I have been searching for a way to autotrade on Nadex
https://www.nadex.com
and came across this script https://github.com/FreeTheQuarks/NadexBot
It is an old script and I am not that experienced in Python.
Q1: Is this a good way to go about, thus since it is not a official API and is probably scraping data from the site, which would mean slower requests and trade execution?
There is also an unofficial API client https://github.com/knoguchi/nadex/tree/master/nadex
But again, not sure if good for live trading.
Q2: Is there better ways to go about this and if so where should I start?
I'm the author of the Nadex unofficial API Python client.
I still maintain it. Recently the streamer support was added.
However, I suggest that you use JavaScript from nadex.com. It's always up-to-date and works just like the official web site, obviously.
The JS code is professionally written. Very readable. There are 100 JavaScript files but essential ones for the API access are only handful.
Nadex is a part of IG Group. Hence the JS has lots of IG namespace. IG offers API and documents for developers. Nadex message format is a little different from IG's but the design is same. Once you learn the document, all the JavaScript code is really easy to understand.
A1: Measure Twice Rather Before One Cut$
Simply put, it is your money you trade with, so warnings like this one ( from FreeTheQuarks )
(cit.:)This was the first non-trivial program I wrote.It hasn't received any significant updates in years.I've only made minor readability updates after first putting this on git.
should give one a sufficient sign to re-think the risks, before one puts a first dollar on table.
This is a for-profit game, isn't it?
A2: Yes, there is a better way.
All quantitatively supported trading strategies need stable and consistent care - i.e. one needs to have
rock-solid historical data
stable API to work with ( Trade Execution & Management, Market Events )
reliable & performant testbed for validating one's own quantitative model of the trading strategy
Having shared this piece of some 100+ man*years experience, one may decide on one's own whether to rely on or rather forget to start any reasonable work with just some reverse-engineering efforts on an "un-official API client".
In case the profit generation capability of some trading strategy supports the case, one may safely order an outsourced technical implementation and technical integration efforts in a turn-key manner.
Epilogue:If there are quantitatively supported reasons to implement a trading strategy,the profit envelope thereof sets the ultimate economically viable modelfor having that strategy automated and operated in-vivo.Failure to decide in this order of precedenceresults in nothing but wasted time & money.Your money.
I was looking into the Nadex platform recently too. I wrote a small wrapper over the oanda foreign exchange broker api v1 in python (now they have v2.0) so I have some experience.
To implement an autotrading bot is a big question, but to try and answer: you may either use a pre-existing wrapper for the Nadex API (it looks like either Python or Javascript are your choices), or write one yourself, in a language of your preference.
If you want to start from scratch, I believe Nadex offers a RESTful service, which basically means you can make GET, POST, DELETE, and other types of requests via a specific URL (most of the time there is a 'base' URL from where other endpoints spawn). I would first go about trying to find the endpoints to the Nadex servers - Kenjis unofficial API should point in the right direction there, since he is using URL strings and has a class for making different requests. I was unsuccessful trying to find any documentation for Nadex API myself, but Kenji's wrapper or the Javascript API both look promising. Depending on the depth of the market and number of requests, I think you are correct saying that you wouldn't want a web scraper for something like this. It would be very slow (and probably wasteful of time) compared to using an existing wrapper. I would start writing classes and/or functions that make simple requests to the Nadex RESTFUL endpoints, for example a function that logs in the accesses account data. Next step would be to retrieve market data and eventually stream the market data into a trade logic algorithm that makes decisions for you.
If you want to build a trading bot easily and with most of the work cut out for you, I would recommend one of the other answers here. That way, you can use their predefined classes/functions and have the "boring" API access code written for you, ready to use.
Hope that helps or leads you in the right direction!
Related
I just need pointers on where to begin. I have some experience with Python, but nothing to brag about.
My end goal is to create a website that will allow multiple users to access it from different computers to fill the table with simple data, very simillar to what Google Sheets alows, and then printing it on a single sheet of paper. Idealy I want my programm to intelegently determine the width of rows and columns so that the table would look decently and would fill the page accordingly.
Right now all I need is some pointers on where to begin. Like can I use SQL to create these tables and have online fuctionality for users to access and fill the spreadsheet, and how to go about printing it.
I know this is very noob question, but I can't seem to find anything relevant here on by just using google.
Thank you.
I don't think this is a very good StackOverflow question because it is very broad and not programming specific. You are asking how to start a new software project which in my opinion belongs more in the software engineering meta: https://softwareengineering.stackexchange.com/
Anyhow, how I would take on such a project:
First I would define my project scope. What is the functionality of the end-product? What must it be able to do and what not? Who are the end-users using the product and what do they expect? These are so called functional requirements.
In which way does the product deliver value? Is it fast, modifiable, distributed... These are so called non-functional requirements.
Develop a basic software architecture based on the previous requirements using patterns and tactics and identify the different subsystems. On the top of my hat I would divide it in a frontend component using a web application, backend component in your favourite language and a database component for persistence.
Research possible languages frameworks for each component, decide and start coding!
For the 4th step I suggest you have a look at Python Django which includes all of this stuff out-of-the-box.
I am a data analyst and just assigned to build a real time recommendation engine for our website.
I need to analyse the visitor behavior and do real time analysis for those input. Thus I have three questions about this project.
1) Users are not forced to sign-up. Is there any methodology to capture user behavior such as search and visit history?
2) The recommendation models can be pre-trained but the prediction process takes time. How can we improve the performance?
3) I only know how to write Python Scripts. How can I implement the recommendation engine with my python scripts?
Thanks.
===============
However, 90% of our customers purchase the products during their first visit and will not come back shortly.
We cannot make a ready model for new visitors.
And they prefer to use itemCF for the recommendation engine.
It sounds like a mission impossible now...
This is quite a broad question however I will do my best to answer:
Visit history can be tracked by enabling some form of analytics tracking on your domain. This can either be a pre-built solution that you implement and will provide a detailed overview of all visitors to your domain, usually with some form of dashboard. Most pre-built solutions provide a way to obtain the analytics that have been collected.
Another way would be to use browser cookies to store information pertaining to each visit to your domain and their search/page history. This information will be available to the website whenever the user visits it within the same browser. When the user visits your website, you could send the information to a server/rest endpoint which could analyse information (I.P/geolocation/number of visits/search/page history) and make recommendation based on that. Another common method is to track past purchases ect.
To improve performance one solution would be to always have the prediction model for a particular user ready for when they next visit the site. That way, there is no delay. However, the first time a user visits you likely wont have enough information to make detailed predictions so you will have to resort to providing options based on geolocation (which shouldn't take to long and wont impact performance)
There is another approach that can be taken and above mainly talked about making predictions based on a users behavior browsing the website. Content-based filtering is another approach which will recommend things that are similar to a item that the user is currently viewing. This approach is generally easier, as it just requires that you query a database for items that are similar in category, purpose/use ect.
There is no getting around using javascript for the client side stuff, however your recommendation engine can be built in Python (it could be a simple REST api endpoint with access to the items database). Most people use flask,django or eve to implement REST API's in Python.
I'm about to start the development of a web analytics tool for an e-commerce website.
I'm going to log several different events, basically clicks on various elements of the page and page views.
These events carry metadata (username of the loggedin user, his country, his age, etc...) and the page itself carries other metadata (category, subcategory, product etc...).
My companies would like something like an OLAP cube, to be able to answer questions like:
How many customer from country x visited category y?
How many pageviews for category x in January 2012?
How many customer from country x visited category y?
My understanding is that I should use an OLAP engine to record these events, and then build a reporting interface to allow my colleagues to use it.
Am I right? Do you have advices on the engine and frontend/reporting tool I should use? I'm a Python programmer, so anything Python-friendly would be nice.
Thank you!
The main question is how big your cube is going to be and if you need an open source OLAP solution or not.
If you're dealing with big cubes and want to get room for future features you might go for a real OLAP Server. A few are open source - Mondrian - and other have a 'limited' community edition - Palo, icCube. The important point here is being compatible with MDX and XMLA. defacto OLAP standard, so you can plug different reporting tools and/or using existing libraries. My understanding, there is no Phyton version for an XMLA library as in Java or .NET not sure this is the way to go.
If you're cubes are small you can develop something on your own or go for other quicker solutions as the comment of Charlax is indicating.
As mentioned in the selected answer, it depends on your data amount. However, just you run into a case that a light-weight Python OLAP framework would be sufficient, then you might try Cubes, sources are on github. It contains SQL backend (any other might be implemented as well) and provides a light HTTP OLAP server. Example of an application (PHP front-end with HTTP Slicer OLAP server backend) using it can be found here It does not contain visualization layer and complex queries thought, but that is trade-off for being small.
The site won't be that complicated and will resemble a modern blog (users, messages, news and other similar features).
Do I need to use a framework for this, and if so, which is best?
Pyramid, Django?
You certainly don't need a webframework to create a simple website. Given that you're new to python and interested in building a python website, I imagine this implies: you're interested in learning python. If you're exclusively interested in learning django-python, there's no reason you can't jump in to django, as Ronak said, of course. He's right. It has a lot of documentation. But it will make for somewhat of an odd intro to python.
If I were in your shoes, I'd either start making some offline programs first, or consider an ultra-lightweight framework. Many would advocate web2py or pyramid for ultralightweight. I might consider going even lighter. Something like Bottle, where you're more or less just pairing functions with urls. This way you can at least do a bit of hacking/trial-and-error, instead of launching right into django.
It's not that django doesn't use python-- it will tell you many times that it is in fact 'just python.' But it's adapted at its core to be used in a large business setting (the chicago something or other online, i think). So it enforces various rules that are helpful in managing many different employees working on a project together. You may or may not wish for this kind of 'help.' It also means the scale of projects is assumed to be large and the time-horizon, limitless. If you want to see how a python dictionary works, you may not want to spend a long time configuring settings and creating the pseudo-static-typing you need for your database, and so on, just to execute your project and see a result.
I realize I will automatically get downvoted for this, but I believe it to be sound advice.
It depends on what kind of website you are planning to come up with. If the website is going to be just a set of static HTML files, then you don't really need a framework. But if your website will have lots of dynamic content that will get updated on regular basis, you should go with some framework. That will make your life maintaining the website much more simpler.
Django is the most popular framework written in Python. It has very good documentation and a strong community base too.
Go with Django - 10,000 Elvis fans can't be wrong.
Or roll your own from scratch. You'll learn a lot, know everything about how you site works, and better appreciate what a framework does for you.
As RonakG first pointed, it all depends on the kind of website you intend to have up and running. Actually, your question is too general for a single, definitive answer. There are more aspects to consider other than just being in python. For example, deadlines. This means considering the learning curve to achieve your results. If you don't have much time, a steep learning curve (time to learn it in order to develop it) is certainly something you will want to avoid. Perhaps you already develop in other languages, and need integration and/or migration support, need scalability, reusability, etc, etc, etc.
Another thing that is not so clear in your question is what you mean by "The site won't be that complicated and will resemble a modern blog (users, messages, news and other similar features)". If it really resembles just a modern blog, with users, messages and news, you could google for CMS (Content Management Systems). There are many options available, that could make you have your site up and running in almost no-time. All you'll have to learn is how to customize whatever it has to as to comply to your needs.
That said, if you prefer python, there are some good CMSs available which you can develop your site fast, like Plone. And if you prefer Django, there's Django CMS and there's the excellent Pinax project, which takes the django code reusability to deliver you sample fully customizable, complete websites.
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I'm comming from java world (apache wicket) and need to use python for my project.
I've heard about Turbogear2, Pyramid(Pylons) or Django and read some about them.
My first choice will be TurboGears2 built on top of Pylons, with tools already packaged, but
perhaps someone as some advice.
I do not need to create a lot of content like wikis or blog, but represent and
give access to some objects in my database, and then build a javascript interface
to work on this data.
What I need the web framework to to for me :
authentication system with roles (admin, user, group,...)
use of enhanced javascript tools like dojo outside the app, but
it would be good if I could share components between the app and the javascript library.
easy AJAX : components have to be refreshed 'onChange' (I don't like submit buttons)
a good ORM. Don't know SQLAlchemy but it seems nice, mapping object to/from database, database pooling,....
easy deployment (coming from java I think it will be ok ;))
add easily css or js to pages
a framework that don't break my nerves ;)
a good documentation and/or good support
threading/multiprocess support (there are a lot of calculations. Some of them taking huge amout of memory, some other taking
processing time. So I want to be able to lauch procees out of application. But I think it's more about using a python library
and nothing to do with this question? )
THX
For myself, mako + sqlalchemy in Pyramid are what seal the deal. If you're into some decent DB work, SqlAlchemy is just the best to work with. I'm also a big fan of the mako templates. The ability to create presentation type functions in mako itself that are reusable vs trying to do things in python modules that you end up trying to import in is a plus in my book.
What I really wanted to mention is that for your final item, you should really look at farming that stuff out to outside workers by using a message queue and something like Celery to do the work and use the web app more for submission/results display than actually trying to split the work out of your web application.
As pointed out by S.Lott in his comment, your requirements do not give a clear-cut "winner" as at least most of the frameworks have that capability.
Three dimensions along which which python web framework diverge more are IMO:
Closeness to the concept of "pythonic"
Lightness
Overhead
Typically lighter frameworks will: require more overhead and have a more pythonic approach (webpy, cherrypy...), while heavier frameworks (django, turbogear...) will let you have your app up and running in minutes but will somehow oblige you to shape your code in a certain (logical but not necessarily pythonic) way.
That said, I believe 95% of your answer relies on personal preference.
HTH!
In addition to the frameworks you have mentioned, you should definitely check out web2py. I think you'll find it among the easiest to set up, learn, and use, particularly given the breadth of functionality it offers. One if its primary goals is to not "break your nerves." It includes an excellent authentication system; integrated Javascript/AJAX support (see also components); a fast and powerful database abstraction layer; web services; automatic RESTful API generation; great documentation; and a very helpful and responsive mailing list. Development is very active, with new releases at least every month (without ever breaking backward compatibility). Here is a recent presentation.
An opinion piece...
I like the character of Pylons (now replaced by Pyramid) and the wide support of new initiatives by the Django framework (though not its keeness to reinvent so many wheels - esp. MVC).
I like the Data Abstraction Layer in Web2py that enables deployment to Google's AppEngine. This was a key feature in making my decision. Web2py is RoR inspired which some may shirk but which I've appreciated and so far hasn't blocked any development path.
In the end having tried several frameworks I've used Web2py (using the offical book as reference). A great community with very fast response.