I want to generate addresses in the code of my application and then make transactions from these addresses. To sign transactions - I need some waves on this accounts. But how can I get the address, knowing only it's seed?
A first question would be to ask what progamming language are you using?
My favorite is pywaves.
In pywaves it is as easy to create a address from your seed by executing following code:
myAddress = pw.Address(seed='put your seed here')
This library knows how to convert the seed into an address object. From there you can execute actions on the object. If you want to get your address back as a string you can use:
myAddress.address
There are also other library's like wavesJ or similar javascript/C++/.. library's, however I don't have a lot off experience with those.
Related
I have an SaaS application in the pipeworks.
One of the things that has me a bit confused is the best way to manage the stable of Austalian suburb and state data across multiple databases (this applies to any country as each country has a list like this).
For example in Australia you have Australian Postcode list that links all the postcodes to the suburbs and you can use that to create a dropdown for state, suburb and postcode etc.
An example of the CSV of australian postcodes can be found HERE.
So you can upload a csv file for example but the problem remains..
Whats the best way to hold this data.. its common to all databases where you have a person, client, employee etc..
Do you replcate it in each database? Is there a better way than having redundant stores of data..
Best way to implement it..
There are several options and considerations I would look at for this problem. Some considerations:
Number of address rows expected
Whether a client database is concerned with prefill/validated international addresses
Whether the client system is web connected or can operate in isolation
Are these databases/systems hosted by you or distributed to individual clients? (SaaS implies "Web" and "Hosted by You" to points 3 & 4)
How critical address integrity is.
For smaller systems, a simple option for address systems is to de-normalize the address data (state, postcode, suburb) and consider using a central lookup database/service, either under your own control or a third party. The denormalized address table would contain the text fields for the State, Postcode, Suburb etc. rather than FK values (stateId, suburbId, etc.) This avoids needing to store lookup tables in every client DB, just one Lookup DB or leave that to a 3rd party service.
The advantage of a third-party lookup is that keeping it up to date with new areas and changes is handled for you. Third party services would require a web connection, and you have to factor in the risk of their service being down or a web connection being unavailable. Larger systems with millions of addresses might benefit from normalizing the address table, so the "cost" of replicating suitable address lookup tables might be worthwhile. You can still a central service to look up addresses, then resolve whether the client DB already has a StateId, SuburbId etc. for the respective state/suburb for that post-code before inserting one if necessary. (Cutting down the number of rows each client DB needs to address values that are actually used)
In that last example you might have lookup tables for State and Suburb linked to PostCodes, linked to Country. Country would default to the target, maybe be an optional selection for international addresses. The user provides a post code to the service which returns suburbs, they select a suburb. The address validation service could go as far as to validate the street address. When you're happy an address is "valid" and ready to be saved, you search your local State, Suburb, (even Street) tables for matches for that PostCode, if found use those FKs, otherwise insert new entries and link the FK.
Using a separate service, or services would be my consideration especially if you need to support validating/storing international addresses. For instance if the client is in Australia but regularly has address information for New Zealand. Storing entire address validation tables could get rather large if clients could be resolving addresses for many countries. (I.e. European countries and neighbours) You can write a Façade service to support different 3rd party address validation providers and/or homemade implementations with a standard interface.
If a system has to operate in isolation of an internet connection then you'll probably be stuck with each database having one or more local data sources to resolve address information.
Data integrity of address information is a separate concern you might want to consider. In some systems you need to validate that an address is recognized and don't want to allow invalid combinations or detect unexpected changes. Services that validate a particular address can provide unique IDs for an address that you can store as part of your address information. (These often tie into geocoordinate solutions where you want to quickly direct a map service to a particular location) Alternatively, if you successfully look up an address then validate that the address information is valid, even if just the country, post code, and suburb, you can create and store a hash of those values to check for tampering. (I.e. someone or some system changed a field to make the address invalid, the combined address won't match the stored hash) Addresses can be checked before use and flagged if not valid.
I'm new to WAVES and I'm learning by experimenting. I just want to know if unlike masternode coins where addresses are stored in the wallet file, with WavesCS, once you generate a seed and create a private key out of it, is the wallet address generated can be used already as is without the need to write to the wallet file or to the blockchain itself?
Node node = new Node();
String walletSeed = PrivateKeyAccount.GenerateSeed();
PrivateKeyAccount privateKeyAccount = PrivateKeyAccount.CreateFromSeed(walletSeed, node.ChainId, 0);
String walletAddress.Text = privateKeyAccount.Address;
Based on my experiment, the answer is yes to my question. All addresses generated from seed by PrivateKetAccount will already work as is and can be imported to other WAVES wallet using the seed. On the other hand, if you use /Addresses post method with corresponding API Key, you generate address but it can't be imported since the address is tied to the seed of the main node wallet.
MongoDB => Holochain Rust DHT
How to import, if possible
If I am using a different app backend, like mongo, and I get my holochain set up correctly and configured, is there a way to get the data from mongo to holochain? How would I do that?
Here is the question in context
Definitely technologically possible; you could write a nodejs script, fire up a Holochain container with the holochain-nodejs library, and import all the data as one agent. Then when users join the HC-based network, they vouch for their identity in some way and 'claim' all the data as theirs.
Here's a sketch of how it could look:
you (let's call you 'agent 0') import all the data.
For each user, you create an 'anchor' with the user's ID (I'll explain anchors in a
sec) and link each piece of data to the anchor.
You also record that
user's password hash as a private entry on your own source chain. A
user joins the network and is required to prove continuity of
identity.
They do this by using node-to-node messaging to send their
user ID and their password hash to you privately. You authorise them
to claim their identity by publishing an entry that says that "agent
public key x = user ID". (You would probably want to link from your
authorisation entry to their user ID anchor and their public key too,
for convenience's sake.)
The user collects all their data by asking
for all the links to their user ID anchor.
The user then publishes
each piece of their data to their own source chain as a way of
'claiming' ownership of it.
Now, every redundant copy of the data in
the DHT has two authors in its metadata fields -- you and the user
that actually owns the data. Peers validate that piece of data by
saying, "Is agent 0 already the author of this piece of data?
If so,
has agent 0 published an authorisation entry that says that the new
author of this data is allowed to claim/republish it?"
Problems with this approach (not insurmountable):
Agent 0 has to be online all the time cuz they never know when a new
user is going to sign up and try to claim their data. Agent 0 has to
import a ton of data. (I don't think it'd be vastly
time-prohibitive though)
For relational data, there's the chicken-and-egg problem of how to
create links if the data doesn't exist. I'm thinking not of linking
data to data -- that can be done on initial import -- but linking
data to humans, who now have a public key which might not exist on
the DHT yet because they haven't joined the network. That would
always have to happen per-user once they join, and it could create
some cyclic dependency problems.
Anchors
Re: anchors, an anchor is just a pattern that consists of a base and a link -- the base is a simple string, so it's easy for anyone who knows the string to find it by hash. It acts as, well, an anchor to hang links off of. That's why I'm recommending using it to connect legacy user IDs to pieces of content. You can get sample source code for implementing the anchor pattern at https://github.com/holochain/mixins/tree/master/anchors (note that this is for the legacy version of Holochain, so it's written in JavaScript).
( answer provided by
pauldaoust )
I'm developing an API with Sails, and now I need to securize some variables from an entity. Those variable will be accesed only from Admin or own user.
I have an structure like this:
Employee (contains your employee records)
fullName
hourlyWage
phoneNumber
accountBank
Location (contains a record for each location you operate)
streetAddress
city
state
zipcode
...
I need to encrypt phonenumber and accountbank, to avoid anyone to see the values of this fields in the DataBase. Only the owner or the admin.
How I can do that? Thanks
You are looking for a way to encrypt data so that people with no required access right could not see it.
The solution for that is not Sails.js specific and Node actually comes with tools to encrypt data :https://nodejs.org/api/crypto.html.
The key rule here is to always keep your secret password safe.
As for integration in your Sails.js application, I would use callbacks in Models. The official documentation provides a good example here : http://sailsjs.org/documentation/concepts/models-and-orm/lifecycle-callbacks
Basically you just define a function that will be called each time the record is about to be created, fetched or updated. You can then apply your encrypt/decrypt functions there.
This will encrypt/decrypt your phone numbers and bank account numbers automatically.
Regarding access control, you can use Sails' policies along with authentication to determine if the client has the right to access the resource. If not you can always remove attributes from the response sent back to the client.
My app has the ability of sharing its content between different instances of the app i.e. there is a button that lets me attach a document to an email and send it off to another user of the app. When they receive this file it opens up in their instance of the app. This is all working.
However, during the import of this data file, I need the app to add address book records to the address book unless the email address is already in the address book then it must just return the ABRecordRef.
I need to decide which approach is more efficient:
A - Loop through the entire address book creating an array of user defined objects with name and email address (which is all I require) and ABRecordRef. Then when the app is reading the attachment file XML it must check this NSArray each time.
B - Access the address book every time I encounter a contact in the attachment XML and search for it based on email address e.g. ABAddressBookCopyArrayOfAllPeople
Any other ideas?
Note: this applies to searching by e-mail address. If you are searching by name this does not apply.
For an arbitrarily sized address book with a fixed size number of addresses to lookup, searching the address book will be faster. This is because the initial cost of putting all the addresses into a hash is guaranteed to take at least linear (O(n)) time with respect to the number of addresses in the book while (assuming the address book is at least moderately efficien) lookup should be either logarithmic (O(ln(n)) or constant time (O(x)) depending on the implementation since you have a fixed number of addresses to check.
Edit:
A brief survey of the address book api shows that you can't simply "search the address book", you have to make a copy and then filter it.
Using Record Identifiers
Every record in the Address Book database has a unique record identifier. This identifier always refers to the same record, unless that record is deleted or the MobileMe sync data is reset. Record identifiers can be safely passed between threads. They are not guaranteed to remain the same across devices.
The recommended way to keep a long-term reference to a particular record is to store the first and last name, or a hash of the first and last name, in addition to the identifier. When you look up a record by ID, compare the record’s name to your stored name. If they don’t match, use the stored name to find the record, and store the new ID for the record.
To get the record identifier of a record, use the function ABRecordGetRecordID. To find a person record by identifier, use the function ABAddressBookGetPersonWithRecordID. To find a group by identifier, use the function ABAddressBookGetGroupWithRecordID. To find a person record by name, use the function ABAddressBookCopyPeopleWithName.
Given the limitations of the address book in iOS, copying the address book into a NSDictionary is going to be faster than trying to search each time.
Assuming you are fine with overwriting on email address collisions, I would create a dictionary with the email address as the key and the ABRecordRef stored as a NSNumber for the object.
I would do all this on a background queue and then monitor for address book changes and reload the dictionary as needed.
We've encountered users with several thousand entries in their address books. In those cases, you may want to create a record object and store it in Core Data. By filtering on the last modified date, you can determine whether or not to update the email addresses for a given record.