Comments (7)
from peaks-consolidation.
you can see this example
To support Python:
import peaks as hk
Table = hk.ReadFile("10MillionRows.csv")
Table2 = hk.Distinct("Table | Ledger, Account, PartNo,Project,Contact,Unit Code, D/C,Currency")
FilePath = hk.WriteFile("Table2 | * ~ Peaks-Distinct10.csv")
FilePath2 = hk.WriteFile("Table | Ledger, Account, PartNo,Project,Contact ~ Peaks-Transaction.csv")
where Table is variable which contain a in-memory table, FilePath is a string variable
File type is auto detected by .ext and its bytearray, so no need _csv
To support Web request and Windows/Linux command line (can be ran by script and command line):
ReadFile{10MillionRows.csv ~ Table}
Distinct{Ledger, Account, PartNo,Project,Contact,Unit Code, D/C,Currency ~ Table2}
WriteFile{Table2 | * ~ Peaks-Distinct10.csv}
WriteFile{Table | Ledger, Account, PartNo,Project,Contact ~ Peaks-Transaction.csv}
where the Python Code (" ") is equvalent to the original syntax {}.
And "variable =" is equvalent to the original syntax "~ TableName"
When output table is a file name instead of in-memory table, the variable
will be a string which contain a full file path of the output file.
from peaks-consolidation.
Need to provide a clear naming, and I will request Pandas and Polars to follow the spec of Peaks Framework, to standarsize ETL expression similar to HTML5. And there are room different software developers joining together to create a standardize ETL expression. If only command ReadFile -> Read obviously not an issue, but there are a lot of other ETL expressions. You can have a look on this doc "WebNameSQL.pdf".
from peaks-consolidation.
from peaks-consolidation.
CSV is one of the formats that any dataframe software supports. Other formats include Parquet, Excel, JSON, HTML and more. However, this software is not intended to be another Polars or Pandas. The benchmark test will mainly focus on some of the most common ETL functions such as ReadFile, Select, Distinct, GroupBy, JoinTable, OrderBy, AddColumn, Crosstab and WriteFile. Other functions will be significantly different from Polars or Pandas. Peaks is derived from my previous experience of accounting software and will be extended to support bioinformatics.
You should be an excellent user. Polars is one of my best recommended dataframe software.
from peaks-consolidation.
from peaks-consolidation.
Polars is one of excellent software for you. I shall introduce it for more friends and companies. In fact I have learnt a lot from Polars. I enjoy using it for testing. Previously I reported issues for billion rows testing, subquently the author fix it.
from peaks-consolidation.
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