#!/usr/bin/python
# -*- coding: utf-8 -*-
# ---------------------------------------------------------------------------------------------------------
# Author : Ulrich Carmesin
# Source : gitea.ucarmesin.de
# ---------------------------------------------------------------------------------------------------------
"""
the issue of this tool is to transform extern data to the internal structure and the internal structure into extern data - i.e. mostly test-results.
* * * * * * * *
the testdata have several elements
* parameter (-td --tdata) : to identify which testdata should be loaded
* source (flaskdb: dbname / dir: filename) : always structured in a table (easy to specify) with columns
  * node : where the rows are
  * action : what should be done - default insert
  + fields : dates in relation of a reference<day or a formula
* interface : configured in components and used in comparison with attributes to each field:
  * ignored - if it should be ignored on differences, it is necessary on technical ID-fields
  * id-field - necessary
* * * * * * * *
the testdata itself which are written in different artifacts of modern applications are mostly stored as tree
- so as xml, json, always with plain data in the leaf. So the intern structure should be also a tree - in python: dictionary.
"""
import os.path

import basic.program
import utils.file_tool
import basic.constants as B

DATA_SRC_DIR = "dir"
DATA_SRC_CSV = "csv"

CSV_HEADER_START = ["node", "table", "tabelle"]
CSV_DELIMITER = ";"

CSV_SPECTYPE_DATA = "data"
CSV_SPECTYPE_TREE = "tree"
CSV_SPECTYPE_KEYS = "keys"
CSV_SPECTYPE_CONF = "conf"
CSV_NODETYPE_KEYS = "_keys"

ATTR_SRC_TYPE = "tdtyp"
ATTR_SRC_DATA = "tdsrc"
ATTR_SRC_NAME = "tdname"

def getTdataAttr():
    job = basic.program.Job.getInstance()
    out = {} #
    out[ATTR_SRC_TYPE] = DATA_SRC_DIR
    print("---getTdataAttr")
    print(vars(job.par))
    if hasattr(job.par, B.PAR_TESTCASE):
        out[ATTR_SRC_NAME] = getattr(job.par, B.PAR_TESTCASE)
    elif hasattr(job.par, B.PAR_TESTSUITE):
        out[ATTR_SRC_NAME] = getattr(job.par, B.PAR_TESTSUITE)
    for p in [ATTR_SRC_TYPE, ATTR_SRC_DATA, ATTR_SRC_NAME]:
        # out[p] = ""
        if hasattr(job.par, p):
            out[p] = getattr(job.par, p)
    return out


def getTestdata():
    """
    get the testdata from one of the possible soources
    * dir: each file in the specific testarchiv
    * csv: specific file
    * db:  specific db with a testcase-catalogue
    :return:
    """
    job = basic.program.Job.getInstance()
    #reftyp = getattr(job.par, "tdtyp")
    #source = getattr(job.par, "tdsrc")
    #criteria = getattr(job.par, "tdname")
    tdata = getTdataAttr()   # {"reftyp": reftyp, "source": source, "criteria": criteria}
    print(tdata)
    if tdata[ATTR_SRC_TYPE] == "flaskdb":
        # read data-structure with sourcename
        # connect to source
        # select with all data with datastructure
        job.m.setInfo("Test-Data readed from " + tdata[ATTR_SRC_TYPE] + " for " + tdata[ATTR_SRC_NAME])
    elif tdata[ATTR_SRC_TYPE] == DATA_SRC_CSV:
        # read file in testdata
        job.m.logInfo("Test-Data readed from " + tdata[ATTR_SRC_TYPE] + " for " + tdata[ATTR_SRC_NAME])
    elif tdata[ATTR_SRC_TYPE] == DATA_SRC_DIR:
        filename = os.path.join(job.conf.getJobConf(B.SUBJECT_PATH+":"+B.ATTR_PATH_TDATA), tdata[ATTR_SRC_NAME], "testspec.csv")
        data = getCsvSpec(job.m, filename, CSV_SPECTYPE_DATA)
        for k in data:
            tdata[k] = data[k]
            if (k == "option"):
                for p in data[k]:
                    setattr(job.par, p, data[k][p])
    else:
        job.m.setFatal("test-Data: reftyp " + tdata[ATTR_SRC_TYPE] + " is not implemented")
    return tdata

def getCsvSpec(msg, filename, type):
    """
    get data from a csv-file
    a = field[0] delimited by :
    a) data : like a table with data-array of key-value-pairs
            a_0 is keyword [option, step, CSV_HEADER_START ]
            a_0 : { a_1 : { f_1 : v_1, .... } # option, step
            a_0 : { .. a_n : { _header : [ .. ], _data : [ rows... ] # table, node
    b) tree : as a tree - the rows must be unique identified by the first column
            a_0 is keyword in CSV_HEADER_START
            a_0 : { .. a_n : { _header : [ fields.. ], _data : { field : value }
    c) keys : as a tree - the rows must be unique identified by the first column
            a_0 is keyword in CSV_HEADER_START
            a_1 ... a_n is key characterized by header-field like _fk* or _pk*
            a_0 : { .. a_n : { _keys : [ _fpk*.. ] , _header : [ fields.. ], _data : { pk_0 : { ... pk_n : { field : value }
    d) conf:
            _header : [ field_0, ... ]
            { field_0 : { attr_0 : val_0, .. }, field_1 : { ... }, ... }
    """
    data = {}
    header = []
    h = [] # from a[]
    lines = utils.file_tool.readFileLines(filename, msg)
    status = "start"
    tableDict = {}
    for l in lines:
        print("lines "+l)
        fields = l.split(CSV_DELIMITER)
        # check empty line, comment
        if (len(l.strip().replace(CSV_DELIMITER,"")) < 1):
            status = "start"
            continue
        if (fields[0][0:1] == "#"):
            continue
        a = fields[0].lower().split(":")
        # keywords option, step, table
        if (a[0] not in data):
            data[a[0]] = {}
        if (a[0].lower() == "step"):
            if (not B.DATA_NODE_STEPS in data):
                data[B.DATA_NODE_STEPS] = []
            step = {}
            step[B.DATA_NODE_COMP] = fields[1]
            step[B.ATTR_DATA_REF] = fields[2]
            step[B.ATTR_STEP_ARGS] = {}
            a = fields[3].split(",")
            for arg in a:
                b = arg.split(":")
                step[B.ATTR_STEP_ARGS][b[0]] = b[1]
            data[B.DATA_NODE_STEPS].append(step)
            continue
        elif (a[0].lower() == "option"):
            data[a[0]][a[1]] = fields[1]
            continue
        elif (a[0].lower() in CSV_HEADER_START):
            # create deep structure a_0 ... a_n
            print("tdata 136 CSV_HEADER_START "+str(len(a)))
            h = a
            tableDict = getTabContent(msg, data, h)
            i = 0
            for f in fields:
                i += 1
                if i <= 1:
                    continue
                if len(f) < 1:
                    break
                header.append(f)
            tableDict[B.DATA_NODE_HEADER] = header
            if type == CSV_SPECTYPE_TREE:
                tableDict[B.DATA_NODE_DATA] = {}
            elif type == CSV_SPECTYPE_KEYS:
                tableDict[CSV_NODETYPE_KEYS] = {}
            elif type == CSV_SPECTYPE_CONF:
                tableDict = {}
                headerFields = []
            else:
                tableDict[B.DATA_NODE_DATA] = []
            setTabContent(msg, data, tableDict, h)
            status = CSV_SPECTYPE_DATA
            continue
        elif (status == CSV_SPECTYPE_DATA):
            # check A-col for substructure
            # fill data
            tableDict = getTabContent(msg, data, h)
            row = {}
            i = 1
            # case-differentiation DATA or TREE
            for f in header:
                row[f] = fields[i]
                if type == CSV_SPECTYPE_TREE:
                    tableDict[B.DATA_NODE_DATA][f] = fields[i]
                i += 1
            if type == CSV_SPECTYPE_DATA:
                tableDict[B.DATA_NODE_DATA].append(row)
            elif type == CSV_SPECTYPE_KEYS:
                tableDict[CSV_NODETYPE_KEYS][fields[1]] = row
            elif type == CSV_SPECTYPE_CONF:
                tableDict[fields[1]] = row
                headerFields.append(fields[1])
            setTabContent(msg, data, tableDict, h)
    if (status in [CSV_SPECTYPE_DATA, CSV_SPECTYPE_KEYS]):
        tableDict = getTabContent(msg, data, h)
        if type == CSV_SPECTYPE_DATA:
            tableDict[B.DATA_NODE_HEADER] = headerFields
        setTabContent(msg, data, tableDict, h)
    print("return getCsvSpec "+str(data))
    return data

def setTabContent(msg, data, tabledata, path):
    if len(path) >= 2 and path[1] not in data[path[0]]:
        data[path[0]][path[1]] = {}
    if len(path) >= 3 and path[2] not in data[path[0]][path[1]]:
        data[path[0]][path[1]][path[2]] = {}
    if len(path) >= 4 and path[3] not in data[path[0]][path[1]][path[2]]:
        data[path[0]][path[1]][path[2]][path[3]] = {}
    if len(path) == 2:
        data[path[0]][path[1]] = tabledata
    elif len(path) == 3:
        data[path[0]][path[1]][path[2]] = tabledata
    elif len(path) == 4:
        data[path[0]][path[1]][path[2]][path[3]] = tabledata

def getTabContent(msg, data, path):
    if len(path) >= 2 and path[1] not in data[path[0]]:
        data[path[0]][path[1]] = {}
    if len(path) >= 3 and path[2] not in data[path[0]][path[1]]:
        data[path[0]][path[1]][path[2]] = {}
    if len(path) >= 4 and path[3] not in data[path[0]][path[1]][path[2]]:
        data[path[0]][path[1]][path[2]][path[3]] = {}
    if len(path) == 2:
        return data[path[0]][path[1]]
    elif len(path) == 3:
        return data[path[0]][path[1]][path[2]]
    elif len(path) == 4:
        return data[path[0]][path[1]][path[2]][path[3]]

def readCsv(msg, filename, comp):
    job = basic.program.Job.getInstance()
    verify = -1+job.getDebugLevel("tdata_tool")
    job.debug(verify, "readCsv " + filename)
    fields = []
    nodes = []
    columns = []
    output = {}
    state = 0
    data = []
    cnt = 0
    lines = utils.file_tool.readFileLines(filename, msg)
    basename = os.path.basename(filename)[0:-4]
    startCols = 1
    for line in lines:
        fields = line.split(';')
        testline = line.replace(";", "")
        job.debug(verify, str(state) + " line " + line + " :" + str(len(fields)) + ": " + str(fields))
        if len(testline) < 2 and state < 1:
            state = 0
        elif fields[0].lower() in CSV_HEADER_START:
            state = 2
            columns = []
            cnt = len(fields)
            job.debug(verify, str(state) + " cnt " + str(cnt))
            j = 0
            for i in range(1, cnt-1):
                if fields[0][0:1] == "_":
                    startCols += 1
                    continue
                job.debug(verify, str(i) + " cnt " + str(fields[i]))
                if len(fields[i]) > 0:
                    columns.append(fields[i])
                    j = j + 1
                cnt = j
            job.debug(verify, str(state) + " " + str(cnt) + " cols " + str(columns))
        elif state >= 2 and len(testline) > 2:
            if state == 2 and not fields[0].isspace():
                struct = fields[0].split(":")
                for x in struct:
                    if len(x) > 2:
                        nodes.append(x)
                job.debug(verify, str(state) + " nodes " + str(nodes))
            state = 3
            row = {}
            for i in range(startCols, cnt-1):
                row[columns[i-startCols]] = fields[i]
            job.debug(verify, str(state) + " row " + str(row))
            data.append(row)
        elif state == 3:
            job.debug(verify, "structure " + str(state) + ": " + str(nodes))
            output = setSubnode(0, nodes, data, output)
            data = []
            state = 0
    if len(nodes) < 1:
        nodes.append(basename)
    output = setSubnode(0, nodes, data, output)
    return output

def setSubnode(i, nodes, data, tree):
    print("setSubnode " + str(i) + ": " + ": " + str(tree))
    if i >= len(nodes):
        print("setSubnode a " + str(i))
        tree["_data"] = data
    elif tree is not None and nodes[i] in tree.keys():
        print("setSubnode b " + str(i))
        tree[nodes[i]] = setSubnode(i+1, nodes, data, tree[nodes[i]])
    else:
        print("setSubnode c " + str(i))
        tree[nodes[i]] = setSubnode((i + 1), nodes, data, {})
    return tree

def getDataStructure(comp):
    # gets data-structure from the vml in the component-folder
    job = basic.program.Job.getInstance()
    verify = -1+job.getDebugLevel("tdata_tool")
    job.debug(verify, "getDataStructure " + comp)

def normalizeDataRow(dstruct, xpathtupel, row, referencedate):
    # normalize data of the row if necessary
    # raw-value is saved as new field with _raw as suffix
    job = basic.program.Job.getInstance()
    verify = -1+job.getDebugLevel("tdata_tool")
    job.debug(verify, "calcDataRow " + row)

def writeCsvData(filename, tdata, comp):
    """
    writes the testdata into a csv-file for documentation of the test-run
    :param teststatus:
    :param tdata:
    :param comp: if specific else None
    :return:
    """
    job = basic.program.Job.getInstance()
    verify = -1+job.getDebugLevel("tdata_tool")
    job.debug(verify, "writeDataTable " + str(comp))
    text = "table"
    for f in tdata[B.DATA_NODE_HEADER]:
        text += ";"+f
    for r in tdata[B.DATA_NODE_DATA]:
        text += "\n"
        for f in tdata[B.DATA_NODE_HEADER]:
            if f in r:
                text += ";"+str(r[f])
            else:
                text += ";"
    text += "\n"
    utils.file_tool.writeFileText(comp.m, filename, text)