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@ -34,6 +34,7 @@ CSV_DELIMITER = ";" |
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CSV_SPECTYPE_DATA = "data" |
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CSV_SPECTYPE_TREE = "tree" |
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CSV_SPECTYPE_KEYS = "keys" |
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ATTR_SRC_TYPE = "tdtyp" |
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ATTR_SRC_DATA = "tdsrc" |
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@ -43,10 +44,15 @@ def getTdataAttr(): |
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job = basic.program.Job.getInstance() |
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out = {} # |
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out[ATTR_SRC_TYPE] = DATA_SRC_DIR |
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print("---getTdataAttr") |
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print(vars(job.par)) |
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if hasattr(job.par, B.PAR_TESTCASE): |
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out[ATTR_SRC_NAME] = getattr(job.par, B.PAR_TESTCASE) |
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elif hasattr(job.par, B.PAR_TESTSUITE): |
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out[ATTR_SRC_NAME] = getattr(job.par, B.PAR_TESTSUITE) |
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for p in [ATTR_SRC_TYPE, ATTR_SRC_DATA, ATTR_SRC_NAME]: |
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out[p] = "" |
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if getattr(job.par, p): |
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# out[p] = "" |
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if hasattr(job.par, p): |
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out[p] = getattr(job.par, p) |
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return out |
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@ -60,10 +66,11 @@ def getTestdata(): |
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:return: |
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""" |
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job = basic.program.Job.getInstance() |
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reftyp = getattr(job.par, "tdtyp") |
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source = getattr(job.par, "tdsrc") |
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criteria = getattr(job.par, "tdname") |
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#reftyp = getattr(job.par, "tdtyp") |
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#source = getattr(job.par, "tdsrc") |
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#criteria = getattr(job.par, "tdname") |
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tdata = getTdataAttr() # {"reftyp": reftyp, "source": source, "criteria": criteria} |
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print(tdata) |
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if tdata[ATTR_SRC_TYPE] == "flaskdb": |
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# read data-structure with sourcename |
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# connect to source |
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@ -84,13 +91,25 @@ def getTestdata(): |
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def getCsvSpec(msg, filename, type): |
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""" |
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get data from a csv-file |
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a = field[0] delimited by : |
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a) data : like a table with data-array of key-value-pairs |
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a_0 is keyword [option, step, CSV_HEADER_START ] |
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a_0 : { a_1 : { f_1 : v_1, .... } # option, step |
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a_0 : { .. a_n : { _header : [ .. ], _data : [ rows... ] # table, node |
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b) tree : as a tree - the rows must be unique identified by the first column |
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a_0 is keyword in CSV_HEADER_START |
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a_0 : { .. a_n : { _header : [ fields.. ], _data : { field : value } |
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c) keys : as a tree - the rows must be unique identified by the first column |
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a_0 is keyword in CSV_HEADER_START |
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a_1 ... a_n is key characterized by header-field like _fk* or _pk* |
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a_0 : { .. a_n : { _keys : [ _fpk*.. ] , _header : [ fields.. ], _data : { pk_0 : { ... pk_n : { field : value } |
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""" |
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data = {} |
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header = [] |
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h = [] # from a[] |
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lines = utils.file_tool.readFileLines(msg, filename) |
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status = "start" |
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tableDict = {} |
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for l in lines: |
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print("lines "+l) |
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fields = l.split(CSV_DELIMITER) |
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@ -121,49 +140,64 @@ def getCsvSpec(msg, filename, type): |
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data[a[0]][a[1]] = fields[1] |
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continue |
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elif (a[0].lower() in CSV_HEADER_START): |
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# create deep structure a_0 ... a_n |
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print("tdata 136 CSV_HEADER_START "+str(len(a))) |
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if (status == CSV_SPECTYPE_DATA): |
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setSpecDict(msg, h, data, tableDict) |
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#CSV_SPECTYPE_DATA |
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#CSV_SPECTYPE_TREE |
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#CSV_SPECTYPE_KEYS |
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tableDict = {} |
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tableDict[B.DATA_NODE_HEADER] = [] |
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if type == CSV_SPECTYPE_DATA: |
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tableDict[B.DATA_NODE_DATA] = [] |
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else: |
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tableDict[B.DATA_NODE_DATA] = [] |
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#CSV_SPECTYPE_DATA |
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#CSV_SPECTYPE_TREE |
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#CSV_SPECTYPE_KEYS |
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# save header in separate structure |
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i = 0 |
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for f in fields: |
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i += 1 |
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if i == 1: continue |
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if i <= 1: continue |
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header.append(f) |
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status = CSV_SPECTYPE_DATA |
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h = a |
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continue |
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elif (status == CSV_SPECTYPE_DATA): |
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# check A-col for substructure |
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if (a[0] not in data): |
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data[a[0]] = {} |
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if len(a) == 1 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][B.DATA_NODE_DATA] = [] |
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# its a component |
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if len(a) > 1 and a[1] not in data[a[0]]: |
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data[a[0]][a[1]] = {} |
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if len(a) == 2 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]]["_data"] = [] |
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if len(a) > 2 and a[2] not in data[a[0]][a[1]]: |
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data[a[0]][a[1]][a[2]] = {} |
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if len(a) == 3 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]][a[1]][B.DATA_NODE_DATA] = [] |
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# fill data |
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row = {} |
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i = 1 |
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# case-differentiation DATA or TREE |
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for f in header: |
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row[f] = fields[i] |
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i += 1 |
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if len(a) == 1 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][B.DATA_NODE_DATA].append(row) |
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elif len(a) == 1 and type == CSV_SPECTYPE_DATA: |
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data[a[0]] = {f: row} |
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elif len(a) == 2 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]][B.DATA_NODE_DATA].append(row) |
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elif len(a) == 1 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]][B.DATA_NODE_DATA] = {f: row} |
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elif len(a) == 3 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]][a[2]] = row |
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elif len(a) == 1 and type == CSV_SPECTYPE_DATA: |
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data[a[0]][a[1]][a[2]] = {f: row} |
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if type == CSV_SPECTYPE_TREE: |
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tableDict[B.DATA_NODE_DATA][f] = fields[i] |
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if type == CSV_SPECTYPE_DATA: |
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tableDict[B.DATA_NODE_DATA].append(row) |
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if (status == CSV_SPECTYPE_DATA): |
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setSpecDict(msg, h, data, tableDict) |
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print("return getCsvSpec "+str(data)) |
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return data |
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def setSpecDict(msg, path, data, tabledata): |
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if len(path) >= 2 and path[1] not in data[path[0]]: |
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data[path[0]][path[1]] = {} |
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if len(path) >= 3 and path[2] not in data[path[0]][path[1]]: |
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data[path[0]][path[1]][path[2]] = {} |
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if len(path) >= 4 and path[3] not in data[path[0]][path[1]][path[2]]: |
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data[path[0]][path[1]][path[2]][path[3]] = {} |
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if len(path) == 2: |
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data[path[0]][path[1]] = tabledata |
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elif len(path) == 3: |
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data[path[0]][path[1]][path[2]] = tabledata |
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elif len(path) == 4: |
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data[path[0]][path[1]][path[2]][path[3]] = tabledata |
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pass |
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def readCsv(msg, filename, comp): |
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job = basic.program.Job.getInstance() |
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verify = -1+job.getDebugLevel("tdata_tool") |
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