### Combined Pulse SDK Installations

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Provides examples of installing multiple feature sets of the Pulse SDK together, such as for a data science workflow, a complete NLP pipeline, or a development setup.

```bash
# Data science workflow
pip install pulse-sdk[analysis,visualization,caching]

# Complete NLP pipeline
pip install pulse-sdk[analysis,nlp,progress]

# Development setup
pip install pulse-sdk[all,dev]
```

--------------------------------

### Test Pulse SDK Installation

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Verify the Pulse SDK installation by importing the CoreClient and printing a success message.

```python
from pulse.core.client import CoreClient

# Quick test
client = CoreClient()
print("✅ Pulse SDK installed successfully!")
```

--------------------------------

### Pulse SDK Installation Commands by Use Case

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Provides multiple pip installation commands for different use cases including complete installation, minimal API access, data science workflows, web service integration, and development environments. Each installs specific optional dependency sets.

```bash
# Complete experience (recommended)
pip install pulse-sdk[all]

# Minimal API access only
pip install pulse-sdk[minimal]

# Data science workflow
pip install pulse-sdk[analysis,visualization,caching]

# Web service integration
pip install pulse-sdk[minimal,progress]

# Development and testing
pip install pulse-sdk[dev]
```

--------------------------------

### Beginner Example: Analyze Reviews with Sentiment and Themes

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

A beginner-friendly example demonstrating how to perform sentiment analysis and theme allocation on a list of customer reviews using Pulse SDK starter functions.

```python
from pulse.starters import sentiment_analysis, theme_allocation

# Load reviews from a file (CSV, TXT, Excel supported)
reviews = [
    "Food was great, service was slow",
    "Amazing pizza, will come back",
    "Too expensive for the quality"
]

# Analyze sentiment
sentiment_results = sentiment_analysis(reviews)

# Find themes
themes = theme_allocation(reviews, themes=["Food", "Service", "Price"])

# Print results
for i, review in enumerate(reviews):
    print(f"Review: {review}")
    print(f"Sentiment: {sentiment_results.results[i].sentiment}")
    print(f"Themes: {themes.assign_single()[i]}")
    print("---")
```

--------------------------------

### Install Pulse SDK using Pip

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Install the Pulse SDK using pip. Options include recommended (all features), minimal (API access only), custom (specific features), and development (for contributors).

```bash
pip install pulse-sdk[all]
```

```bash
pip install pulse-sdk[minimal]
```

```bash
# Data science workflow
pip install pulse-sdk[analysis,visualization,caching]

# Basic API with progress tracking
pip install pulse-sdk[minimal,progress]
```

```bash
git clone https://github.com/researchwiseai/pulse-py.git
cd pulse-py
pip install -e ".[dev]"
```

--------------------------------

### Create Minimal Reproduction for Issue Reporting

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/dependency-troubleshooting.md

Steps to create a minimal, reproducible example of an installation issue. This involves setting up a fresh environment and capturing installation logs.

```bash
# Fresh environment
python -m venv test_env
source test_env/bin/activate
pip install --upgrade pip

# Try installation
pip install pulse-sdk[all] > install_log.txt 2>&1
```

--------------------------------

### Advanced Example: Complete Analysis Pipeline with Analyzer

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

An advanced example showcasing a complete analysis pipeline using the Analyzer class, including theme generation and sentiment analysis processes, with caching enabled.

```python
from pulse.analysis.analyzer import Analyzer
from pulse.analysis.processes import ThemeGeneration, SentimentProcess

# Your dataset
reviews = [
    "The food was excellent but service was slow",
    "Great atmosphere, terrible food",
    "Perfect experience, will recommend"
]

# Build analysis pipeline
processes = [
    ThemeGeneration(min_themes=3, max_themes=5),
    SentimentProcess()
]

# Run analysis with caching
with Analyzer(dataset=reviews, processes=processes, cache_dir=".pulse_cache") as analyzer:
    results = analyzer.run()

# Access results
print("Generated Themes:")
for theme in results.theme_generation.themes:
    print(f"- {theme}")

print("\nSentiment Analysis:")
df = results.sentiment.to_dataframe()
print(df[['text', 'sentiment', 'confidence']])
```

--------------------------------

### Install Pulse SDK with Bash

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Provides the command to install the Pulse SDK using pip. This command is essential for setting up the library in your Python environment.

```bash
pip install pulse-sdk
```

--------------------------------

### Pulse SDK Minimal Core Example Usage (Python)

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Demonstrates how to use the `CoreClient` from the minimal installation of the Pulse SDK to perform basic API calls like sentiment analysis.

```python
from pulse.core.client import CoreClient

client = CoreClient()
result = client.analyze_sentiment(["Hello world"])
print(result.results[0].sentiment)
```

--------------------------------

### Pulse SDK Caching Example Usage (Python)

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Demonstrates the use of the `Analyzer` with a specified cache directory, showing how results are automatically cached to disk for future runs.

```python
from pulse.analysis.analyzer import Analyzer

# Results are automatically cached to disk
with Analyzer(cache_dir=".pulse_cache") as analyzer:
    results = analyzer.run()  # Cached for future runs
```

--------------------------------

### Set Up a Fresh Virtual Environment for Pulse SDK

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Create and activate a new virtual environment to avoid dependency conflicts when installing the Pulse SDK. This is a standard practice for managing Python project dependencies.

```bash
python -m venv fresh_env
source fresh_env/bin/activate
pip install pulse-sdk
```

--------------------------------

### Install Pulse SDK for Development

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with all development, testing, formatting, and documentation tools, intended for contributors and advanced users.

```bash
pip install pulse-sdk[dev]
```

--------------------------------

### Install Pulse SDK

Source: https://github.com/researchwiseai/pulse-py/blob/main/examples/async_api.ipynb

Installs the Pulse SDK using pip. Ensure you have pip installed and accessible in your environment.

```python
# Install the Pulse SDK if not already installed
!pip install pulse-sdk
```

--------------------------------

### Upgrade Pip

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Upgrade the pip package installer to the latest version to ensure compatibility and resolve potential issues with dependency resolution.

```bash
pip install --upgrade pip
```

--------------------------------

### Install Pulse SDK with Progress Tracking

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with progress tracking features, adding libraries like `tqdm` to provide visual feedback on the progress of long-running operations.

```bash
pip install pulse-sdk[progress]
```

--------------------------------

### Activate Virtual Environment with Bash

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Shows how to activate a Python virtual environment on Linux/Mac systems. This is a common step before installing or running Python projects to manage dependencies.

```bash
source venv/bin/activate  # Linux/Mac
```

--------------------------------

### Pulse SDK Installation for Web Developers

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs a lightweight version of the Pulse SDK suitable for web services, including minimal core features and progress tracking for API operations.

```bash
# Lightweight for web services
pip install pulse-sdk[minimal,progress]
```

--------------------------------

### Pulse SDK Analysis Features Example Usage (Python)

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Shows how to utilize the `Analyzer` and `ThemeGeneration` classes from the analysis features of the Pulse SDK, including converting results to a pandas DataFrame.

```python
from pulse.analysis.analyzer import Analyzer
from pulse.analysis.processes import ThemeGeneration

analyzer = Analyzer(dataset=texts, processes=[ThemeGeneration()])
results = analyzer.run()
df = results.theme_generation.to_dataframe()  # Requires pandas
```

--------------------------------

### Install Pulse SDK with Visualization Features

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with libraries for plotting and chart generation, enabling the creation of visualizations from analysis results.

```bash
pip install pulse-sdk[visualization]
```

--------------------------------

### Pulse SDK Installation for Production Deployments

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs an optimized version of the Pulse SDK for production environments, focusing on analysis features and caching for improved performance and reliability.

```bash
# Optimized for production with caching
pip install pulse-sdk[analysis,caching]
```

--------------------------------

### Pulse SDK Installation for Content Analysis and NLP

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with features for comprehensive text processing, including analysis, NLP utilities, and visualization capabilities.

```bash
# Full text processing capabilities
pip install pulse-sdk[analysis,nlp,visualization]
```

--------------------------------

### Setup Virtual Environment and Install Dependencies

Source: https://github.com/researchwiseai/pulse-py/blob/main/README.md

Initialize a Python 3.8+ virtual environment and install the Pulse SDK with development tools. Creates an isolated environment and installs the package in editable mode with optional pre-commit hooks for code quality checks.

```bash
python -m venv venv
source venv/bin/activate   # Windows: venv\\Scripts\\activate
pip install -e ".[dev]"
pre-commit install
pre-commit install --hook-type commit-msg
```

--------------------------------

### Install Pulse SDK with uv

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with all features using uv, a fast Python package installer and resolver. uv aims to provide a quicker alternative to pip.

```bash
uv pip install pulse-sdk[all]
```

--------------------------------

### Pulse SDK Installation for Data Scientists

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs a comprehensive stack for data scientists, including analysis, visualization, caching, and progress tracking features for robust data workflows.

```bash
# Complete data science stack
pip install pulse-sdk[analysis,visualization,caching,progress]
```

--------------------------------

### Troubleshoot Dependency Conflicts: Minimal Installation

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs a minimal version of the Pulse SDK first, then adds desired features incrementally. This method is useful when facing extensive dependency issues or to reduce initial installation size.

```bash
# Install minimal version first
pip install pulse-sdk[minimal]

# Add features incrementally
pip install pulse-sdk[analysis]
pip install pulse-sdk[visualization]
```

--------------------------------

### Minimal First Pulse SDK Installation Strategy

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/dependency-troubleshooting.md

Installs the Pulse SDK with minimal features first, then incrementally adds features and tests each addition. Suitable for cautious installations.

```bash
# 1. Install minimal version
pip install pulse-sdk[minimal]

# 2. Test core functionality
python -c "from pulse.core.client import CoreClient; print('Core OK')"

# 3. Add features incrementally
pip install pulse-sdk[analysis]
pip install pulse-sdk[visualization]

# 4. Test each addition
python -c "import numpy, pandas; print('Analysis OK')"
```

--------------------------------

### Local Development Setup

Source: https://github.com/researchwiseai/pulse-py/blob/main/README.md

Installs development dependencies and sets up pre-commit hooks for local development. Requires Python 3.8+ and involves creating a virtual environment, activating it, and installing the project with dev dependencies.

```bash
python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -e .[dev]
pre-commit install
pre-commit install --hook-type commit-msg
```

--------------------------------

### Install Pulse SDK with Caching Features

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with caching capabilities, including libraries for on-disk caching to improve performance on repeated analyses, especially with large datasets.

```bash
pip install pulse-sdk[caching]
```

--------------------------------

### Install Pulse SDK with Pipenv

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with all features using pipenv, a dependency management tool for Python. Pipenv manages project dependencies and virtual environments.

```bash
pipenv install pulse-sdk[all]
```

--------------------------------

### Verify Pulse SDK Installation: Basic Import

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Performs a basic check to verify that the Pulse SDK can be imported successfully and prints its version. This is the first step in confirming a correct installation.

```python
try:
    import pulse
    print("✅ Pulse SDK imported successfully")
    print(f"Version: {pulse.__version__}")
except ImportError as e:
    print(f"❌ Import failed: {e}")
```

--------------------------------

### Install Pulse SDK with NLP Features

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with advanced natural language processing utilities, adding libraries for text preprocessing and linguistic feature extraction.

```bash
pip install pulse-sdk[nlp]
```

--------------------------------

### Gather Diagnostic Information for Troubleshooting

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

A set of bash commands to gather essential diagnostic information for troubleshooting installation or connection issues. This includes Python and pip versions, and a list of installed 'pulse' packages.

```bash
python --version
pip --version
pip list | grep pulse
```

--------------------------------

### Install Pulse SDK with Analysis Features

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Installs the Pulse SDK with added data science and machine learning capabilities, including libraries for numerical computing, data manipulation, and machine learning utilities.

```bash
pip install pulse-sdk[analysis]
```

--------------------------------

### Summarize Text with Pulse SDK

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Summarize a list of texts using the summarize starter function. It can take an optional question to guide the summarization.

```python
from pulse.starters import summarize

# Summarize customer feedback
feedback = [
    "Great food but slow service",
    "Amazing pizza, friendly staff",
    "Food was cold, waited too long"
]

summary = summarize(feedback, question="What do customers say about the restaurant?")
print("Summary:", summary.summary)
```

--------------------------------

### Document Summarization with Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Summarizes a list of meeting notes using the `summarize` function from `pulse.starters`. It allows specifying a question to guide the summary and the desired length.

```python
from pulse.starters import summarize

# Summarize meeting notes
meeting_notes = [
    "Discussed Q4 budget allocation for marketing",
    "Decided to hire two new developers",
    "Marketing campaign launch delayed to January",
    "Need to review vendor contracts by month end"
]

# Generate summary
summary = summarize(
    meeting_notes,
    question="What were the key decisions and action items?",
    length="short"
)

print("Meeting Summary:")
print(summary.summary)
```

--------------------------------

### Incremental Pulse SDK Installation

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/dependency-troubleshooting.md

A strategy for resolving complex dependency issues by installing the Pulse SDK incrementally. Start with the minimal installation, test core functionality, and then add feature sets one by one to identify potential conflicts.

```bash
# Start with minimal
pip install pulse-sdk[minimal]

# Test basic functionality
python -c "from pulse.core.client import CoreClient; print('✅ Core works')"

# Add features one by one
pip install pulse-sdk[analysis]
pip install pulse-sdk[visualization]
pip install pulse-sdk[caching]
```

--------------------------------

### Process Results in Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Iterates through a list of results, printing the sentiment and confidence score for each. This is a basic example of accessing and displaying analysis outcomes.

```python
for result in results.results:
    print(f"Sentiment: {result.sentiment} (confidence: {result.confidence:.2f})")
```

--------------------------------

### Pulse SDK Visualization Example Usage (Python)

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Illustrates how to plot the distribution of sentiment analysis results using a method that requires matplotlib and seaborn, typically available with the visualization features.

```python
from pulse.analysis.results import SentimentResults

results = SentimentResults(...)
results.plot_distribution()  # Requires matplotlib/seaborn
```

--------------------------------

### Install pulse-sdk with all features

Source: https://github.com/researchwiseai/pulse-py/blob/main/README.md

Installs the pulse-sdk package including all available features, recommended for most users. This command uses pip to fetch and install the package from the Python Package Index.

```bash
pip install pulse-sdk[all]
```

--------------------------------

### Check for Dependency Conflicts with Pip

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Use the `pip check` command to identify and diagnose any dependency conflicts within your current Python environment. This helps resolve installation issues.

```bash
pip check
```

--------------------------------

### Troubleshoot Platform Issues: Linux System Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Guides users on installing the Pulse SDK on Linux systems using system Python. It includes instructions for installing necessary development headers (python3-dev or python3-devel) which are often required for package compilation.

```bash
# Install development headers if needed
sudo apt-get install python3-dev  # Ubuntu/Debian
# or
sudo yum install python3-devel    # CentOS/RHEL

pip install pulse-sdk[all]
```

--------------------------------

### CoreClient with Environment Variable Authentication

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Initializes CoreClient that automatically loads API credentials from environment variables for secure production deployment.

```python
from pulse.core.client import CoreClient

# Automatically uses environment variables
client = CoreClient()
```

--------------------------------

### Create and Activate Fresh Python Environment

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/dependency-troubleshooting.md

Sets up a new, isolated Python environment to avoid dependency conflicts. This is a reliable method for starting with a clean slate and installing the Pulse SDK and its dependencies without interference from existing packages.

```bash
python -m venv fresh_env
source fresh_env/bin/activate
```

--------------------------------

### Install Pulse SDK with uv Package Manager

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/version-compatibility.md

Install Pulse SDK using the uv package manager, which offers faster installation than pip. Includes setup of a virtual environment and installation of all extras.

```bash
uv pip install pulse-sdk[all]
uv venv
source .venv/bin/activate
uv pip install pulse-sdk[all]
```

--------------------------------

### Create Minimal Reproduction Case for Pulse SDK Issues

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Develop a small, self-contained code snippet that demonstrates the reported issue with the Pulse API client. This aids in debugging and reporting problems.

```python
from pulse.core.client import CoreClient

client = CoreClient()
try:
    result = client.analyze_sentiment(["test"])
    print("✅ Working!")
except Exception as e:
    print(f"❌ Error: {e}")
```

--------------------------------

### Troubleshoot Network Issues: Install with Retries

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Mitigates temporary network failures during installation by configuring pip to retry downloads a specified number of times. This increases the robustness of the installation process.

```bash
pip install --retries 5 pulse-sdk[all]
```

--------------------------------

### Load Custom Data with Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Demonstrates how to load text data from both files and lists using the `get_strings` function from the `pulse.starters` module. It shows how to check the number of loaded texts.

```python
from pulse.starters import get_strings

# Load text from various sources
texts_from_file = get_strings("reviews.txt")
texts_from_list = get_strings(["review 1", "review 2", "review 3"])

print(f"Loaded {len(texts_from_file)} texts from file")
```

--------------------------------

### Troubleshoot Permission Issues: User Installation

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Resolves permission denied errors during installation by installing packages to the user's local site-packages directory instead of the system-wide location. This avoids the need for administrator privileges.

```bash
pip install --user pulse-sdk[all]
```

--------------------------------

### CoreClient with Direct ClientCredentialsAuth Configuration

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Creates CoreClient with explicit client credentials authentication by passing ClientCredentialsAuth instance. Allows programmatic credential management without environment variables.

```python
from pulse.core.client import CoreClient
from pulse.auth import ClientCredentialsAuth

auth = ClientCredentialsAuth(
    client_id="your_client_id",
    client_secret="your_client_secret"
)
client = CoreClient(auth=auth)
```

--------------------------------

### Run Jupyter Notebook Examples

Source: https://github.com/researchwiseai/pulse-py/blob/main/README.md

Execute example Jupyter notebooks demonstrating both high-level API and DSL API usage. Notebooks are located in the examples/ directory and provide practical demonstrations of text analysis workflows.

```bash
jupyter notebook examples/high_level_api.ipynb
jupyter notebook examples/dsl_api.ipynb
```

--------------------------------

### Troubleshoot Platform Issues: Windows Microsoft Store Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Provides the correct command for installing packages on Windows when Python is installed from the Microsoft Store. It utilizes the 'py' launcher to ensure pip is correctly associated with the Python installation.

```bash
# Use py launcher
py -m pip install pulse-sdk[all]
```

--------------------------------

### Install Pulse SDK with Poetry

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/installation.md

Adds the Pulse SDK with all features to a project managed by Poetry, a dependency management and packaging tool for Python. Poetry handles dependency resolution and project metadata.

```bash
poetry add pulse-sdk[all]
```

--------------------------------

### CoreClient with Interactive PKCE Authentication

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/quickstart.md

Implements interactive browser-based authentication using Authorization Code PKCE flow. Automatically opens a browser for user login and creates authenticated CoreClient instance.

```python
from pulse.auth import AuthorizationCodePKCEAuth
from pulse.core.client import CoreClient

# Opens browser for interactive login
auth = AuthorizationCodePKCEAuth(client_id="your_client_id")
client = CoreClient(auth=auth)
```

--------------------------------

### Conda + Pip Hybrid Pulse SDK Installation Strategy

Source: https://github.com/researchwiseai/pulse-py/blob/main/docs/dependency-troubleshooting.md

Installs core scientific packages (NumPy, Pandas, etc.) using Conda and then installs the Pulse SDK using pip. Ideal for environments with existing Conda installations.

```bash
# 1. Install scientific packages with conda
conda install numpy pandas scikit-learn matplotlib seaborn

# 2. Install Pulse SDK with pip
pip install pulse-sdk[minimal]

# 3. Verify all features work
python -c "from pulse.analysis.analyzer import Analyzer; print('All features OK')"
```

--------------------------------

### Constructing the CoreClient in Python

Source: https://github.com/researchwiseai/pulse-py/blob/main/site/core-client/index.html

Demonstrates various ways to instantiate the CoreClient. You can use default settings, provide explicit base URLs and timeouts, or pass a pre-configured HTTPX client. Convenience methods for authentication (client credentials, PKCE) are also available.

```python
from pulse.core.client import CoreClient

# Default construction (uses PROD base URL, auto-authentication, gzip client)
client = CoreClient()

# With explicit base_url and timeout
client = CoreClient(base_url="https://dev.core.researchwiseai.com/pulse/v1", timeout=30.0)

# Using a pre-configured HTTPX client (you manage auth and base_url)
import httpx
client = CoreClient(client=httpx.Client(base_url="https://..."))

# Using convenience auth-aware helpers (resolves args from environment variables)
client = CoreClient.with_client_credentials()
client = CoreClient.with_pkce(code="...", code_verifier="...")
```