\Scripts\activate # Windows
pip install -r excel_filter/requirements.txt
pip install streamlit
```
### Run Development Server
```bash
streamlit run streamlit_app.py
```
## License
See LICENSE file for details.

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# Excel Filter Tool - Docker Compose Configuration
# For Coolify deployment
version: '3.8'
services:
excel-filter:
build:
context: .
dockerfile: Dockerfile
container_name: excel-filter-app
restart: unless-stopped
ports:
- "8501:8501"
environment:
- TZ=Europe/Berlin
volumes:
# Optional: Persist temporary files
- temp_data:/tmp
networks:
- excel-filter-network
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8501/_stcore/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 10s
volumes:
temp_data:
driver: local
networks:
excel-filter-network:
driver: bridge

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python-docx>=1.1.0
pytest>=8.0.0
psutil>=5.8.0
streamlit>=1.28.0

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@echo off
REM Excel Filter Tool - Streamlit App Runner
REM This script starts the Streamlit web application
echo ========================================
echo Excel Filter Tool - Web Application
echo ========================================
echo.
REM Check if Python is installed
python --version >nul 2>&1
if errorlevel 1 (
echo Error: Python is not installed or not in PATH
pause
exit /b 1
)
REM Check if we're in the correct directory
if not exist "streamlit_app.py" (
echo Error: streamlit_app.py not found
echo Please run this script from the project root directory
pause
exit /b 1
)
REM Create virtual environment if it doesn't exist
if not exist "venv" (
echo Creating virtual environment...
python -m venv venv
)
REM Activate virtual environment
echo Activating virtual environment...
call venv\Scripts\activate.bat
REM Install/upgrade pip
echo Upgrading pip...
python -m pip install --upgrade pip -q
REM Install requirements
echo Installing dependencies...
pip install -r excel_filter\requirements.txt -q
pip install streamlit -q
echo.
echo Starting Streamlit server...
echo The app will open in your browser automatically.
echo Press Ctrl+C to stop the server.
echo.
REM Run Streamlit app
streamlit run streamlit_app.py
REM Deactivate virtual environment on exit
call venv\Scripts\deactivate.bat

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#!/bin/bash
# Excel Filter Tool - Streamlit App Runner
# This script starts the Streamlit web application
echo "========================================"
echo " Excel Filter Tool - Web Application"
echo "========================================"
echo ""
# Check if Python is installed
if ! command -v python &> /dev/null; then
echo "Error: Python is not installed or not in PATH"
exit 1
fi
# Check if we're in the correct directory
if [ ! -f "streamlit_app.py" ]; then
echo "Error: streamlit_app.py not found"
echo "Please run this script from the project root directory"
exit 1
fi
# Create virtual environment if it doesn't exist
if [ ! -d "venv" ]; then
echo "Creating virtual environment..."
python -m venv venv
fi
# Activate virtual environment
echo "Activating virtual environment..."
source venv/bin/activate 2>/dev/null || source venv/Scripts/activate 2>/dev/null
# Install/upgrade pip
echo "Upgrading pip..."
pip install --upgrade pip -q
# Install requirements
echo "Installing dependencies..."
pip install -r excel_filter/requirements.txt -q
pip install streamlit -q
echo ""
echo "Starting Streamlit server..."
echo "The app will open in your browser automatically."
echo "Press Ctrl+C to stop the server."
echo ""
# Run Streamlit app
streamlit run streamlit_app.py --server.headless=true
# Deactivate virtual environment on exit
deactivate

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import streamlit as st
import pandas as pd
import re
from io import BytesIO
from typing import List, Dict, Any, Optional
import time
# Seitenkonfiguration
st.set_page_config(
page_title="Excel Filter Tool",
page_icon=None,
layout="wide",
initial_sidebar_state="expanded"
)
# --- Regex Bausteine ---
REGEX_BRICKS = {
"Exakter Text": {
"regex": "{}",
"desc": "Findet den exakten Text, den du eingibst. Sonderzeichen werden automatisch maskiert.",
"needs_input": True,
"allows_quantifier": True
},
"Ziffer (0-9)": {
"regex": r"\d",
"desc": "Findet eine einzelne Ziffer von 0 bis 9.",
"needs_input": False,
"allows_quantifier": True
},
"Buchstabe (A-Z, a-z)": {
"regex": r"[a-zA-Z]",
"desc": "Findet einen einzelnen Buchstaben des deutschen Alphabets, sowohl Groß- als auch Kleinschreibung. Achtung, gilt nicht für Umlaute!",
"needs_input": False,
"allows_quantifier": True
},
"Leerzeichen": {
"regex": r"\s",
"desc": "Findet Leerzeichen, Tabulatoren und Zeilenumbrüche.",
"needs_input": False,
"allows_quantifier": True
},
"Beliebiges einzelnes Zeichen": {
"regex": r".",
"desc": "Findet genau ein beliebiges Zeichen (Buchstabe, Ziffer, Symbol oder Leerzeichen).",
"needs_input": False,
"allows_quantifier": True
},
"Beliebige Zeichenfolge": {
"regex": r".*",
"desc": "Findet null oder mehr beliebige Zeichen. Nützlich als breiter Platzhalter.",
"needs_input": False,
"allows_quantifier": False
},
"ODER (Alternative)": {
"regex": r"|",
"desc": "Funktioniert als logischer ODER-Operator. Das Muster findet entweder den Ausdruck davor oder danach.",
"needs_input": False,
"allows_quantifier": False
},
"Zeilenanfang": {
"regex": r"^",
"desc": "Verankert den Treffer am Anfang einer Zeile oder Zeichenkette.",
"needs_input": False,
"allows_quantifier": False
},
"Zeilenende": {
"regex": r"$",
"desc": "Verankert den Treffer am Ende einer Zeile oder Zeichenkette.",
"needs_input": False,
"allows_quantifier": False
}
}
QUANTIFIERS = {
"Genau 1 (Standard)": "",
"1 oder mehr (+)": "+",
"0 oder mehr (*)": "*",
"Optional: 0 oder 1 (?)": "?"
}
def get_pattern_presets() -> Dict[str, str]:
return {
"Fehler & Warnungen": r"error|warning|critical|fehler|warnung",
"Nur Fehler": r"error|fehler",
"Nur Warnungen": r"warning|warnung",
"Kritische Fehler": r"critical|kritisch",
"E-Mail-Adressen": r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}",
"Telefonnummern": r"\+?[0-9\s-]{10,}",
"Datum (JJJJ-MM-TT)": r"\d{4}-\d{2}-\d{2}",
}
def init_session_state():
defaults = {
"df": None,
"sheets": [],
"selected_sheet": None,
"columns": [],
"filtered_df": None,
"stats": None,
"regex_enabled": True,
"numeric_enabled": False,
"column_selection_enabled": False,
"selected_columns": [],
"regex_pattern": "",
"regex_test_text": "",
"regex_blocks": [],
"temp_block_val": "",
"temp_quantifier": "Genau 1 (Standard)"
}
for key, val in defaults.items():
if key not in st.session_state:
st.session_state[key] = val
def load_excel_file(uploaded_file) -> tuple:
try:
file_bytes = BytesIO(uploaded_file.getvalue())
xls = pd.ExcelFile(file_bytes)
sheets = xls.sheet_names
file_bytes.seek(0)
df = pd.read_excel(file_bytes, sheet_name=sheets[0])
return df, sheets, None
except Exception as e:
return None, [], str(e)
def apply_filters(df: pd.DataFrame, pattern: Optional[str] = None, regex_column: Optional[str] = None, numeric_filter: Optional[Dict[str, Any]] = None, selected_columns: Optional[List[str]] = None) -> tuple:
start_time = time.time()
input_rows = len(df)
input_columns = len(df.columns)
filtered_df = df.copy()
filters_applied = []
if pattern and pattern.strip():
try:
columns_to_search = [regex_column] if regex_column and regex_column != "Alle Spalten" else df.columns.tolist()
regex = re.compile(pattern, re.IGNORECASE)
mask = filtered_df.apply(lambda row: any(regex.search(str(row[col])) for col in columns_to_search if col in row and pd.notna(row[col])), axis=1)
filtered_df = filtered_df[mask]
filters_applied.append("Regex")
except re.error as e:
return None, None, f"Ungültiges Regex-Muster: {e}"
if numeric_filter and numeric_filter.get("column"):
try:
column = numeric_filter["column"]
operator = numeric_filter["operator"]
value = numeric_filter["value"]
if column == "Alle Spalten":
combined_mask = pd.Series([False] * len(filtered_df), index=filtered_df.index)
for col in filtered_df.columns:
num_series = pd.to_numeric(filtered_df[col], errors='coerce')
col_mask = eval(f"num_series {operator} value")
combined_mask = combined_mask | col_mask
filtered_df = filtered_df[combined_mask]
else:
num_series = pd.to_numeric(filtered_df[column], errors='coerce')
filtered_df = filtered_df[eval(f"num_series {operator} value")]
filters_applied.append("Numerisch")
except Exception as e:
return None, None, f"Fehler beim Anwenden des numerischen Filters: {e}"
if selected_columns:
available_columns = [col for col in selected_columns if col in filtered_df.columns]
if available_columns:
filtered_df = filtered_df[available_columns]
end_time = time.time()
stats = {
"input_rows": input_rows,
"input_columns": input_columns,
"output_rows": len(filtered_df),
"output_columns": len(filtered_df.columns),
"rows_removed": input_rows - len(filtered_df),
"processing_time": end_time - start_time,
"filters_applied": filters_applied,
"retention_rate": (len(filtered_df) / input_rows * 100) if input_rows > 0 else 0
}
return filtered_df, stats, None
def explain_regex_german(blocks: List[Dict]) -> str:
"""Übersetzt die Regex-Bausteine in einen deutschen Satz."""
if not blocks:
return "Muster ist leer."
explanations = []
for block in blocks:
b_type = block["key"]
val = block.get("value", "")
q_key = block.get("quantifier_key", "Genau 1 (Standard)")
# 1. Grundbegriff
if "Exakter Text" in b_type: noun = f"den exakten Text '{val}'"
elif "Ziffer" in b_type: noun = "eine Ziffer (0-9)"
elif "Buchstabe" in b_type: noun = "einen Buchstaben (A-Z oder a-z)"
elif "Leerzeichen" in b_type: noun = "ein Leerzeichen"
elif "Beliebiges einzelnes Zeichen" in b_type: noun = "ein beliebiges einzelnes Zeichen"
elif "Beliebige Zeichenfolge" in b_type: noun = "eine beliebige Zeichenfolge"
elif "ODER" in b_type: noun = "ODER"
elif "Zeilenanfang" in b_type: noun = "den Anfang der Zeichenkette"
elif "Zeilenende" in b_type: noun = "das Ende der Zeichenkette"
else: noun = "ein Element"
# 2. Quantoren anwenden
if noun not in ["ODER", "den Anfang der Zeichenkette", "das Ende der Zeichenkette", "eine beliebige Zeichenfolge"]:
if "1 oder mehr" in q_key:
noun = f"eine oder mehr {noun.replace('eine ', '').replace('einen ', '').replace('ein ', '').replace('den ', '').replace('das ', '')}en" if any(noun.startswith(x) for x in ["eine ", "einen ", "ein ", "den ", "das "]) else f"ein oder mehr {noun}"
elif "0 oder mehr" in q_key:
noun = f"null oder mehr {noun.replace('eine ', '').replace('einen ', '').replace('ein ', '').replace('den ', '').replace('das ', '')}en" if any(noun.startswith(x) for x in ["eine ", "einen ", "ein ", "den ", "das "]) else f"null oder mehr {noun}"
elif "Optional" in q_key:
noun = f"ein optionales {noun.replace('eine ', '').replace('einen ', '').replace('ein ', '').replace('den ', '').replace('das ', '')}" if any(noun.startswith(x) for x in ["eine ", "einen ", "ein ", "den ", "das "]) else f"ein optionales {noun}"
explanations.append(noun)
# 3. Zusammenfügen
sentence = ""
for i, exp in enumerate(explanations):
if i == 0:
sentence += exp
else:
if exp == "ODER" or explanations[i-1] == "ODER":
sentence += f" {exp} "
else:
sentence += f", gefolgt von {exp}"
return sentence[:1].upper() + sentence[1:] + "."
def apply_sleek_dark_theme():
st.markdown("""
<style>
h1, h2, h3 { font-weight: 500 !important; letter-spacing: -0.5px; }
.stApp { background-color: #0F1115; color: #FAFAFA; }
.stTextInput>div>div>input,
.stSelectbox>div>div>div,
.stNumberInput>div>div>input,
.stTextArea>div>div>textarea {
background-color: #1E2028 !important;
border: 1px solid #2D3342 !important;
color: #FAFAFA !important;
border-radius: 6px !important;
padding: 8px 12px !important;
}
.section-header {
font-size: 1.4rem;
font-weight: 600;
color: #FFFFFF;
margin-top: 2.5rem;
margin-bottom: 1.5rem;
padding-bottom: 0.5rem;
border-bottom: 1px solid #2D3342;
}
.success-box {
background-color: #1A3B2B;
color: #4ADE80;
padding: 1rem 1.25rem;
border-radius: 6px;
font-size: 0.95rem;
margin-bottom: 1.5rem;
border: 1px solid #224D38;
}
.info-box {
background-color: #1a233a;
color: #8fa1c4;
padding: 0.75rem 1rem;
border-radius: 6px;
font-size: 0.9rem;
margin-bottom: 1rem;
border: 1px solid #2d3748;
}
.translation-box {
background-color: #2D241E;
color: #E29A5B;
padding: 1rem;
border-radius: 6px;
font-size: 1rem;
margin-bottom: 1.5rem;
border: 1px solid #5C3D22;
line-height: 1.5;
}
.block-brick {
background-color: #1E2028;
border: 1px solid #3B4252;
border-left: 4px solid #F03E3E;
color: #FAFAFA;
padding: 0.75rem 1rem;
border-radius: 4px;
font-size: 0.95rem;
margin-bottom: 0.5rem;
display: flex;
align-items: center;
}
[data-testid="stSidebar"] {
background-color: #161A23 !important;
border-right: 1px solid #2D3342;
}
hr { border-color: #2D3342 !important; }
[data-testid="stMetric"] {
background-color: transparent !important;
border: none !important;
padding: 0 !important;
}
[data-testid="stMetricValue"] { color: #FFFFFF !important; font-size: 1.8rem !important; }
.stTabs [data-baseweb="tab-list"] { gap: 24px; background-color: transparent; }
.stTabs [data-baseweb="tab"] { color: #A0AEC0; padding-top: 10px; padding-bottom: 10px; }
.stTabs [aria-selected="true"] { color: #FFFFFF !important; }
</style>
""", unsafe_allow_html=True)
def render_pipeline_tab():
st.markdown('<div class="section-header">Schritt 1: Datei auswählen</div>', unsafe_allow_html=True)
uploaded_file = st.file_uploader("Lade eine Excel-Datei hoch (.xlsx, .xls)", type=["xlsx", "xls"], label_visibility="collapsed")
if uploaded_file:
if uploaded_file != st.session_state.get("last_uploaded"):
st.session_state.last_uploaded = uploaded_file
with st.spinner("Lade..."):
df, sheets, error = load_excel_file(uploaded_file)
if error:
st.error(f"Fehler: {error}")
else:
st.session_state.df = df
st.session_state.sheets = sheets
st.session_state.selected_sheet = sheets[0]
st.session_state.columns = df.columns.tolist()
st.session_state.filtered_df = None
st.session_state.stats = None
st.session_state.selected_columns = list(df.columns)
st.markdown(f'<div class="success-box">Datei geladen: {uploaded_file.name}</div>', unsafe_allow_html=True)
col1, _ = st.columns([1, 2])
with col1:
current_idx = st.session_state.sheets.index(st.session_state.selected_sheet) if st.session_state.selected_sheet in st.session_state.sheets else 0
selected_sheet = st.selectbox("Arbeitsblatt auswählen", st.session_state.sheets, index=current_idx)
if selected_sheet != st.session_state.selected_sheet:
st.session_state.selected_sheet = selected_sheet
st.session_state.df = pd.read_excel(BytesIO(st.session_state.last_uploaded.getvalue()), sheet_name=selected_sheet)
st.session_state.columns = st.session_state.df.columns.tolist()
st.session_state.selected_columns = list(st.session_state.df.columns)
st.rerun()
if st.session_state.df is not None:
st.markdown('<div class="section-header">Schritt 2: Filter konfigurieren</div>', unsafe_allow_html=True)
filter_tabs = st.tabs(["Regex-Filter", "Numerischer Filter", "Spaltenauswahl"])
with filter_tabs[0]:
st.write("")
st.session_state.regex_enabled = st.checkbox("Regex-Filter aktivieren", value=st.session_state.regex_enabled)
if st.session_state.regex_enabled:
col1, col2 = st.columns([2, 1])
with col1:
presets = get_pattern_presets()
preset_names = ["-- Vorlagen --"] + list(presets.keys())
def on_preset_change():
sel = st.session_state.preset_selector
if sel != preset_names[0] and sel in presets:
st.session_state.regex_pattern = presets[sel]
st.selectbox("Vorlage laden", preset_names, key="preset_selector", on_change=on_preset_change)
st.session_state.regex_pattern = st.text_input("Aktives Regex-Muster (Nutze den 'Regex-Builder' zum visuellen Erstellen)", value=st.session_state.regex_pattern, placeholder="z.B. ^Fehler.*")
with col2:
regex_column = st.selectbox("Spalte für Regex-Filter", ["Alle Spalten"] + st.session_state.columns)
with filter_tabs[1]:
st.write("")
st.session_state.numeric_enabled = st.checkbox("Numerischen Filter aktivieren", value=st.session_state.numeric_enabled)
if st.session_state.numeric_enabled:
col1, col2, col3 = st.columns([2, 2, 1])
with col1:
numeric_column = st.selectbox("Spalte", ["Alle Spalten"] + st.session_state.columns)
with col2:
ops = {">": ">", "<": "<", ">=": ">=", "<=": "<=", "=": "="}
selected_op = st.selectbox("Vergleichsoperator", list(ops.values()))
numeric_operator = [k for k, v in ops.items() if v == selected_op][0]
with col3:
numeric_value = st.text_input("Wert")
with filter_tabs[2]:
st.write("")
st.session_state.column_selection_enabled = st.checkbox("Spaltenauswahl aktivieren", value=st.session_state.column_selection_enabled)
if st.session_state.column_selection_enabled:
col_btn1, col_btn2, _ = st.columns([1, 1, 3])
with col_btn1:
if st.button("Alle auswählen", use_container_width=True):
st.session_state.selected_columns = list(st.session_state.columns)
st.rerun()
with col_btn2:
if st.button("Alle abwählen", use_container_width=True):
st.session_state.selected_columns = []
st.rerun()
st.session_state.selected_columns = st.multiselect("Spalten auswählen", st.session_state.columns, default=st.session_state.get("selected_columns", st.session_state.columns))
st.markdown('<div class="section-header">Schritt 3: Ergebnisse & Export</div>', unsafe_allow_html=True)
if st.button("Filter anwenden", type="primary"):
val_error = None
if st.session_state.regex_enabled and not st.session_state.regex_pattern: val_error = "Bitte gib ein Regex-Muster ein"
if st.session_state.numeric_enabled and not numeric_value: val_error = "Bitte gib einen numerischen Wert ein"
if val_error:
st.error(val_error)
else:
num_dict = {"column": numeric_column, "operator": numeric_operator, "value": float(numeric_value)} if (st.session_state.numeric_enabled and numeric_value) else None
cols = st.session_state.selected_columns if st.session_state.column_selection_enabled else None
with st.spinner("Verarbeite..."):
filtered_df, stats, err = apply_filters(st.session_state.df, pattern=st.session_state.regex_pattern if st.session_state.regex_enabled else None, regex_column=regex_column if st.session_state.regex_enabled else None, numeric_filter=num_dict, selected_columns=cols)
if err:
st.error(f"Fehler: {err}")
else:
st.session_state.filtered_df = filtered_df
st.session_state.stats = stats
st.success("Filter erfolgreich angewendet.")
if st.session_state.filtered_df is not None and st.session_state.stats is not None:
st.divider()
sc1, sc2, sc3, sc4 = st.columns(4)
sc1.metric("Eingabezeilen", f"{st.session_state.stats['input_rows']:,}")
sc2.metric("Ausgabezeilen", f"{st.session_state.stats['output_rows']:,}")
sc3.metric("Entfernte Zeilen", f"{st.session_state.stats['rows_removed']:,}")
sc4.metric("Trefferquote", f"{st.session_state.stats['retention_rate']:.1f}%")
st.write("")
st.dataframe(st.session_state.filtered_df.head(100), use_container_width=True, height=300)
st.caption(f"Zeige {min(100, len(st.session_state.filtered_df))} von {len(st.session_state.filtered_df)} Zeilen")
out_buf = BytesIO()
with pd.ExcelWriter(out_buf, engine='openpyxl') as writer:
st.session_state.filtered_df.to_excel(writer, index=False)
out_buf.seek(0)
st.download_button("Gefilterte Datei herunterladen", out_buf, "gefilterte_ausgabe.xlsx", "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", type="primary")
def render_regex_builder_tab():
st.markdown('<div class="section-header">Visueller Regex-Builder</div>', unsafe_allow_html=True)
st.markdown("Erstelle Suchmuster durch Kombinieren von modularen Bausteinen. Das Muster wird von oben nach unten aufgebaut.")
st.write("")
col_build, col_test = st.columns([1.2, 1])
with col_build:
st.markdown("### 1. Bausteine hinzufügen")
selected_block_key = st.selectbox("Wähle einen Bausteintyp:", list(REGEX_BRICKS.keys()))
block_data = REGEX_BRICKS[selected_block_key]
st.markdown(f'<div class="info-box"><b>Beschreibung:</b> {block_data["desc"]}</div>', unsafe_allow_html=True)
col1, col2 = st.columns(2)
with col1:
if block_data["needs_input"]:
st.text_input("Text zum Suchen:", placeholder="z.B. Fehler", key="temp_block_val")
else:
st.session_state.temp_block_val = ""
with col2:
if block_data["allows_quantifier"]:
st.selectbox("Wie oft:", list(QUANTIFIERS.keys()), key="temp_quantifier")
else:
st.session_state.temp_quantifier = "Genau 1 (Standard)"
def add_block_callback():
st.session_state.regex_blocks.append({
"key": selected_block_key,
"value": st.session_state.temp_block_val if block_data["needs_input"] else "",
"regex_format": block_data["regex"],
"quantifier_key": st.session_state.temp_quantifier if block_data["allows_quantifier"] else "Genau 1 (Standard)"
})
st.session_state.temp_block_val = ""
st.session_state.temp_quantifier = "Genau 1 (Standard)"
st.button("Baustein hinzufügen", use_container_width=True, on_click=add_block_callback)
st.write("---")
st.markdown("### 2. Bausteine als Reihe")
if not st.session_state.regex_blocks:
st.info("Die Bausteinreihe ist leer. Wähle oben einen Baustein und klicke auf Hinzufügen.")
else:
for i, block in enumerate(st.session_state.regex_blocks):
c1, c2 = st.columns([5, 1])
with c1:
val_display = f" <code style='color:#F03E3E; background:transparent;'>{block['value']}</code>" if block['value'] else ""
q_key = block.get('quantifier_key', 'Genau 1 (Standard)')
q_display = f" &nbsp; <span style='color:#8fa1c4; font-size: 0.8em;'>[ <i>{q_key}</i> ]</span>" if q_key != "Genau 1 (Standard)" else ""
st.markdown(f'<div class="block-brick">{block["key"]}{val_display}{q_display}</div>', unsafe_allow_html=True)
with c2:
if st.button("Entfernen", key=f"del_block_{i}", help="Diesen Baustein entfernen"):
st.session_state.regex_blocks.pop(i)
st.rerun()
# Kompiliere die visuellen Bausteine zu echtem Regex-Code
regex_parts = []
for block in st.session_state.regex_blocks:
q_val = QUANTIFIERS[block.get("quantifier_key", "Genau 1 (Standard)")]
if block["value"]:
safe_val = re.escape(block["value"])
if q_val:
regex_parts.append(f"(?:{safe_val}){q_val}")
else:
regex_parts.append(safe_val)
else:
regex_parts.append(f"{block['regex_format']}{q_val}")
generated_regex = "".join(regex_parts)
with col_test:
st.markdown("### 3. Muster testen")
st.markdown("**Muster-Erklärung:**")
german_translation = explain_regex_german(st.session_state.regex_blocks)
st.markdown(f'<div class="translation-box">"{german_translation}"</div>', unsafe_allow_html=True)
st.markdown("**Generiertes Regex:**")
st.code(generated_regex if generated_regex else "(leer)", language="regex")
test_text = st.text_input("Testtext", value=st.session_state.regex_test_text, placeholder="Gib einen Beispieltext ein...")
st.session_state.regex_test_text = test_text
test_btn = st.button("Muster testen", use_container_width=True)
if (test_btn or test_text) and generated_regex and test_text:
try:
regex = re.compile(generated_regex, re.IGNORECASE)
matches = regex.findall(test_text)
if matches:
st.success(f"{len(matches)} Treffer gefunden.")
highlighted = test_text
for match in set(matches):
if match:
highlighted = highlighted.replace(match, f"**{match}**")
st.markdown(f"> {highlighted}")
else:
st.warning("Keine Treffer gefunden. Passe dein Muster oder den Testtext an.")
except re.error:
st.error("Ungültige Mustersyntax. Vervollständige die Musterfolge.")
st.write("")
if st.button("Auf Excel-Pipeline anwenden", type="primary", use_container_width=True):
if generated_regex:
st.session_state.regex_pattern = generated_regex
st.success("Muster angewendet. Wechsle zum Tab 'Excel-Filter' um deine Daten zu filtern.")
else:
st.error("Kann kein leeres Muster anwenden.")
def render_help_tab():
st.markdown('<div class="section-header">Hilfe</div>', unsafe_allow_html=True)
st.markdown("""
### Tab: Excel-Pipeline
**Schritt 1: Datei auswählen**
- Lade Excel-Dateien im Format `.xlsx` oder `.xls` hoch
- Wähle das zu verarbeitende Arbeitsblatt, falls die Datei mehrere enthält
**Schritt 2: Filter konfigurieren**
*Regex-Filter:*
- Gib ein reguläres Ausdrucksmuster manuell ein oder nutze den visuellen Regex-Builder
- Wähle eine bestimmte Spalte oder durchsuche alle Spalten
- Mustersuche ist standardmäßig Groß-/Kleinschreibung unabhängig
*Numerischer Filter:*
- Filtere Zeilen basierend auf numerischen Vergleichen (>, <, >=, <=, =)
- Wende auf eine bestimmte Spalte oder alle (numerischen) Spalten an
*Spaltenauswahl:*
- Wähle, welche Spalten in der Ausgabe enthalten sein sollen
- Nutze "Alle auswählen" / "Alle abwählen" für schnelle Auswahl
**Schritt 3: Ergebnisse & Export**
- Überprüfe die Filterstatistiken (beibehaltene Zeilen, entfernte Zeilen, Trefferquote)
- Zeige die gefilterten Daten an (erste 100 Zeilen)
- Lade den gefilterten Datensatz als neue Excel-Datei herunter
---
### Tab: Visueller Regex-Builder
Erstelle reguläre Ausdrücke visuell durch Kombinieren modularer Bausteine:
**Verfügbare Bausteine:**
| Baustein | Beschreibung | Regex-Äquivalent |
|----------|--------------|------------------|
| Exakter Text | Findet wörtlichen Text | `text` |
| Ziffer (0-9) | Findet eine einzelne Ziffer | `\d` |
| Buchstabe (A-Z, a-z) | Findet einen Buchstaben | `[a-zA-Z]` |
| Leerzeichen | Findet Leerzeichen, Tabs, Zeilenumbrüche | `\s` |
| Beliebiges einzelnes Zeichen | Platzhalter für ein Zeichen | `.` |
| Beliebige Zeichenfolge | Platzhalter für beliebigen Inhalt | `.*` |
| ODER (Alternative) | Findet entweder Ausdruck davor oder danach | `\|` |
| Zeilenanfang | Verankert am Anfang | `^` |
| Zeilenende | Verankert am Ende | `$` |
**Quantifizierer:**
- **Genau 1:** Findet das Element einmal (Standard)
- **1 oder mehr (+):** Findet ein oder mehr Vorkommen
- **0 oder mehr (*):** Findet null oder mehr Vorkommen
- **Optional (?):** Findet null oder ein Vorkommen
**Beispiel: Fehlercodes finden**
Um Zeilen zu finden, die mit "Fehler" beginnen, gefolgt von einem Leerzeichen und Ziffern (z.B. "Fehler 404"):
1. Füge "Zeilenanfang" hinzu - verankert am Zeilenanfang
2. Füge "Exakter Text" mit Wert "Fehler" hinzu
3. Füge "Leerzeichen" mit Quantifizierer "1 oder mehr (+)" hinzu
4. Füge "Ziffer (0-9)" mit Quantifizierer "1 oder mehr (+)" hinzu
Generiertes Muster: `^Fehler\s+\d+`
---
### Tipps für effektives Filtern
1. **Teste Muster zuerst:** Nutze die Testfunktion des Regex-Builders, bevor du ihn auf den kompletten Datensatz anwendest
2. **Kombiniere Filter sorgfältig:** Mehrere Filter können gleichzeitig aktiviert werden; sie arbeiten nacheinander
3. **Spaltenauswahl reduziert Dateigröße:** Exportiere nur benötigte Spalten um Ergebnisse zu straffen
4. **Groß-/Kleinschreibung:** Alle Regex-Muster ignorieren standardmäßig Groß-/Kleinschreibung
5. **Sonderzeichen in exaktem Text:** Der Builder maskiert spezielle Regex-Zeichen automatisch
---
""")
def main():
init_session_state()
apply_sleek_dark_theme()
with st.sidebar:
st.markdown("### Datenübersicht")
if st.session_state.df is not None:
# Dateiinformationen
st.markdown("**Infos**")
st.caption(f"Aktives Blatt: {st.session_state.selected_sheet}")
st.divider()
# Zeilenstatistik
st.markdown("**Statistik**")
st.metric("Alle Zeilen", f"{len(st.session_state.df):,}")
st.metric("Alle Spalten", f"{len(st.session_state.df.columns):,}")
st.divider()
# Datentypen-Zusammenfassung
st.markdown("**Spaltentypen**")
dtype_counts = st.session_state.df.dtypes.value_counts()
for dtype, count in dtype_counts.items():
st.caption(f"{dtype}: {count} Spalte(n)")
st.divider()
# Filterstatus
if st.session_state.stats is not None:
st.markdown("**Filterergebnisse**")
st.metric("Ausgabezeilen", f"{st.session_state.stats['output_rows']:,}")
st.metric("Trefferquote", f"{st.session_state.stats['retention_rate']:.1f}%")
if st.session_state.stats['filters_applied']:
st.caption(f"Filter: {', '.join(st.session_state.stats['filters_applied'])}")
st.divider()
# Speicherverbrauch
memory_mb = st.session_state.df.memory_usage(deep=True).sum() / 1024 / 1024
st.caption(f"Speicher: {memory_mb:.1f} MB")
st.caption("*Version 0.1* ")
else:
st.info("Lade eine Excel-Datei hoch, um Statistiken anzuzeigen.")
st.divider()
st.markdown("**Anleitung**")
st.markdown("""
1. Excel-Datei hochladen
2. Filter konfigurieren (optional)
3. "Filter anwenden" klicken
4. Ergebnisse herunterladen
""")
st.title("Excel Filter Tool")
st.markdown("*Temporäre Session: Es werden keine Daten und Einstellungen gespeichert!* ")
st.write("")
main_tabs = st.tabs(["Excel-Filter", "Regex-Builder", "Hilfe"])
with main_tabs[0]: render_pipeline_tab()
with main_tabs[1]: render_regex_builder_tab()
with main_tabs[2]: render_help_tab()
if __name__ == "__main__":
main()