Uniswap V3 allows a user to provide liquidity within specific price ranges known as a range order. For example, you could provide liquidity on ETH:USDC just within the range of $2500-$3500. Meaning you are willing to use your entire position to purchase ETH at $2500 and are willing to sell your entire position to USDC at $3500. Uniswap lists some examples of strategies that can be built with range orders like take profit and buy limit orders.
First detailed in Uniswap V3 LP Tokens as Perpetual Put and Call Options Guillaume Lambert explains how Uniswap V3 liquidity positions can form…
Two easy steps
Thank you to everyone that has already activated their DAI on Give Together. Today we made needed changes to the contract. There was a bug that did not forward rDAI to the charities when sent to the contract. This has been fixed in this commit. In addition to the fix, a few new methods have been added, including one to transfer ownership of the contact is necessary.
If you have activated your DAI on Give Together you will need to withdraw it and then activate it again. This is due to how rDAI works. When you activate…
No Loss Charitable Donations powered by rDAI
Give Together allows you to donate to a new charity each week all at no loss to you!
Each week an Ethereum Smart Contract determines a new charity currently from this list (although we are open to adding more!). This week’s charity is Code for America and later today the interest generated will be redeemed to them (the contract became live on the mainnet last week). The interest accrues from the Compound Protocol and is redeemed to the smart contract using rDai. …
IPFS + ENS
When hosting a website usually you use a dedicated VPS like Digital Ocean, Linode, Google, or Amazon. After setting up your server you can register a domain at Google Domains or NameCheap. The last step is editing your DNS records to point your domain at your server. Now you can access your website by navigating to your domain name. However, there is a problem with this. Your VPS controls the hosting of your site and the domain name service you went with maintains control of your domain. What happens if your VPS goes down or the company you are using…
Sentence parsing can be helpful in understanding the meaning, structure, and syntactical relationships in sentences. Two common types are dependency and constituency parsing which is also known as syntactical parsing. Dependency parsing is the process of defining the grammatical structure of a sentence by listing each word as a node and displaying links to its dependents. A constituency parsed tree displays the syntactic structure of a sentence using context-free grammar. Unlike dependency parsing which relies on dependency grammar. Both types of parsing are important in computational linguistics but there is much debate over which is better. …
In 100 lines of code
Investing in the stock market used to require a ton of capital and a broker that would take a cut from your earnings. Then Robinhood disrupted the industry allowing you to invest as little as $1 and avoid a broker altogether. Robinhood and apps like it have opened up investing to anyone with a connected device and gave non-investors the opportunity to profit from the newest tech start-up.
However, giving those of us who are not economists or accountants the freedom to invest our money in the “hottest” or “trending” stocks is not always the best financial decision.
I recently read an article in the Washington Post titled, “Ranking the media from liberal to conservative, based on their audiences”. Inspiring me to rank news sites based on their subjectivity and polarity on a given subject, in this case, Donald Trump.
I used Python to pull the following news sites for their 30 most recent articles that contained the keyword “Trump” (ranging from the liberal side of the Washington Post article to the conservative side):
- New Yorker
- NPR
- CNN
- Fox News
- Drudge Report
- Breitbart
Then performed a text analysis on the description of the article to return a list…
After creating the Free Wtr bot using Tweepy and Python and this code, I wanted a way to see how Twitter users were perceiving the bot and what their sentiment was. So I created a simple data analysis program that takes a given number of tweets, analyzes them, and displays the data in a scatter plot.
Setup
I had to install a few packages to create this: Tweepy, Tkinter, Textblob and matplotlib. You can install each of these with the pip package manager. For example:
pip install tweepyor you can clone into the Github repository like this.
git clone https://github.com/sloria/textblob
cd…The information age has revolutionized the way we interact, communicate and are perceived. In the United States, approximately 90 percent of the population is on the internet, using Facebook and Google to catch up with high school friends and to answer their questions. Companies such as Google constantly collect data on search habits of the user and what they like, in order to provide more personalized results and to improve their company.
Data collection and the selling of this personal data has been a topic of controversy lately, primarily due to the Facebook and Cambridge Analytica scandal. In the 2017…
After creating the Free Wtr bot using Tweepy and Python and this code, I wanted a way to see how Twitter users were perceiving the bot and what their sentiment was. So I created a simple data analysis program that takes a given number of tweets, analyzes them, and displays the data in a scatter plot.
Setup
I had to install a few packages to create this: Tweepy, Tkinter, Textblob and matplotlib. You can install each of these with the pip package manager. For example:
pip install tweepyor you can clone into the Github repository like this.
git clone https://github.com/sloria/textblob
cd…
