Python Log Parsing & Analytics visualisation Dashboard
Budget: $30 – $250 USD
Improve Python Log-Parser & Build Interactive Call/SMS Analytics Dashboard
Project Overview
I have an existing Python 3.11 project that parses MacroDroid “Call / SMS” log files (main.py + sms_parser.py).
Right now the parser:
handles calls well
fails to capture SMS blocks
offers no visual reporting
I need an experienced Python developer (data-pipeline + front end) to:
Fix / refine the parser so all call and SMS formats are recognised (including tricky edge-cases).
Produce clean CSV/JSON outputs.
Create a lightweight interactive dashboard interface (python - windows desktop ) that shows business-friendly call & SMS stats.
Key Analytics (minimum)
Dimension Visuals & Metrics
Volume over time Line / bar charts for total calls, missed calls, outgoing, answered vs unanswered — by day, week, month
Durations - Average / median call length (incoming & outgoing)
- Scatter plot : call duration vs. time of day
Load Intensity Scatter / heat-map of “number of calls per time-unit” (minute / hour)
SMS Count of received vs sent, daily trend
Alerts Configurable thresholds (e.g. “more than N missed calls in 1 h” or “total calls below X per day”). Trigger e-mail / on-screen warning.
Add any extra insightful charts you feel would help a business quickly spot anomalies (e.g. rolling 7-day averages, top contacts by volume, distribution histograms).
Deliverables
Refactored main.py / sms_parser.py with unit-tests (pytest) proving ≥ 99 % block coverage on sample logs.
Dashboard app packaged with requirements.txt / poetry, deployable via python -m.
Tech Stack & Skills
Strong Python 3.11, regex, datetime handling
Plotting/UI: streamlit / dash / plotly / bokeh (open to suggestions)
Pandas for aggregation
Test-driven mindset; clear logging
Bonus: experience with MacroDroid logs (I have this kind of data)
Budget & Timeline
Budget: open for realistic bids (please suggest).
Timeline: parser fix within 1 week, dashboard within 1 week and 2 weeks total.
When you apply, please:
Briefly outline similar projects you’ve done.
Confirm you can start immediately.
Suggest your preferred visualization stack.
Looking forward to working with you!
Project Overview
I have an existing Python 3.11 project that parses MacroDroid “Call / SMS” log files (main.py + sms_parser.py).
Right now the parser:
handles calls well
fails to capture SMS blocks
offers no visual reporting
I need an experienced Python developer (data-pipeline + front end) to:
Fix / refine the parser so all call and SMS formats are recognised (including tricky edge-cases).
Produce clean CSV/JSON outputs.
Create a lightweight interactive dashboard interface (python - windows desktop ) that shows business-friendly call & SMS stats.
Key Analytics (minimum)
Dimension Visuals & Metrics
Volume over time Line / bar charts for total calls, missed calls, outgoing, answered vs unanswered — by day, week, month
Durations - Average / median call length (incoming & outgoing)
- Scatter plot : call duration vs. time of day
Load Intensity Scatter / heat-map of “number of calls per time-unit” (minute / hour)
SMS Count of received vs sent, daily trend
Alerts Configurable thresholds (e.g. “more than N missed calls in 1 h” or “total calls below X per day”). Trigger e-mail / on-screen warning.
Add any extra insightful charts you feel would help a business quickly spot anomalies (e.g. rolling 7-day averages, top contacts by volume, distribution histograms).
Deliverables
Refactored main.py / sms_parser.py with unit-tests (pytest) proving ≥ 99 % block coverage on sample logs.
Dashboard app packaged with requirements.txt / poetry, deployable via python -m.
Tech Stack & Skills
Strong Python 3.11, regex, datetime handling
Plotting/UI: streamlit / dash / plotly / bokeh (open to suggestions)
Pandas for aggregation
Test-driven mindset; clear logging
Bonus: experience with MacroDroid logs (I have this kind of data)
Budget & Timeline
Budget: open for realistic bids (please suggest).
Timeline: parser fix within 1 week, dashboard within 1 week and 2 weeks total.
When you apply, please:
Briefly outline similar projects you’ve done.
Confirm you can start immediately.
Suggest your preferred visualization stack.
Looking forward to working with you!