Data sources
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PyPI

PyPI Data Integration — Package Analytics Decoded

Gather download statistics, package popularity, and dependency data from Python Package Index. Build developer ecosystem dashboards in Tableau with open-source usage insights.

500+
Data Sources
46K+
Metrics
99.9%
SLA
<5 min
Setup
SOC 2
Type II
Why Improvado

Automate PyPI package data extraction

Improvado connects to PyPI's API to extract package download statistics, version information, and dependency data automatically. Pull download counts, geographic distribution, and version adoption rates without manual data collection. The integration refreshes package metrics on schedule, tracking your Python package performance over time. Monitor both your own packages and competitor analysis.

PyPI Improvado
Snowflake BigQuery Redshift Tableau Power BI AI Agent
46K+ metrics 500+ sources No code Auto-refresh
Your sources
PyPI + 500 more
Marketing Common Data Model
Same metrics
Same schema
Any destination
Unified Data

Combine PyPI data with business metrics

Improvado's Marketing Common Data Model normalizes PyPI package data alongside your marketing and product analytics. Correlate package downloads with marketing campaigns, track developer engagement across channels, and measure open source community growth. Your PyPI metrics combine with GitHub, Google Analytics, and 500+ other sources for comprehensive developer tool insights.

Use Cases

What users ask their PyPI integration

Cross-channel
Track package adoption rates against marketing campaign performance
3 hrs → 8 min
Budget optimization
Analyze download geography to optimize developer conference sponsorships
Manual → auto
Executive reporting
Build executive reports showing open source community growth metrics
5 hrs → 15 min
AI Agent Access

Go beyond dashboards — give your AI agent direct access to ad data

Improvado MCP connects your ad platform data to Claude, ChatGPT, Cursor, and any MCP-compatible AI tool. Read metrics, launch campaigns, monitor anomalies — all through one protocol.

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Launch
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Read

Pull ROAS, CPA, search terms, geo data — across every account and campaign type. Your AI agent handles the API calls.

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Write

Launch campaigns, pause underperformers, adjust bids and budgets. Every action logged, governed, and reversible.

Monitor

Set up CPA alerts, budget pacing watches, and weekly auto-reports. Problems caught before they eat your budget.

40K+
Harmonized metrics
250+
Governance rules
500+
Connectors
40h+
Saved weekly
Works with Claude ChatGPT Cursor Gemini Any MCP Client
99.9% SLA
Data warehouse
Managed storage
Cross-channel
Deep granularity
Attribution

Extract data from 500+ data sources

Connect and manage all your marketing data sources in one platform, both in the cloud or on-premise.

Load data to any data warehouse

Connect multiple data sources and analyze them as if they were a single database.

Combine, map, and normalize data to produce a comprehensive data set surrounding your marketing activities.

Transform your data without SQL skills

Analyze data in
real-time

You can use it directly with your favorite business intelligence tools, ingest it to econometric models and populate the enterprise data warehouse

Get analysis-ready data for marketing analytics

Get all your data in one place instantly

SOC 2 Type II

Auditing procedure that ensures secure management of data.

HIPAA

Complies with Health Insurance Portability
and Accountability Act (HIPAA)

Improvado is GDPR compliant.
GDPR

General Data Protection Regulation (GDPR) Certified

Improvado is CCPA compliant.
CCPA

Complies with California Consumer Privacy Act (CCPA)

Centralize all your marketing data in one place

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You can analyze data from 500+ data sources

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G2 Crowd logo
Capterra logo

A great customer service that always tries to be helpful with a "how can we make it" approach. They understand your needs, provide all relevant solutions to successfully implement them, and make your job done.

Ahmet Sergen D
Ahmet Sergen D
Regional Digital Manager
Ahmet Sergen D
Regional Digital Manager

A great customer service that always tries to be helpful with a "how can we make it" approach. They understand your needs, provides all relevant solutions to successfully implement them, and make your job done.

If you consider hiring Improvado, you are also a hiring team that supports you to achieve your goals to become a more data-driven company.

Improvado is helping us to aggregate our paid marketing data from multiple channels and present it in a meaningful way. We are more efficient with reporting our campaign results and have better ideas about what's going on easily.

Read the case study
G2 Crowd logo
Capterra logo

Professional, responsive and willing to go the extra mile to help. They are a solution to connect to most advertising platforms and provide a multitude of metrics from these platforms

They are willing to go the extra mile to attend to your query and help to the best they can.

Helping to connect to various advertising platform such as Google Ads, Facebook, DV360, Trade Desk.

They are a solution to connect to most advertising platform and provide a multitude of metrics from these platforms

Read the case study

Frequently Asked Questions

What PyPI data does Improvado extract?
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Improvado extracts package download statistics, version information, file details, and metadata from PyPI. We also pull dependency data, release history, and geographic download distribution. All data includes timestamps for trend analysis.
How frequently does PyPI data update?
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PyPI data syncs daily by default to capture new downloads and version releases. You can adjust frequency for packages with high update volumes. Real-time monitoring is available for critical package launches.
Can I track multiple PyPI packages at once?
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Yes, Improvado can monitor unlimited PyPI packages simultaneously. Track your own packages, competitor packages, or entire dependency ecosystems. Each package's data is clearly organized for comparative analysis.
Does this include package dependency information?
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Yes, Improvado extracts package dependencies, requirements, and version constraints from PyPI. This enables ecosystem analysis, dependency tracking, and understanding package relationship networks within your data warehouse.
Where can PyPI data be sent for analysis?
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PyPI data flows to BigQuery, Snowflake, Redshift, Azure Synapse, and other data warehouses. It also connects directly to Tableau, Power BI, Looker for visualization. Choose destinations that fit your developer analytics stack.
Can I combine PyPI data with GitHub metrics?
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Absolutely. When combined with GitHub data in your warehouse, you can analyze the relationship between repository activity and package downloads. Track how code commits, issues, and releases impact PyPI adoption rates.