Skip to main content

ApparatusAI Python SDK

The ApparatusAI SDK provides an easy-to-use interface to interact with the ApparatusAI API. This SDK enables developers to fetch user information, run business forecasts, and analyze social trends using ApparatusAI's powerful machine learning models.

Features

  • Secure API Token Authentication
  • Business Forecasting
  • Social Trend Analysis
  • ⚡ Easy Integration with Python Applications

Installation

To install the SDK, run:

pip install apparatusai
Getting Started
1. Import the SDK
python
Copy
Edit
from apparatusai import ApparatusAI
2. Initialize the SDK with your API Token
python
Copy
Edit
ai = ApparatusAI("apai_your_api_token_here")
⚠️ Note: Ensure your API token starts with apai_, or an error will be raised.

3. Fetch User Info
python
Copy
Edit
try:
    user_info = ai.get_user_info()
    print("User Info:", user_info)
except Exception as error:
    print("Error fetching user info:", error)
4. Perform Business Forecasting
python
Copy
Edit
try:
    forecast_data = ai.forecast({"revenue": [10000, 12000, 15000]})
    print("Forecast Result:", forecast
::contentReference[oaicite:0]{index=0}
 

Metadata

Release files for apparatusai 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for apparatusai 1.0.0
File Size Uploaded Provenance
apparatusai-1.0.0.tar.gz 2.9 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for apparatusai 1.0.0
File Interpreter ABI Platform
apparatusai-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 5.5 kB

Release files / apparatusai-1.0.0.tar.gz

Download URL apparatusai-1.0.0.tar.gz
Size 2.9 kB
Tags Source
SHA-256 checksum
How to use checksums
f5f4eeb9fbce124a39109f962df033dd2b95b39f11bbe92083ab26eb429c5997
BLAKE2b-256 checksum
How to use checksums
8909bba8dad0e578f34921c363fe48c199445be5549702332bc9a990fd7252dd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.3

Release files / apparatusai-1.0.0-py3-none-any.whl

Download URL apparatusai-1.0.0-py3-none-any.whl
Size 2.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a7b304fa1ff28397422bb0b8820de904b53586cc5f8ccca503de4adfb5a271d3
BLAKE2b-256 checksum
How to use checksums
3ca66bf93c2a334e45378c7cffa442dff40932cc6bba65e4a52cebf44d45118c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.3

Security for apparatusai 1.0.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

1.0.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page