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Python SDK Marketing - Immediate Action Plan

Goal: Increase PyPI downloads from current baseline to 500+/month within 30 days Status: Ready to execute Time Required: 2-3 hours total

✅ COMPLETED (Just Now)

  1. Added Downloads Badge to README.md
  2. Created CODE_OF_CONDUCT.md
  3. Verified Backlinks - You have 2 backlinks from pypi.org:

🚀 IMMEDIATE ACTIONS (Do Today - 30 minutes)

1. Commit and Push SDK Improvements

cd /home/kwaldman/code/sdks/python
git add README.md CODE_OF_CONDUCT.md
git commit -m "Add downloads badge and CODE_OF_CONDUCT

- Add PyPI downloads/month badge for transparency
- Add Contributor Covenant Code of Conduct v2.1
- Improve community documentation

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>"
git push

2. Submit to awesome-python (5 minutes)

Steps:

  1. Go to: https://github.com/vinta/awesome-python
  2. Click "Fork" button
  3. Edit README.md, find "Third-Party APIs" section
  4. Add alphabetically: 
    * [oilpriceapi](https://github.com/oilpriceapi/python-sdk) - Official SDK for oil & commodity price data with Pandas integration.
  5. Create PR with title: "Add oilpriceapi SDK"
  6. In PR description: "Adding OilPriceAPI Python SDK - real-time commodity price data with first-class Pandas support"

3. Submit to Python Weekly (2 minutes)

URL: https://www.pythonweekly.com/submit

Form Fields:

  • Title: OilPriceAPI Python SDK - Real-time Commodity Prices
  • URL: https://github.com/oilpriceapi/python-sdk
  • Description: 
    Official Python SDK for OilPriceAPI with Pandas integration, async support, and CLI tools.
Get real-time and historical oil & energy commodity prices for trading and financial analysis.
Features: DataFrame support, technical indicators (SMA, RSI, MACD), smart caching,
rate limit handling. Free tier: 100 requests (lifetime).

4. Email PyCoder's Weekly (3 minutes)

To: editors@pycoders.com Subject: Submission: OilPriceAPI Python SDK

Hi PyCoder's Weekly Team,

I'd like to submit our Python SDK for consideration:

Project: OilPriceAPI Python SDK
GitHub: https://github.com/oilpriceapi/python-sdk
PyPI: https://pypi.org/project/oilpriceapi/

Official Python SDK for real-time and historical commodity price data. Features:
- Pandas DataFrame integration
- Async/await support
- Built-in technical indicators (SMA, RSI, MACD, Bollinger Bands)
- CLI tool for quick exports
- Smart caching and rate limit handling

Perfect for energy traders, financial analysts, and data scientists.
Free tier: 100 requests (lifetime).

Thanks for considering!
OilPriceAPI Team

📅 THIS WEEK ACTIONS (1-2 hours)

5. Post on r/Python (10 minutes)

Subreddit: https://www.reddit.com/r/Python/submit Best Time: Tuesday-Thursday, 9-11am EST

Post Type: Text Post

Title:

[P] OilPriceAPI Python SDK - Real-time commodity prices with Pandas integration

Content:

Hi r/Python!

I've released a Python SDK for OilPriceAPI and wanted to share it.

**What it does:**
- Real-time and historical oil & commodity price data
- First-class Pandas DataFrame support
- Async/await for high-performance applications
- Built-in technical indicators (SMA, RSI, Bollinger Bands)
- CLI tool for exports

**Quick example:**
```python
from oilpriceapi import OilPriceAPI

client = OilPriceAPI()
df = client.prices.to_dataframe(
    commodity="BRENT_CRUDE_USD",
    start="2024-01-01"
)
print(df.describe())

Links:

Use cases:

  • Financial/trading analysis
  • Energy market research
  • Data science projects
  • Academic research

Free tier: 100 requests (lifetime). Feedback welcome!


### 6. Submit to awesome-quant (5 minutes)
**Repo:** https://github.com/wilsonfreitas/awesome-quant

1. Fork repository
2. Find "Data Sources" section
3. Add:
   ```markdown
   - [OilPriceAPI](https://oilpriceapi.com) - Real-time oil & energy commodity prices. [Python SDK](https://github.com/oilpriceapi/python-sdk)
  1. Create PR

7. Post on LinkedIn (5 minutes)

Excited to share the OilPriceAPI Python SDK! 🎉

After months of development, we've launched a Python SDK that makes commodity price data accessible.

Key features:
✅ Real-time and historical data
✅ Pandas DataFrame integration
✅ Async support
✅ Built-in technical indicators
✅ Free tier to get started

Perfect for energy trading firms, financial analysts, data scientists, and researchers.

PyPI: https://pypi.org/project/oilpriceapi/
GitHub: https://github.com/oilpriceapi/python-sdk

#Python #DataScience #EnergyTrading #FinTech #OpenSource

8. Tweet Announcement (3 minutes)

🚀 Launched: OilPriceAPI Python SDK v1.0

Get real-time oil & commodity prices in Python:

pip install oilpriceapi

✅ Pandas integration
✅ Async support
✅ Technical indicators
✅ CLI tool

Free tier: 100 requests (lifetime)

PyPI: https://pypi.org/project/oilpriceapi/
Docs: https://docs.oilpriceapi.com/sdk/python

#Python #DataScience #Trading

📝 CONTENT CREATION (Next Week - 2-3 hours)

9. Write dev.to Article

Title: "Analyzing Oil Price Data with Python and Pandas"

Outline:

  1. Introduction - Why commodity price data matters
  2. Getting Started - Installation and setup
  3. Basic Usage - Fetching latest prices
  4. Data Analysis - Using Pandas for analysis
  5. Technical Indicators - SMA, RSI examples
  6. Real-World Use Case - Spread analysis
  7. Conclusion - Call to action

Target Length: 1,500-2,000 words Include: 5-7 code examples with outputs Images: 2-3 charts/visualizations

10. Cross-post to Medium

Same article as dev.to, published 1 week later

📊 TRACKING & METRICS

Monitor These Metrics:

PyPI Stats:

# Check current downloads
curl -s https://pypistats.org/api/packages/oilpriceapi/recent | python3 -m json.tool

GitHub Stats:

Website Analytics:

  • Referrals from pypi.org
  • Referrals from github.com
  • API signups with UTM source=pypi

Success Criteria (30 Days):

  • 500+ PyPI downloads/month
  • 50+ GitHub stars
  • 10+ website signups from PyPI
  • Featured in 1+ newsletter
  • 3+ community mentions

🎯 PRIORITY RANKING

DO TODAY (30 min):

  1. ✅ Commit SDK improvements
  2. Submit to awesome-python
  3. Submit to Python Weekly
  4. Email PyCoder's Weekly

DO THIS WEEK: 5. Post on r/Python (wait for Tue-Thu) 6. Submit to awesome-quant 7. Post on LinkedIn 8. Tweet announcement

DO NEXT WEEK: 9. Write dev.to article 10. Cross-post to Medium

📋 CHECKLIST

  • Git commit and push SDK changes
  • Fork and PR to awesome-python
  • Submit to Python Weekly
  • Email PyCoder's Weekly
  • Schedule r/Python post (Tue-Thu morning)
  • Submit to awesome-quant
  • LinkedIn post
  • Twitter post
  • Write dev.to article
  • Cross-post to Medium
  • Monitor metrics weekly
  • Respond to all comments/questions

💡 TIPS FOR SUCCESS

  1. Be Authentic - You're sharing a useful tool, not spamming
  2. Engage with Comments - Respond to all feedback promptly
  3. Provide Value - Focus on how it helps developers
  4. Don't Over-Promote - Let the features speak for themselves
  5. Track Everything - Use UTM parameters for attribution

UTM Parameters to Use:

  • ?utm_source=reddit&utm_medium=post&utm_campaign=python_sdk_launch
  • ?utm_source=python_weekly&utm_medium=newsletter&utm_campaign=python_sdk_launch
  • ?utm_source=awesome_python&utm_medium=list&utm_campaign=python_sdk_launch

🔄 NEXT STEPS

After completing all actions above:

  1. Wait 7 days
  2. Review metrics
  3. Adjust strategy based on what works
  4. Consider paid promotion if organic growth is slow
  5. Plan Phase 2 (Node.js SDK marketing)

Total Time Investment: 4-6 hours over 2 weeks Expected ROI: 5-10x increase in PyPI downloads Cost: $0 (all organic)

Ready to execute? Start with the "DO TODAY" section! 🚀