I have a folder which has log files from June to now. I want to retrieve files created in the last week of August and store them at a different path. I can get the creation date from the filename which is in this format:
Run_Merge_BJDSBC_20190901-093
I want to code this in python, so far I have reached here:
for filename in glob.glob(r"C:\Users\chke01\Desktop\PentahoLogs\BAF\*201908[0-9]*.log"):
But I dont know how to select these filenames and write to another folder. Can someone help me here
glob.glob('path') gives you a list of files. You can iterate over that list and use the shutil module to move and rename the files.
for file in glob.glob('*'):
shutil.move(file, new_folder_path)
Related
I am trying to loop through multiple folders and subfolders in Azure Blob container and read multiple xml files.
Eg: I have files in YYYY/MM/DD/HH/123.xml format
Similarly I have multiple sub folders under month, date, hours and multiple XML files at last.
My intention is to loop through all these folder and read XML files. I have tried using few Pythonic approaches which did not give me the intended result. Can you please help me with any ideas in implementing this?
import glob, os
for filename in glob.iglob('2022/08/18/08/225.xml'):
if os.path.isfile(filename): #code does not enter the for loop
print(filename)
import os
dir = '2022/08/19/08/'
r = []
for root, dirs, files in os.walk(dir): #Code not moving past this for loop, no exception
for name in files:
filepath = root + os.sep + name
if filepath.endswith(".xml"):
r.append(os.path.join(root, name))
return r
The glob is a python function and it won't recognize the blob folders path directly as code is in pyspark. we have to give the path from root for this. Also, make sure to specify recursive=True in that.
For Example, I have checked above pyspark code in databricks.
and the OS code as well.
You can see I got the no result as above. Because for the above, we need to give the absolute root. it means the root folder.
glob code:
import glob, os
for file in glob.iglob('/path_from_root_to_folder/**/*.xml',recursive=True):
print(file)
For me in databricks the root to access is /dbfs and I have used csv files.
Using os:
You can see my blob files are listed from folders and subfolders.
I have used databricks for my repro after mounting. Wherever you are trying this code in pyspark, make sure you are giving the root of the folder in the path. when using glob, set the recursive = True as well.
There is an easier way to solve this problem with PySpark!
The tough part is all the files have to have the same format. In the Azure databrick's sample directory, there is a /cs100 folder that has a bunch of files that can be read in as text (line by line).
The trick is the option called "recursiveFileLookup". It will assume that the directories are created by spark. You can not mix and match files.
I added to the data frame the name of the input file for the dataframe. Last but not least, I converted the dataframe to a temporary view.
Looking at a simple aggregate query, we have 10 unique files. The biggest have a little more than 1 M records.
If you need to cherry pick files for a mixed directory, this method will not work.
However, I think that is an organizational cleanup task, versus easy reading one.
Last but not least, use the correct formatter to read XML.
spark.read.format("com.databricks.spark.xml")
I frequent a real estate website that shows recent transactions, from which I will download data to parse within a Pandas dataframe. Everything about this dataset remains identical every time I download it (regarding the column names, that is).
The name of the Excel output may change, though. For example, if I already have download a few of these in my Downloads folder, the file that's exported may read "Generic_File_(3)" or "Generic_File_(21)" if I already have a few older "Generic_File" exports in that folder from a previous export.
Ideally, I'd like my workflow to look like this: export this Excel file of real estate sales, then run a Python script to read in the most recent export as a Pandas dataframe. The catch is, I don't want to have to go in and change the filename in the script to match the appending number of the Excel export everytime. I want the pd.read_excel method to simply read the "Generic_File" that is appended with the largest number (which will obviously correspond to the most rent export).
I suppose I could always just delete old exports out of my Downloads folder so the newest, freshest export is always named the same ("Generic_File", in this case), but I'm looking for a way to ensure I don't have to do this. Are wildcards the best path forward, or is there some other method to always read in the most recently downloaded Excel file from my Downloads folder?
I would use the OS package and create a method to read to file names in the downloads folder. Parsing string filenames you could then find the file following your specified format with the highest copy number. Something like the following might help you get started.
import os
downloads = os.listdir('C:/Users/[username here]/Downloads/')
is_file = [True if '.' in item else False for item in downloads]
files = [item for keep, item in zip(is_file, downloads) if keep]
** INSERT CODE HERE TO IDENTIFY THE FILE OF INTEREST **
Regex might be the best way to find matches if you have a diverse listing of files in your downloads folder.
I need to get last modified dates of all Folders and Files in DBFS mount point (of ADLS Gen1) under Azure Databricks.
Folder structure is like:
Not containing any files, Empty folders:
/dbfs/mnt/ADLS1/LANDING/parent/child/subfolder1
/dbfs/mnt/ADLS1/LANDING/parent/child/subfolder2/subfolder3
Containing some files:
/dbfs/mnt/ADLS1/LANDING/parent/XYZ/subfolder4/File1.txt
/dbfs/mnt/ADLS1/LANDING/parent/XYZ/subfolder5/subfolder6/File2.txt
Used following Python code to get last modified date:
root_dir = "/dbfs/mnt/ADLS1/LANDING/parent"
def get_directories(root_dir):
for child in Path(root_dir).iterdir():
if child.is_file():
print(child, datetime.fromtimestamp(getmtime(child)).date())
else:
print(child, datetime.fromtimestamp(getmtime(child)).date())
get_directories(child)
From above code, I am getting correct modified date for all folders containing files.
But for empty folders, it is giving current date. Not last modified date.
Whereas, when I hardcode the path for empty folder, it is giving correct modified date:
print(datetime.fromtimestamp(getmtime("/dbfs/mnt/ADLS1/LANDING/parent/child/subfolder1")).date())
Can someone please help me out, what am I missing here in loop?
Seems, the issue was with processing time.
I given a wait time : time.sleep(.000005).
It worked as expected.
I am attempting to move a couple thousand pdfs from one file location to another. The source folder contains multiple subfolders and I am combining just the pdfs (technical drawings) into one folder to simplify searching for the rest of my team.
The main goal is to only copy over files that do not already exist in the destination folder. I have tried a couple different options, most recently what is shown below, and in all cases, every file is copied every time. Prior to today, any time I attempted a bulk file move, I would received errors if the file existed in the destination folder but I no longer do.
I have verified that some of the files exist in both locations but are still being copied. Is there something I am missing or can modify to correct?
Thanks for the assistance.
import os.path
import shutil
source_folder = os.path.abspath(r'\\source\file\location')
dest_folder = os.path.abspath(r'\\dest\folder\location')
for folder, subfolders, files in os.walk(source_folder):
for file in files:
path_file=os.path.join(folder, file)
if os.path.exists(file) in os.walk(dest_folder):
print(file+" exists.")
if not os.path.exists(file) in os.walk(dest_folder):
print(file+' does not exist.')
shutil.copy2(path_file, dest_folder)
os.path.exists returns a Boolean value. os.walk creates a generator which produces triples of the form (dirpath, dirnames, filenames). So, that first conditional will never be true.
Also, even if that conditional were correct, your second conditional has a redundancy since it's merely the negation of the first. You could replace it with else.
What you want is something like
if file in os.listdir(dest_folder):
...
else:
...
I have a requirement to copy few files from an ADLS Gen1 location to another ADLS Gen1 location, but have to create folder based on file name.
I am having few files as below in the source ADLS:
ABCD_20200914_AB01_Part01.csv.gz
ABCD_20200914_AB02_Part01.csv.gz
ABCD_20200914_AB03_Part01.csv.gz
ABCD_20200914_AB03_Part01.json.gz
ABCD_20200914_AB04_Part01.json.gz
ABCD_20200914_AB04_Part01.csv.gz
Scenario-1
I have to copy these files into destination ADLS as below with only csv file and create folder from file name (If folder exists, copy to that folder) :
AB01-
|-ABCD_20200914_AB01_Part01.csv.gz
AB02-
|-ABCD_20200914_AB02_Part01.csv.gz
AB03-
|-ABCD_20200914_AB03_Part01.csv.gz
AB04-
|-ABCD_20200914_AB04_Part01.csv.gz
Scenario-2
I have to copy these files into destination ADLS as below with only csv and json files and create folder from file name (If folder exists, copy to that folder):
AB01-
|-ABCD_20200914_AB01_Part01.csv.gz
AB02-
|-ABCD_20200914_AB02_Part01.csv.gz
AB03-
|-ABCD_20200914_AB03_Part01.csv.gz
|-ABCD_20200914_AB03_Part01.json.gz
AB04-
|-ABCD_20200914_AB04_Part01.csv.gz
|-ABCD_20200914_AB04_Part01.json.gz
Is there any way to achieve this in Data Factory?
Appreciate any leads!
So I am not sure if this will entirely help, but I had a similar situation where we have 1 zip file and I had to copy those files out into their own folders.
So what you can do is use parameters in the datasink that you would be using, plus a variable activity where you would do a substring.
The job below is more for the delta job, but I think has enough stuff in it to hopefully help. My job can be divided into 3 sections.
The first Orange section gets the latest file name date from ADLS gen 1 folder that you want to copy.
It is then moved to the orange block. On the bottom I get the latest file name based on the ADLS gen 1 date and then I do a sub-string where I take out the date portion of the file. In your case you might be able to do an array and capture all of the folder names that you need.
Getting file name
Getting Substring
On the top section I get first extract and unzip that file into a test landing zone.
Source
Sink
I then get the names of all the files that were in that zip file to them be used in the ForEach Activity. These file names will then become folders for the copy activity.
Get File names from initial landing zone:
I then pass on those childitems from "Get list of staged files" into ForEach:
In that ForEach activity I have one copy activity. For that I made to datasets. One to grab the files from the initial landing zone that we have created. For this example lets call it Staging (forgive the ms paint drawing):
The purpose of this is to go to that dummy folder and grab each file that was just copied into there. From that 1 zip file we expect 5 files.
In the Sink section what I did is create a new dataset with a parameter for folder and file name. In that dataset I have am putting that data into same container, but created a new folder called "Stage" and concatenated it with the item name. I also added a "replace" command to remove the ".txt" from the file name.
What this will do then is what ever the file name that is coming from that dummy staging it will then have a folder name specifically for each file. Based on your requirements I am not sure if that is what you want to do, but you can always rework that to be more specific.
For Item name I basically get the same file name, then replace the ".txt", concat the name of the date value, and only after that add the ".txt" extension. Otherwise I would have had to ".txt" in the file name.
In the end I have created a delete activity that will then be used to delete all the files (I am not sure if have set that up properly so feel free to adjust obviously).
Hopefully the description above gave you an idea on how to use parameters for your files. Let me know if this helps you in your situation.