Skip to main content
###########
## BTEdb ##
###########
BTEdb (Better Than Ethan's database) is a project created because Ethan thought he could write a database in Python, and mine has to be better than his

It is a schemaless database like MongoDB that serializes to JSON. It can either serialize to a file, or an object that you pass it.

An example:

db = BTEdb.Database("filename.json")

Or:

class MyClass:
def seek(self,position,mode):
pass
def truncate(self):
return False
def __init__(self):
self.data = ""
def write(self,data):
self.data = data
def flush(self):
pass
def read(self):
return self.data
def close(self):
pass
MyObject = MyClass()
db = BTEdb.Database(MyObject)

You don't need to specify an object at all when initiating a database, but you will still need to create one. For example:

db = BTEdb.Database("filename.json")

does the same thing as:

db = BTEdb.Database()
db.OpenDatabase("filename.json")

This allows you to switch files on-the-fly

BTEdb also supports pretty-print. Specify any number of spaces for the database to use, for example:

db = BTEdb.Database("filename.json", 4)

or:

db = BTEdb.Database()
db.OpenDatabase("filename.json", 4)


You can safely close file descriptors and return the database to a just-created state like this:

db.Destroy()

Creating a table looks like this:

db.Create("Table name")

If the table exists, it will be truncated

If the table does not exist, most of the following methods will raise a TableDoesNotExistException

Drop the bass:

db.Drop("Table name")

Truncate a table like this:

db.Truncate("Table name")

Dump the entire database:

db.Dump()

Or a specific table:

db.Dump("Table name")

Check if a table exists like this:

db.TableExists("Table name")

Insert like this:

db.Insert("Table name", Username = "Niles", UID = 1000, favColour = 0xffffff)

As with all schemaless databases, you are responsible for sanitizing the input and output to the database. It is entirely possible to store that entry and {x = 12, y = 24, pointColour = "green"} in the same table.

Select data like this:

db.Select("Table name", UID = 1000)

This selects all entries with the UID of 1000 and the favourite colour of white:

db.Select("Table name", UID = 1000, favColour = 0xffffff)

This selects all entries with the favourite colour of white and who has an E in their username, case insensitive:

db.Select("Table name", favColour = 0xffffff, lambda x: "e" in x["username"].lower())

You may use a lambda or a pre-defined function. For example:

import urllib2
def CheckUser(Datapoint):
values = { "UID" : Datapoint["UID"], "username" : Datapoint["username"] }
postdata = urllib2.encode(values)
request = urllib2.Request("http://example.com/CheckUser.php",postdata)
response = request.read()
if response == "User accepted":
return True
else:
return False
db.Select("Table name", CheckUser)

That would query an external server to check the username and UID to determine if each row should be selected or not. Be warned that this will generate a LOT of network traffic

Deleting is similar. The following will delete any user with the UID of 1000:

db.Delete("Table name", UID = 1000)

Lambdas and functions may also be used here.

It is important to note that the first non-keyword argument is the table name. Non-function or lambda non-keyword arguments after the table name will raise a TypeError

Update is a little bit more complicated. Here is an example to get you going

db.Update("Table name", db.Select("Table name", favColour = 0xffffff), UID = 12, Username = "test")

This is the same as the SQL statement:

UPDATE `Table name` SET `UID` = 12, `Username` = 'test' WHERE `favColour` = 0xffffff;

Lambdas may be used in the select statement, but not the update statement. To achieve something similar, you can do this:

for x in db.Select("Table name", favColour = 0xffffff):
db.Update("Table name", [x], UID = x["UID"] + 1)

That would increment the UIDs of every user with the favourite colour of white.

It can also be combined with the Dump method

db.Update("Table name", db.Dump("Table name"), username = "newusername")

That would change every user's username to "newusername"

Saving a savepoint is as easy as this:

db.Save("Savepoint name")

Reverting back to a savepoint:

db.Revert("Savepoint name")

Saving a specific table:

db.Save("Savepoint name", "Table name")

Recovering a specific table from a savepoint:

db.Revert("Savepoint name", "Table name")

Deleting a savepoint

db.RemoveSave("Savepoint name")

If you only saved a few tables, only those tables will be recovered if you attempt to recover the entire save.

You can manually retrieve or insert a savepoint with these methods:

db.GetSave("Savepoint name")
db.GetSave()
db.PutSave(data,"Savepoint name")
db.PutSave(data)

Under most circumstances, you should never need to use those methods. If for some reason you do, DO NOT confuse whether you are putting a save requested with a savepoint name or without one.

Triggers are identified by name, which can be a string, integer, float, or a few other datatypes. The name must be unique, however you may have infinite triggers.

You can add a trigger something like this:

import time
def handler(db, datapoint, table, event):
print("Handler being called on event " + event + " on datapoint " + str(datapoint) + " in table " + table)
db.Save(str(time.time()),table)
db.AddTrigger("Trigger Name", "AFTER UPDATE", "Table name", handler)

That will make any update to something in the "Table name" table print a message and make a new savepoint. Beware that this will run for each individual datapoint.

You may also use lambda expressions.

Valid events are "BEFORE INSERT", "AFTER INSERT", "BEFORE DELETE", "AFTER DELETE", "BEFORE UPDATE" and "AFTER UPDATE"

With INSERT and DELETE, the same datapoint is passed to both BEFORE and AFTER handlers. With UPDATE, the old and new datapoints are passed to the BEFORE and AFTER handlers, respectively.

Remove like this:

db.RemoveTrigger("Trigger name")

You may have multiple handlers for a single event.

Transactions are necessary for an efficient database.

While not inside a transaction, methods that modify the database write out the database to the disk before they return. This is good if you don't have a lot of requests, but if you are going to execute two or more statements that modify data in a row, you should execute them within a transaction.

Begin a transaction like this:

db.BeginTransaction()

However, that will create a savepoint called "transaction". To begin a transaction without that, (you will be unable to revert the transaction) do this:

db.BeginTransaction(False)

To commit the transaction and write to the disk:

db.CommitTransaction()

If you chose to make a save, you can revert a transaction:

db.RevertTransaction()

You can always tell if a transaction is in progress with the boolean value ``db.TransactionInProgress``

Other less used methods:

db.Vacuum() # Forces a write to the disk
db.ListSaves() # Lists savepoints
db.ListTables() # Guess
db.ListTriggers() # Figure it out yourself
db.TriggerExists(name) # Who even reads these

Metadata

Release files for BTEdb 7.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for BTEdb 7.0.1
File Size Uploaded Provenance Actions
BTEdb-7.0.1.tar.gz 7.7 kB Without provenance Details for BTEdb-7.0.1.tar.gz

Built distributions (wheels)

Table of built distributions (wheels) for BTEdb 7.0.1
File Actions
BTEdb-7.0.1-py3.5.egg Legacy Egg format - - Details for BTEdb-7.0.1-py3.5.egg
BTEdb-7.0.1-py3-none-any.whl Python 3 none any Details for BTEdb-7.0.1-py3-none-any.whl
BTEdb-7.0.1-py2.7.egg Legacy Egg format - - Details for BTEdb-7.0.1-py2.7.egg
BTEdb-7.0.1-py2-none-any.whl Python 2 none any Details for BTEdb-7.0.1-py2-none-any.whl

Total release size: 40.1 kB

Release files / BTEdb-7.0.1.tar.gz

Download URL BTEdb-7.0.1.tar.gz
Size 7.7 kB
Tags Source
SHA-256 checksum
How to use checksums
b1609cd70d14c35ed053c802fdf00e747ed693199a58cc5205ea26f1eda47faa
BLAKE2b-256 checksum
How to use checksums
bf0e8aabd72a6d78ec7d32af86d5d7b6f21368fb7a9a2eab63423d08cbd5f312
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / BTEdb-7.0.1-py3.5.egg

Download URL BTEdb-7.0.1-py3.5.egg
Size 10.1 kB
Tags Egg
SHA-256 checksum
How to use checksums
d35e6e00f7a752d50c53d8393491b780411cbce32bbf678c8543809bfe8714ca
BLAKE2b-256 checksum
How to use checksums
924f007cffa2d2983a73066dcd641aeb7205fc7ac19fecf11cce12154f106960
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / BTEdb-7.0.1-py3-none-any.whl

Download URL BTEdb-7.0.1-py3-none-any.whl
Size 6.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
5bb7fe1be99b69bdde184ffb9353fe73c9c4125a746a20b7d74a6250f8260754
BLAKE2b-256 checksum
How to use checksums
f8579c00793b0350b8eba78ad8a4ec813ae06c0652bc308074cb625cec83a702
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / BTEdb-7.0.1-py2.7.egg

Download URL BTEdb-7.0.1-py2.7.egg
Size 9.8 kB
Tags Egg
SHA-256 checksum
How to use checksums
3b321329607ffa3b21f19c01689908f5f64b085d6f570f7961c3edd8bd18e7ff
BLAKE2b-256 checksum
How to use checksums
0f016e27cc1384c67909200f2ef0195cfd6bdc70914ba4f33b4b526ab32d43a2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Release files / BTEdb-7.0.1-py2-none-any.whl

Download URL BTEdb-7.0.1-py2-none-any.whl
Size 6.2 kB
Tags Python 2
SHA-256 checksum
How to use checksums
a7293c7bf5d88e8c616072074f00e64d2455acd3a8bba2ec9777836e097f8cd2
BLAKE2b-256 checksum
How to use checksums
a128324d62cb97a51fa31d5bc68ea777211dd143f14a9b73cb4db7bbc4a51d6a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No

Security for BTEdb 7.0.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page