Skip to main content

Bigdata.com API High-Efficiency Tools at Scale

Project description

Bigdata Logo

Bigdata Research Tools

Python version support PyPI version

Bigdata.com API High-Efficiency Tools at Scale

This repository provides efficient toolset to use the Bigdata.com SDK.


Installation

Install the package from PyPI using pip:

pip install bigdata-research-tools

Usage

The following example demonstrates the convenient way to run multiple searches in a concurrent and rate-limited manner:

from bigdata_research_tools import run_search
from bigdata_client import Bigdata

bigdata = Bigdata()

results = run_search(bigdata=bigdata,
                     queries=YOUR_LIST_OF_QUERIES,
                     limit=1000)

1. Return Values

1.1. Return only the results list

By default, setting only_results=True will return a list of all results from all queries.

results = run_search(bigdata=bigdata,
                     queries=YOUR_LIST_OF_QUERIES,
                     limit=1000,
                     only_results=True)
>>> results
[
    [results1, results2, ...],
    [results1, results2, ...],
    [results1, results2, ...],
]

1.2. Return queries with their corresponding results

Setting only_results=False will return a dictionary mapping each (query, date_range) combination pair to their respective search results list.

query_results = run_search(bigdata=bigdata,
                           queries=YOUR_LIST_OF_QUERIES,
                           limit=1000,
                           only_results=False)
>>> query_results
{
    '(query1, date_range1)': [results1, results2, ...],
    '(query1, date_range2)': [results1, results2, ...],
    '(query2, date_range1)': [results1, results2, ...],
    '(query2, date_range2)': [results1, results2, ...],
    ...
}

Key Features

  • Rate Limiting: Enforces a configurable query-per-minute (RPM) limit using a token bucket algorithm.
  • Concurrency Support: Executes multiple search queries simultaneously with a user-defined maximum number of threads.
  • Thread-Safe: Ensures safe concurrent access to shared resources with built-in thread locks.
  • Flexible Configuration:
    • Set custom RPM limits and token bucket sizes.
    • Configure search parameters such as date ranges, sorting, and result limits.
  • Minimum Dependencies: Requires only the bigdata_client SDK.
  • Ease of Use: Includes a convenience function for running multiple searches with minimal setup.

License

This software is licensed for use solely under the terms agreed upon in the applicable Master Agreement and Order Schedule between the parties. For trials, the applicable legal documents are the Mutual Non-Disclosure Agreement, or if applicable the Trial Agreement. No other rights or licenses are granted by implication, estoppel, or otherwise. For further details, please refer to your specific Master Agreement and Order Schedule or contact us at legal@ravenpack.com.


RavenPack | Bigdata.com
All rights reserved © 2025

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bigdata_research_tools-0.16.0.tar.gz (56.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bigdata_research_tools-0.16.0-py3-none-any.whl (76.6 kB view details)

Uploaded Python 3

File details

Details for the file bigdata_research_tools-0.16.0.tar.gz.

File metadata

File hashes

Hashes for bigdata_research_tools-0.16.0.tar.gz
Algorithm Hash digest
SHA256 01550e7700381c3766db7d4384784136968d18e7f0086481701b100735735152
MD5 f169347452ec47ae48dc254fbf052d70
BLAKE2b-256 f380d9f93f8a314cc4411afe34b89151dffdcae116c4883fd797ef4c9de9e648

See more details on using hashes here.

File details

Details for the file bigdata_research_tools-0.16.0-py3-none-any.whl.

File metadata

File hashes

Hashes for bigdata_research_tools-0.16.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d2e127bc235f76c064a01d89da06e4d05ee83ff763b228a04bf4462dbf7cdcf5
MD5 52203bfdea3b332544a431300face497
BLAKE2b-256 addb96c1fb6f53b86b51fbac09fec0d42c9eff368378ce0e5ab3c35aad4e621d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page