revnext 0.1.5

Revolution Next (*.revolutionnext.com.au) report downloads via REST API

revnext

Download Revolution Next (*.revolutionnext.com.au) reports (Parts Price List, Parts by Bin Location) via REST API. Uses auto-login and saves the session to disk so the next run reuses it; if the session is invalid, it logs in again automatically.

• Install: pip install revnext
• Editable (from repo root): pip install -e ./packages/revnext

Configuration (.env)

Put your base URL, username, and password in a .env file (e.g. in the project root or cwd). Optional: use python-dotenv so RevNextConfig.from_env() loads it.

Variable	Required	Description
REVNEXT_URL	Yes	Full base URL (e.g. https://yourtenant.revolutionnext.com.au)
REVNEXT_USERNAME	Yes	RevNext login User ID
REVNEXT_PASSWORD	Yes	RevNext login Password
REVNEXT_SESSION_PATH	No	Where to save/load session cookies (default: .revnext-session.json in cwd)

Example .env:

REVNEXT_URL=https://yourtenant.revolutionnext.com.au
REVNEXT_USERNAME=your_user_id
REVNEXT_PASSWORD=your_password

The first run logs in via the web form (CSRF + j_spring_security_check) and saves the session to REVNEXT_SESSION_PATH or .revnext-session.json. Later runs load that file, check that the session is still valid, and only re-login if it has expired.

Parts reports

Two report types are supported:

Report	Function	Params class
Parts by Bin Location	download_parts_by_bin_report()	PartsByBinLocationParams
Parts Price List	download_parts_price_list_report()	PartsPriceListParams

Use the params class to set company, division, department, filters (franchise, bin, stock type, etc.) when you need non-defaults. Pass an instance as report_params=...; if omitted, defaults are used.

Parts enquiries – supplier part

Search for supplier parts by part number and load full part data (e.g. dimensions, weight, price) from the Supplier Part enquiry. Import from revnext.parts or revnext.parts.enquiries.supplier_part:

from revnext.common import get_or_create_session
from revnext.parts.enquiries.supplier_part import (
    GET_RESULTS_SERVICE,
    load_supplier_part,
    search_supplier_parts,
)

config = RevNextConfig.from_env()
session = get_or_create_session(config, GET_RESULTS_SERVICE)

# Search by part number (e.g. PZQ6160670)
rows = search_supplier_parts(session, config.base_url, "PZQ6160670")
# Each row has x_rowid, supid, supprt, prtdsc, supprc, spnam, etc.

# Load full part for one supplier (e.g. Toyota supid 7001)
row = next(r for r in rows if r.get("supid") == "7001")
part = load_supplier_part(session, config.base_url, row["x_rowid"])
# part has prtid, prtdsc, prtlen, prtwdt, prthgt, prtvol, prtwgt, supprc, etc. (with untlen, untwdt, unthgt, untvol, untwgt for units)

Quick start

from pathlib import Path
from revnext import download_parts_by_bin_report, download_parts_price_list_report

# Config from env (.env or REVNEXT_*)
path1 = download_parts_by_bin_report(
    output_path=Path("C:/Reports/parts_by_bin.csv"),
)
path2 = download_parts_price_list_report(
    output_path=Path("C:/Reports/parts_price_list.csv"),
)

Return data in memory (e.g. for pandas)

Use return_data=True to get the CSV content as bytes without saving a file. Load into pandas with io.BytesIO:

import io
import pandas as pd
from revnext import download_parts_by_bin_report, download_parts_price_list_report

# Get report as bytes, then load into a DataFrame
csv_bytes = download_parts_by_bin_report(return_data=True)
df = pd.read_csv(io.BytesIO(csv_bytes))

# Or save to file yourself later
# Path("reports/parts_by_bin.csv").write_bytes(csv_bytes)

When return_data=True, the function returns bytes; when return_data=False (default), it saves to output_path and returns the Path.

Download one report with explicit config

from pathlib import Path
from revnext import RevNextConfig, download_parts_by_bin_report, download_parts_price_list_report

config = RevNextConfig.from_env()  # or RevNextConfig( base_url="...", username="...", password="...", session_path=... )

path1 = download_parts_by_bin_report(
    config=config,
    output_path=Path("C:/Reports/parts_by_bin.csv"),
)
path2 = download_parts_price_list_report(
    config=config,
    output_path=Path("C:/Reports/parts_price_list.csv"),
)

Example: download both reports (implement in your project)

from pathlib import Path
from typing import Optional

from revnext import RevNextConfig, download_parts_by_bin_report, download_parts_price_list_report


def download_all_reports(
    config: Optional[RevNextConfig] = None,
    output_dir: Optional[Path | str] = None,
) -> list[Path]:
    """Run both reports and save CSVs. Returns the list of paths where files were saved."""
    config = config or RevNextConfig.from_env()
    output_dir = Path(output_dir) if output_dir is not None else Path.cwd()
    path1 = download_parts_by_bin_report(
        config=config,
        output_path=output_dir / "Parts_By_Bin_Location.csv",
    )
    path2 = download_parts_price_list_report(
        config=config,
        output_path=output_dir / "Parts_Price_List.csv",
    )
    return [path1, path2]

Example: download both reports in parallel

from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from typing import Optional

from revnext import RevNextConfig, download_parts_by_bin_report, download_parts_price_list_report


def download_all_reports_parallel(
    config: Optional[RevNextConfig] = None,
    output_dir: Optional[Path | str] = None,
) -> list[Path]:
    """Run both reports in parallel. Returns the list of paths where files were saved."""
    config = config or RevNextConfig.from_env()
    output_dir = Path(output_dir) if output_dir is not None else Path.cwd()
    path1 = output_dir / "Parts_By_Bin_Location.csv"
    path2 = output_dir / "Parts_Price_List.csv"
    with ThreadPoolExecutor(max_workers=2) as executor:
        f1 = executor.submit(
            download_parts_by_bin_report,
            config=config,
            output_path=path1,
        )
        f2 = executor.submit(
            download_parts_price_list_report,
            config=config,
            output_path=path2,
        )
        return [f1.result(), f2.result()]

See the main repo README for the monorepo layout.