Quick CSV
Read and write small or large CSV/TXT files in a simple manner
Installation
pip install quick-csv
Examples for small files
Example 1: read and write csv or txt files
from quickcsv.file import *
# read a csv file
list_model=read_csv('data/test.csv')
for idx,model in enumerate(list_model):
print(model)
list_model[idx]['id']=idx
# save a csv file
write_csv('data/test1.csv',list_model)
# write a text file
write_text('data/text1.txt',"Hello World!")
# read a text file
print(read_text('data/text1.txt'))Example 2: create dataframe from a list of models
from quickcsv.file import *
# read a csv file
list_model=read_csv('data/test.csv')
# create a dataframe from list_model
df=create_df(list_model)
# print
print(df)Examples for large files
Example 1: read large csv file
from quickcsv.largefile import *
if __name__=="__main__":
csv_path=r"umls_atui_rels.csv" # a large file (>500 MB)
total_count=0
def process_partition(part_df,i):
print(f"Part {i}")
def process_row(row,i):
global total_count
print(i)
total_count+=1
list_results=read_large_csv(csv_file=csv_path,row_func=process_row,partition_func=process_partition)
print("Return: ")
print(list_results)
print("Total Record Num: ",total_count)Example 2: query from a large csv file
from quickcsv.largefile import *
if __name__=="__main__":
csv_path=r"umls_sui_nodes.csv" # a large file (>500 MB)
total_count=0
# process each partition in the large file
def process_partition(part_df,i):
print(f"Part {i}")
print()
# process each row in a partition while reading
def process_row(row,i):
global total_count
print(row)
total_count+=1
# field is a field in the csv file, and value is the value you need to find within the csv file
list_results=read_large_csv(csv_file=csv_path, field="SUI",value="S0000004", append_row=True, row_func=process_row,partition_func=process_partition)
print("Return: ")
print(list_results)
print("Total Record Num: ",total_count)Example 3: read top N records from the large csv file
from quickcsv.largefile import *
if __name__=="__main__":
csv_path=r"umls_atui_rels.csv"
total_count=0
# return top 10 rows in the csv file
list_results=read_large_csv(csv_file=csv_path,head_num=10)
print("Return: ")
print(list_results)
print("Total Record Num: ",total_count)License
The quick-csv project is provided by Donghua Chen.
