React Native bundle loading failing on a physical device

I’m building a React Native application and recently updated to v0.31.0 and at first things were working well debugging on the device benefiting from a feature of the react-native-xcode.sh script. The script copies your Dev machine’s IP address to a text file called ip.txt which is used for establishing the connection to your machine from your device since localhost points to the wrong place. Here’s the line of code in ./node_modules/react-native/packager/react-native-xcode.sh:

echo "$IP.xip.io" > "$DEST/ip.txt"

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Using Google Sheets, Pivot Tables and Charts as a Startup Dashboard – Part II

In my previous post I wrote about the process that lead me to build a dashboard but first I want to talk a bit about the structure of the data in the Google Sheet where the whole process started. I first started by looking to quickly create a few charts to visualize some of our KPI‘s. To source the data I created a text file containing the SQL statements and used psql to fetch Postgres data which I dumped it to data into .CSV files for import into separate “data” only tabs in Google Sheets.

psql -h pgserver -d mydb -U myuser -w -t -A -F $'\t'  -f ~/Campaigns.sql > campaign.csv

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From Google Sheets to an Automated Shiny Dashboard (Part I)

Over the past several months I’ve been building what’s become a large Google Sheet (which is now at the 2M cell limit) tracking Find&Save Cash Dash offers. Like a lot of data projects this one started out small but over many months grew to a point where it no longer makes sense to cut/paste SQL data into a Google Sheet for pivot tables and charts. I wanted a solution that could pull data from REST APIs, MSSQL and Postgres and present data in an internal dashboard. Unfortunately, Google Sheet’s JDBC support doesn’t include Postgres otherwise Google Apps Script might have been a viable choice for automating data collection notwithstanding size limitations. Finally, another issue with Sheets was that I couldn’t seem to get pivot tables to resize automatically as more data was added. So, 3 strikes and Google Sheets was out.

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Plotting Weekly Mobile Retention from the Localytics API using R and ggplot2

Part of building mobile web apps is understanding the myriad of mobile analytics and in part visualizing the data to shed light on trends that my otherwise be difficult to see in tabular data or even a colorful cohort table. I’ve been building a dashboard using R, RStudio, Shiny, and Shiny Dashboards aggregating data from MSSQL, Postgres, Google Analytics, and Localytics.

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Fetching Localytics API Data in R and working with the JSON result

Recently, I’ve been building a dashboard for Find&Save using R, RStudio and Shiny Dashboards and one of our core mobile metrics is 30 day active users for both iOS and Android which I can get from Localytics (our analytics platform) via their API. Googling around I found I’m not reinventing the wheel (via SO) though I did run into a problem where the response failed to convert properly thus the post.

Here’s the original function from SO with some slight tweaks for my needs:

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ReactNativeJNI: Check failed: *m_isDestroyed JSCExecutor::destroy() must be called before its destructor

Short post to get this indexed as we didn’t find it elsewhere on the web.

While working to ship a new release of the Find&Save Android app we ran into a crash on launch which only occurred in our release build. The crash was in JSCExecutor.cpp which is part of React Native and left very few hints as to what was wrong with no call stack, Crashlytics logs etc. The only error we had was:

ReactNativeJNI: Check failed: *m_isDestroyed JSCExecutor::destroy() must be called before its destructor

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Dimming the insanely bright LED’s on a Motorola SB6141 cable modem

A few weeks ago I decided to upgrade an aging Motorola SB6141 cable modemMotorola SB5101 cable modem to a new Motorola SURFboard 400 Series SB6141. After the obligatory call to Comcast to register the new MAC address everything was going swimmingly until I turned off the lights and suddenly landed in the world of TRON. The entire room was basked in cool blue light from the “stupidly, ridiculously, blindingly bright” LED’s. Seriously, they’re that bad and more, blinking incessantly and with a case full of holes it nearly filled the room.

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