What is the preferred/ usual way of storing data that is entered by the user when running a Python script, if I need the data again the next time the script runs?
For example, my script performs calculations based on what the user enters and then when the user runs the script again, it fetches the result from the last run.
For now, I write the data to a text file and read it from there. I don't think that I would need to store very large records ( less than 100, I'd say).
I am targeting Windows and Linux users both with this script, so a cross platform solution would be good. My only apprehension with using a text file is that I feel it might not be the best and the usual way of doing it.
So my question is, if you ever need to store some data for your script, how do you do it?
you could use a slite database or a CSV file. They are both very easy to work with but lend themselves to rows with the same type of information.
The best option might be shelve module
import shelve
shelf = shelve.open(filename)
shelf['key1'] = value1
shelf['key2'] = value2
shelf.close()
# next run
shelf.open(filename)
value1 = shelf['key1']
#etc
For small amounts of data, Python's pickle module is great for stashing away data you want easy access to later--just pickle the data objects from memory and write to a (hidden) file in the user's home folder (good for Linux etc.) or Application Data (on Windows).
Of, as #aaronnasterling mentioned, a sqlite3 file-based database is small, fast and easy that it's no wonder that so many popular programs like Firefox and Pidgin use it.
For 100 lines, plain text is fine with either the standard ConfigParser or csv modules.
Assuming your data structure is simple, text affords opportunities (e.g. grep, vi, notepad) that more complex formats preclude.
Since you only need the last result, just store the result in a file.
Example
write('something', wb)
It will only store the last result. Then when you re-run the script, do a open and read the previous result.
Related
I'm trying to record some stats on a script I'm running in python (a few percentages, less than 12 characters worth). I want it to be efficient. I want the stats to keep being updated as the script runs so that if the script were to exit I still have the stats available to be updated when I run the script again.
I've thought of ways such as recording in a csv (seems inefficient since there looks to be no functionality to keep updating the same row ), updating the title of a file within the system. But can think of nothing which is as clean and efficient as I was hoping. Any ideas?
You could store it in a .txt file if you'd like really, or anything. Using the built in module for .csv files in Python, overwriting rows directly - rather than having to recreate the file - isn't possible AFAIK. Check out the sqlite3 module for storing the information in a database.
https://docs.python.org/3/library/sqlite3.html
I have first file (data.py):
database = {
'school': 2,
'class': 3
}
my second python file (app.py)
import data
del data.database['school']
print(data.database)
>>>{'class': 3}
But in data.py didn't change anything? Why?
And how can I change it from my app.py?
del data.database['school'] modifies the data in memory, but does not modify the source code.
Modifying a source code to manage the persistence of your data is not a good practice IMHO.
You could use a database, a csv file, a json file ...
To elaborate on Gelineau's answer: at runtime, your source code is turned into a machine-usable representation (known as "bytecode") which is loaded into the process memory, then executed. When the del data.database['school'] statement (in it's bytecode form) is executed, it only modifies the in-memory data.database object, not (hopefully!) the source code itself. Actually, your source code is not "the program", it's a blueprint for the runtime process.
What you're looking for is known as data persistance (data that "remembers" it's last known state between executions of the program). There are many solutions to this problem, ranging from the simple "write it to a text or binary file somewhere and re-read it at startup" to full-blown multi-servers database systems. Which solution is appropriate for you depends on your program's needs and constraints, whether you need to handle concurrent access (multiple users / processes editing the data at the same time), etc etc so there's really no one-size-fits-all answers. For the simplest use cases (single user, small datasets etc), json or csv files written to disk or a simple binary key:value file format like anydbm or shelve (both in Python's stdlib) can be enough. As soon as things gets a bit more complex, SQL databases are most often your best bet (no wonder why they are still the industry standard and will remain so for long years).
In all cases, data persistance is not "automagic", you will have to write quite some code to make sure your changes are saved in timely manner.
As what you are trying to achieve is basically related to file operation.
So when you are importing data , it just loads instanc of your file in memory and create a reference from your new file, ie. app.py. So, if you modify it in app.py its just modifiying the instance which is in RAM not in harddrive where your actual file is stored in harddrive.
If you want to change source code of another file "As its not good practice" then you can use file operations.
I am in the process of writing a program and need some guidance. Essentially, I am trying to determine if a file has some marker or flag attached to it. Sort of like the attributes for a HTTP Header.
If such a marker exists, that file will be manipulated in some way (moved to another directory).
My question is:
Where exactly should I be storing this flag/marker? Do files have a system similar to HTTP Headers? I don't want to access or manipulate the contents of the file, just some kind of property of the file that can be edited without corrupting the actual file--and it must be rather universal among file types as my potential domain of file types is unbound. I have some experience with Web APIs so I am familiar with HTTP Headers and json. Does any similar system exist for local files in windows? I am especially interested in anyone who has professional/industry knowledge of common techniques that programmers use when trying to store 'meta data' in files in order to access them later. Or if anyone knows of where to point me, as I am unsure to what I should be researching.
For the record, I am going to write a program for Windows probably using Golang or Python. And the files I am going to manipulate will be potentially all common ones (.docx, .txt, .pdf, etc.)
Metadata you wish to add is best kept in a separate file or database for all files.
Or in another file with same name and different extension or prefix, that you can make hidden.
Relying on a file system is very tricky and your data will be bound by the restrictions and capabilities of the file system your file is stored on.
And, you cannot count on your data remaining intact as any application may wish to change these flags.
And some of those have very specific, clearly defined use, such as creation time, modification time, access time...
See, if you need only flagging the document, you may wish to use creation time, which will stay unchanged through out the live of this document (until is copied) to store your flags. :D
Very dirty business, unprofessional, unreliable and all that.
But it's a solution. Poor one, but exists.
I do not know that FAT32 or NTFS file systems support any extra bits for flagging except those already used by the OS.
Unixes EXT family FS's do support some extra bits. And even than you should be careful in case some other important application makes use of them for something.
Mac OS may support some metadata by itself, but I am not 100% sure.
On Windows, you have one more option to associate more data with a file, but I wouldn't use that as well.
Well, NTFS file system (FAT doesn't support that) has a feature called streams.
In essential, same file can have multiple data streams under itself. I.e. You have more than one file contents under same file node.
To be more clear. Same file contains two different files.
When you open the file normally only main stream is visible to the application. Applications must check whether the other streams are present and choose the one they want to follow.
So, you may choose to store metadata under the second stream of the file.
But, what if all streams are taken?
Even more, anti-virus programs may prevent you access to the metadata out of paranoya, or at least ask for a permission.
I don't know why MS included that option, probably for file duplication or something, but bad hackers made use of the fact that you can store some data, under existing regular file, that nobody is aware of.
Imagine a virus writing it's copy into another stream of one of programs already there.
All that is needed for it to start, instead of your old program next time you run it is a batch script added to task scheduler that flips two streams making the virus data the main one.
Nasty trick! So when this feature started to be abused, anti-virus software started restricting files with multiple streams, so it's like this feature doesn't exist.
If you want to add some metadata using OS's technology, use Windows registry,
but even that is unwise.
What to tell you?
Don't add metadata to files, organize a separate file, or index your data in special files with same name as the file you are refering to and in same folder.
If you are dealing with binary files like docx and pdf, you're best off storing the metadata in seperate files or in a sqlite file.
Metadata is usually stored seperate from files, in data structures called inodes (at least in Unix systems, Windows probably has something similar). But you probably don't want to get that deep into the rabbit hole.
If your goal is to query the system based on metadata, then it would be easier and more efficient to use something SQLite. Having the meta data in the file would mean that you would need to open the file, read it into memory from disk, and then check the meta data - i.e slower queries.
If you don't need to query based on metadata, then storing metadata in the file might make sense. It would reduce the dependencies in your application, but in order to access the contents of the file through Word or Adobe Reader, you'd need to strip the metadata before handing it off to the application. Not worth the hassle, usually
Is there any way of keeping a result variable in memory so I don't have to recalculate it each time I run the beginning of my script?
I am doing a long (5-10 sec) series of the exact operations on a data set (which I am reading from disk) every time I run my script.
This wouldn't be too much of a problem since I'm pretty good at using the interactive editor to debug my code in between runs; however sometimes the interactive capabilities just don't cut it.
I know I could write my results to a file on disk, but I'd like to avoid doing so if at all possible. This should be a solution which generates a variable the first time I run the script, and keeps it in memory until the shell itself is closed or until I explicitly tell it to fizzle out. Something like this:
# Check if variable already created this session
in_mem = var_in_memory() # Returns pointer to var, or False if not in memory yet
if not in_mem:
# Read data set from disk
with open('mydata', 'r') as in_handle:
mytext = in_handle.read()
# Extract relevant results from data set
mydata = parse_data(mytext)
result = initial_operations(mydata)
in_mem = store_persistent(result)
I've an inkling that the shelve module might be what I'm looking for here, but looks like in order to open a shelve variable I would have to specify a file name for the persistent object, and so I'm not sure if it's quite what I'm looking for.
Any tips on getting shelve to do what I want it to do? Any alternative ideas?
You can achieve something like this using the reload global function to re-execute your main script's code. You will need to write a wrapper script that imports your main script, asks it for the variable it wants to cache, caches a copy of that within the wrapper script's module scope, and then when you want (when you hit ENTER on stdin or whatever), it calls reload(yourscriptmodule) but this time passes it the cached object such that yourscript can bypass the expensive computation. Here's a quick example.
wrapper.py
import sys
import mainscript
part1Cache = None
if __name__ == "__main__":
while True:
if not part1Cache:
part1Cache = mainscript.part1()
mainscript.part2(part1Cache)
print "Press enter to re-run the script, CTRL-C to exit"
sys.stdin.readline()
reload(mainscript)
mainscript.py
def part1():
print "part1 expensive computation running"
return "This was expensive to compute"
def part2(value):
print "part2 running with %s" % value
While wrapper.py is running, you can edit mainscript.py, add new code to the part2 function and be able to run your new code against the pre-computed part1Cache.
To keep data in memory, the process must keep running. Memory belongs to the process running the script, NOT to the shell. The shell cannot hold memory for you.
So if you want to change your code and keep your process running, you'll have to reload the modules when they're changed. If any of the data in memory is an instance of a class that changes, you'll have to find a way to convert it to an instance of the new class. It's a bit of a mess. Not many languages were ever any good at this kind of hot patching (Common Lisp comes to mind), and there are a lot of chances for things to go wrong.
If you only want to persist one object (or object graph) for future sessions, the shelve module probably is overkill. Just pickle the object you care about. Do the work and save the pickle if you have no pickle-file, or load the pickle-file if you have one.
import os
import cPickle as pickle
pickle_filepath = "/path/to/picklefile.pickle"
if not os.path.exists(pickle_filepath):
# Read data set from disk
with open('mydata', 'r') as in_handle:
mytext = in_handle.read()
# Extract relevant results from data set
mydata = parse_data(mytext)
result = initial_operations(mydata)
with open(pickle_filepath, 'w') as pickle_handle:
pickle.dump(result, pickle_handle)
else:
with open(pickle_filepath) as pickle_handle:
result = pickle.load(pickle_handle)
Python's shelve is a persistence solution for pickled (serialized) objects and is file-based. The advantage is that it stores Python objects directly, meaning the API is pretty simple.
If you really want to avoid the disk, the technology you are looking for is a "in-memory database." Several alternatives exist, see this SO question: in-memory database in Python.
Weirdly, none of the earlier answers here mention simple text files. The OP says they don't like the idea, but as this is becoming a canonical for duplicates which might not have that constraint, this alternative deserves a mention. If all you need is for some text to survive between invocations of your script, save it in a regular text file.
def main():
# Before start, read data from previous run
try:
with open('mydata.txt', encoding='utf-8') as statefile:
data = statefile.read().rstrip('\n')
except FileNotFound:
data = "some default, or maybe nothing"
updated_data = your_real_main(data)
# When done, save new data for next run
with open('mydata.txt', 'w', encoding='utf-8') as statefile:
statefile.write(updated_data + '\n')
This easily extends to more complex data structures, though then you'll probably need to use a standard structured format like JSON or YAML (for serializing data with tree-like structures into text) or CSV (for a matrix of columns and rows containing text and/or numbers).
Ultimately, shelve and pickle are just glorified generalized versions of the same idea; but if your needs are modest, the benefits of a simple textual format which you can inspect and update in a regular text editor, and read and manipulate with ubiquitous standard tools, and easily copy and share between different Python versions and even other programming languages as well as version control systems etc, are quite compelling.
As an aside, character encoding issues are a complication which you need to plan for; but in this day and age, just use UTF-8 for all your text files.
Another caveat is that beginners are often confused about where to save the file. A common convention is to save it in the invoking user's home directory, though that obviously means multiple users cannot share this data. Another is to save it in a shared location, but this then requires an administrator to separately grant write access to this location (except I guess on Windows; but that then comes with its own tectonic plate of other problems).
The main drawback is that text is brittle if you need multiple processes to update the file in rapid succession, and slow to handle if you have lots of data and need to update parts of it frequently. For these use cases, maybe look at a database (probably start with SQLite which is robust and nimble, and included in the Python standard library; scale up to Postgres or etc if you have entrerprise-grade needs).
And, of course, if you need to store native Python structures, shelve and pickle are still there.
This is a os dependent solution...
$mkfifo inpipe
#/usr/bin/python3
#firstprocess.py
complicated_calculation()
while True:
with open('inpipe') as f:
try:
print( exec (f.read()))
except Exception as e: print(e)
$./first_process.py &
$cat second_process.py > inpipe
This will allow you to change and redefine variables in the first process without copying or recalculating anything. It should be the most efficient solution compared to multiprocessing, memcached, pickle, shelve modules or databases.
This is really nice if you want to edit and redefine second_process.py iteratively in your editor or IDE until you have it right without having to wait for the first process (e.g. initializing a large dict, etc.) to execute each time you make a change.
You can do this but you must use a Python shell. In other words, the shell that you use to start Python scripts must be a Python process. Then, any global variables or classes will live until you close the shell.
Look at the cmd module which makes it easy to write a shell program. You can even arrange so that any commmands that are not implemented in your shell get passed to the system shell for execution (without closing your shell). Then you would have to implement some kind of command, prun for instance, that runs a Python script by using the runpy module.
http://docs.python.org/library/runpy.html
You would need to use the init_globals parameter to pass your special data to the program's namespace, ideally a dict or a single class instance.
You could run a persistent script on the server through the os which loads/calcs, and even periodically reloads/recalcs the sql data into memory structures of some sort and then acess the in-memory data from your other script through a socket.
trying to keep it stupidly simple. Is it a bad idea to move a txt file into and out of a python list? the txt files will probably get to about 2-5k entries. what is the preferred method to create a simple flat file databse?
It might or might not be a bad idea. It depends on what you are trying to achieve, how much memory you have and how big those lines are on average. It also depends on what you are doing with that data. Maybe it is worth it to read and process file line by line? In any case, database assumes indexes, what are you going to do with a list of strings without an index? You cannot search it efficiently, for example.
In any case, if you feel like you need a database, take a look at SQLite. It is a small embedded SQL server written in C with Python interface. It is stable and proven to work. For example, it is being used on iPhone in tons of applications.
If you're looking for a very simple file database, maybe you should look at the shelve module. Example usage:
import shelve
with shelve.open("myfile") as mydb:
mydb["0"] = "first value"
mydb["1"] = "second value"
# ...